Eindhoven University of Technology MASTER A ... · analyses the potential sustainability impacts as a result of a (re)arrangement of urban land uses in a densely built-up urban area

Eindhoven University of Technology

MASTER

A functionalistic approach for assessing sustainability impacts in an urban environmentthe development of a sustainability impact assessment model (SIAM) which systematicallyanalyses the potential sustainability impacts as a result of a (re)arrangement of urban landuses in a densely built-up urban area

Koops, J.

Award date:2012

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Where innovation starts

A functionalistic approach for assessing sustainability impacts in an urban environment

Jan Koops

2012Construction Management and Engineering

students are free to include a picture in the field above the title of your research - you can also use the back cover

A functionalistic approach for assessing sustainability impacts in an urban environment

The development of a sustainability impact assessment model (SIAM) which systematically analyses the potential sustainability impacts as a result of a (re)arrangement of urban land uses in a densely built‐up urban area.

Author: Jan Koops

Date: 23rd of August 2012

Graduation Committee:

Prof. dr. ir. Bauke de Vries (TU/e) Dr. Qi Han (TU/e) E. ten Dam (RHDHV)

Graduation Company:

Royal HaskoningDHV

Graduation Program:

Construction, Management & Engineering ‐ University of Technology Eindhoven

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Final Report, 23rd of August 2012

Master Thesis ‐ J. Koops.|3

Preface I am proud to present to you my final thesis: the product of several months of hard labor. Nevertheless I have enjoyed my time at Royal Haskoning to the fullest and I’m grateful for opening up their kitchen for me. The end result certainly meets my expectations. Hopefully, this will be the crowning glory of the work I’ve done over de past 2 years.

I would like to use the opportunity to thank several individuals who have contributed to the realization of my final thesis, directly or indirect. First of all, I would like to thank all the experts at Royal HaskoningDHV who have contributed to this by providing data or by participating in interviews. In my opinion, their input made this research a success. I would like to thank Ellis ten Dam and Martine Verhoeven in particular for supervising my research during the past 7 months.

Furthermore, a special word of gratitude for my brother and my parents who have supported me in every possible way imaginable. I would like to thank my brother for his hospitality, his advice and his critical view at my work and my parents for their unconditional support in varias areas. Last but not least, I would to thank my girlfriend for the all the moral support she has given me, for pushing me when I needed it and just for putting up with me….

I hope you will enjoy reading my final thesis.

Jan Koops

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Contents Preface .................................................................................................................................................................... 3

1. Research framework ........................................................................................................................................... 7

1.1 Time for Change ............................................................................................................................................ 7

1.2 Motive ........................................................................................................................................................... 8

1.3 Problem Analysis ......................................................................................................................................... 10

1.4 Problem Statement ..................................................................................................................................... 11

1.5 Research Questions .................................................................................................................................... 11

1.5 Research Objectives ................................................................................................................................... 12

1.6 Research Approach ..................................................................................................................................... 12

1.7 Research Relevance .................................................................................................................................... 13

1.8 Research Delineation .................................................................................................................................. 14

1.9 Royal HaskoningDHV .................................................................................................................................. 14

1.10 Guide ......................................................................................................................................................... 14

2. Sustainable development .................................................................................................................................. 15

2.1 The Genesis of Sustainable Development .................................................................................................. 15

2.2 Understanding Sustainable Development .................................................................................................. 16

2.3 The Triple Bottom Line ............................................................................................................................... 16

2.4 Sustainable Urban Development ................................................................................................................ 17

2.5 The relevance of scale ................................................................................................................................ 18

2.6 Concretizing Sustainable Development ...................................................................................................... 19

2.7 Sustainability Themes and Aspects ............................................................................................................. 20

2.8 Conclusions ................................................................................................................................................. 23

3. Functional Diversity and Sustainable Development ......................................................................................... 25

3.1 Urban Land Uses ......................................................................................................................................... 25

3.2 Functional Diversity .................................................................................................................................... 25

3.3 History Functional Diversity ........................................................................................................................ 27

3.4 The usefulness of Functional Diversity: Opportunities en Threats ............................................................. 28

3.5 Functional diversity in urban planning practice: search of synergy ........................................................... 30

3.6 Influential Variables .................................................................................................................................... 30

3.7 Conclusions ................................................................................................................................................. 33

4. Sustainability Impact Assessment ..................................................................................................................... 35

4.1 Sustainability Impact Assessment Model (SIAM) ................................................................................ 36

4.2 Selected sustainability aspects ............................................................................................................ 38

4.3 Model inputs ........................................................................................................................................ 40

4.4 Sustainability Impact Calculation ......................................................................................................... 45

4.5 Model Outputs..................................................................................................................................... 54

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4.6 Conclusions .......................................................................................................................................... 56

5. Data collection & Analysis ............................................................................................................................ 59

5.1 Data collection ..................................................................................................................................... 59

5.2 Data review .......................................................................................................................................... 60

5.3 Data Analysis ....................................................................................................................................... 63

5.4 Scale factor determination .................................................................................................................. 65

5.5 Conclusions .......................................................................................................................................... 66

6. The utilization of SIAM ................................................................................................................................. 67

6.1 Simulating functional intermingling .................................................................................................... 67

6.2 Case Study: Europoint Rotterdam ....................................................................................................... 70

6.3 Project data ......................................................................................................................................... 71

6.4 The Alternatives ................................................................................................................................... 73

6.5 Results ................................................................................................................................................. 74

6.6 Conclusion ........................................................................................................................................... 77

7. Conclusion and Recommendations .............................................................................................................. 79

7.1 Conclusions ................................................................................................................................................. 79

7.2 Recommendations ...................................................................................................................................... 81

References ............................................................................................................................................................ 83

Literature: ......................................................................................................................................................... 83

Expertise ........................................................................................................................................................... 86

Summary ............................................................................................................................................................... 87

Appendices ............................................................................................................................................................ 89

Appendix I: Scenario Output Sheet ................................................................................................................... 90

Appendix II: Sustainability Aspects Reduction .................................................................................................. 91

Appendix III: Sustainability Impact Matrices .................................................................................................... 94

Appendix IV: Parcel ID Map ............................................................................................................................ 105

Appendix V: Land Use ID Table ....................................................................................................................... 106

Appendix VI: Detailed Alternative Comparison Sheet .................................................................................... 107

Appendix VII: Detailed Subject Floor Output Sheet ........................................................................................ 108

Appendix VIII: AHP Weight Calculation Overview .......................................................................................... 109



1. Research framework

In this chapter the research subject and method is introduced and justified. This chapter starts with a subject introduction and the motive for doing research on this specific subject. Subsequently, the research problem & research questions, the research objectives and the research will be addressed. This chapter ends with subject delineation and a reader guide.

1.1 Time for Change Economic, demographic, social and environmental developments have become the base for changes in urban development. Some of these are expected to be only temporarily like the economic and financial crisis although these economic development will leave lasting scarves in future urban planning. Other developments will lead to structural changes. Demographic changes for instance like population shrinkage and stabilization of the population growth in Western Europe, the growing attention for the environment and sustainability, and the growing participation of the well‐informed citizens in urban development will lead structural changes in urban development (Laglas, 2011). Urban development is under pressure and the real estate and construction sector are struggling to cope with this new situation. On a global level these developments are an important motive for change (Ministerie van Infrastructuur en Milieu, 2011).

In urban development the emphasis was placed on new developments over the last decades. Construction of new office buildings, new business areas and new infrastructure was easy, quick and generated financial means to reinvest in other new developments. This cycle has now been terminated as a result of recent financial and socio‐economic developments (Ministerie van Infrastructuur en Milieu, 2011).

After World War II, the urban development market could be characterized as purely supply‐driven. Real estate in all sectors was developed for a conceited market and participation of the end‐user in the development process was very limited (FGH, 2011). The current market in the Netherlands now faces the consequences. The reluctance to adapt development strategies to a changing market situation resulted in a significant amount of stock which does not meet the current user’s needs and demands and lacks flexibility to be adapted to the changed demands without huge investments. The consequences are evident throughout several sectors of the real estate market. First of all, degenerated neighborhoods build in the postwar period are in need of renovation, or will even have to be torn down (FGH, 2011). Approximately 220 thousand dwellings will be withdrawn from the housing stock in the period 2010‐2019 (ABF Research, 2010). Second, deteriorated industrial areas require huge investments in order to be adjusted to meet current demands. An estimated acreage of 15.800 hectares needs to be redeveloped before 2020 (Ministeries van VROM, EZ en IPO, 2009). Third, the office market faces an enormous amount of vacancy. About 7 million of square meters of office space are currently vacant, about 14 percent of the total stock (NVM). This percentage is expect to increase to 50 percent over the next 20 years as a result of decreasing labor force, technology innovations and the introduction of a new way of working (Haijer, 2011). And finally, the retail market faces a vacancy percentage of 9 percent (Evers, 2011). Evidently, the renovation and redevelopment task is huge throughout

8| Chapter 1. – Research Framework

all real estate sectors. Consequently, a shift in urban development is much needed from development to management and maintenance to tackle this complex challenge.

Despite the emphasis on this new focus on management and maintenance, there will be still a development task ahead of us in several sectors and in specific regions. In the Randstad‐area e.g. an estimated 750 thousand houses will have to be build in order to meet future demands in the period 2010‐2019 (ABF Research, 2010). And even in the highly saturated office market a demand for newly build office will continue to exist, although in a slimmed‐down form (FGH, 2011). Urban developers and planners now face the challenge to prevent future generations from facing similar problems as result of another social or economic development.

It’s time for change. Dwellings and commercial real estate are no longer the engine of urban development. Investments in accessibility, water, energy, education and health care might take over this central role in urban development. These will be the new value creators in urban development. (Franzen & De Zeeuw, 2011)

Exploitation should be based upon continuity and long term value development from now on, allowing real estate and urban areas to grow along with changing demands, resulting in future‐proof urban development. The value of real estate and its surroundings will be related to flexibility and sustainable design and its prolonged exploitation. The focus will shift from quantity to quality (Agentschap NL, 2011). Continuity and flexibility are key factors in sustainable urban development. Sustainability will no longer be a distinctive factor; sustainability will be raised to standard (FGH, 2011).

1.2 Motive “Intricate mingling of different uses in cities is not a form of chaos. On the contrary, they represent a complex and highly developed form of order. “

Jane Jacobs (1961)

The quote above (Jacobs, 1961) concerns an important criterion for future‐proof urban developments. Jane Jacobs, an American‐Canadian writer and city activist, already advocated for diversity back in the sixties. Jacobs argued that it is all about the keen integration of different building types and uses, residential and commercial, old and new, to create urban vitality. According to this idea, cities depend on the diversity of cities, residences, business and other non‐residential uses, as well as people of different ages using areas at different times of the day. The intermingling of city uses and users are critical to economic and urban development according to Jacobs.

Jacobs interpreted urban areas as living eco‐systems. Jacobs suggested that on the long term buildings, public domain, streets and neighborhoods functions as dynamic organisms, much like a natural eco‐system.

Urban developing methodology needs to be reinvented (FGH, 2011). Jacob’s view on urban development is getting more and more acknowledgement in doing so. The analogy concerning eco‐systems and urban systems, initiated by Jacobs, is also acknowledged in more recent literature. Epema et al. (2011) describes resilience as one of the most powerful



characteristics of an ecosystem, a characteristic which is lacking in urban systems. Ecosystems are able to create conditions for viability: the resource loops are largely closed; diversity in species preserves the system; and synergy and symbiosis are important system principles. Based on nature’s principles Epema et al. developed their strategy for evolutionary value creation. Diversity is seen as a precondition for survival, similar to an ecosystem. A sophisticated mix of urban functions results in a viable urban environment (Buma, 2011).

User’s demands and requirements have a limited shelf life and socio‐economic developments follow up each other rapidly. Elasticity is needed at different scale levels in urban development to prevent future generations from facing similar problems of deterioration, degradation and vacancy. Diversity is off the essence to generate this much needed elasticity in urban areas. Intermingling between urban functions will result in urban resilience, enabling urban areas to resolve from socio‐economic developments (Ten Dam, 2011).

One of the essences of urban development is combining urban functions such as living, working and recreating. Functional diversity in urban areas is a precondition for connecting functions. Combining functions perhaps seems to be obvious but ever since the emergence of CIAM early last century, Dutch Planning applied principles of functional segregation, like zoning and contours (Franzen and De Zeeuw, 2009). A shift to a more service‐oriented economy in recent years in the Netherlands allows function mingling (VROM‐Raad, 2010).

Function mingling contributes to future stability of an area, allowing an area to adapt continuously to future developments. Combining functions offers opportunities for creating added value; e.g. combining parking with water storage or the concurrence of green, water, recreation and real estate. Cities which are able to offer an attractive location for settlement and which succeed in exploiting agglomeration advantages have a bright future. Quality of working and living, of education, training and development and of physical and social connections and interactions are decisive competitive advantages. The interactions between urban functions offer opportunities for creating additional added value (Ministerie van Infrastructuur en milieu, 2011). Combining function might generate a multiplier effect: the combination of functions yields more than the sum of the autonomous parts (Agentschap NL, 2011).

Sustainable development has become a central theme in urban planning all over the world in the recent years. (Re)positioning functions will contribute creating a more sustainable and future‐proof build environment (VROM‐Raad 2010). Red, green and blue functions should be positioned in such a way that it yields sustainable profit. Interrelationships between functions should strengthen socio‐cultural, economic and ecological values for concerned stakeholders. The values of these stakeholders should be connected in order to create synergy. Smart urban development prevents undesired impacts and establishes connections between stakeholder values in order to create mutual gains (Nirov, 2011).

Every location owns region‐specific characteristics which offer offers opportunities for creating win‐win situations: industrial areas offer opportunities for residual heat exchange and cascading, nature and agricultural areas deliver bio mass, and on business areas multiple land use might be interesting.


In practice, the attention for sustainable development is often narrowed down to only one of the three pillars, usually the ecological pillar. Sustainable development is often translated in all sorts of environmental measures, for example in the field of energy or carbon reduction. A broad approach is necessary in order to come to integral sustainable development (VROM‐Raad, 2010).

1.3 Problem Analysis The spatial interaction between urban functions can be positive and negative (Taleai et al., 2006). The interaction between functions often results in multiple effects in various fields. Kong et al. (2006) explored the relationship between green spaces and house prices and confirmed the positive amenity impact of proximate urban green spaces on house prices; an positive economic effect. Kong et al. only focused on one specific effect of functional mingling in an urban area, limiting their scope considerably. Additional externalities of green spaces in urban areas were disregarded, like contribution of urban green spaces to air quality, viability, water regulation and biodiversity. By narrowing down the research to one specific research aspect undesirable side effects might be overlooked. Green area might have negative influence on the feeling of safety or the social control. An integral methodology is needed to consider the total impact of interacting urban functions on ecological, economical and socio‐cultural values.

The narrow approach seems to have the upper hand in scientific research about sustainable urban development. Consequently, a sub‐optimal outcome arises as a result of a strong focus on a single sustainable aspect (Ministerie van Infrastructuur en Milieu, 2011). This focus in this narrow approach is often placed on the ecological interest (Nirov, 2011). Re‐embedding of the ecological interest is needed (VROM‐Raad, 2010). A prospective sustainable ecological future is not conceivable without well‐balanced socio‐economic ratios which meet up to the sustainable ambitions to the upmost. Ecological and socio‐economic interest need to be addressed in relation to each other.

Approaches in sustainable urban development can either be defensive or offensive. Taleai et al. (2006) developed an integrated approach for assessing the compatibility of urban functions from a defensive perspective, aiming at minimizing negative, spatial interaction. The main focus is prevention of offloading negative impacts. Economic growth should not be pursued at the expense of e.g. ecology. Neither should future generations face the consequences of contemporary actions and policies.

Nowadays a bigger ambition has emerged: striving for reciprocal gains. This offensive approach seeks for synergetic urban functional combinations: solution which allows economic, ecological and socio‐cultural added value. Such an approach aims at linking values at different levels.

A systematic analysis of possible synergetic solutions by (re)positioning functions in an urban environment is missing. The challenge is to comprehend the effect of possible function combinations on economic, ecological and socio‐cultural values in relation to each other.



1.4 Problem Statement The added value of functional diversity and the opportunities offered by intermingling of urban land uses is widely acknowledged. As described earlier Dutch urban planning departments have handled a defensive approach when it comes down to urban development, resulting in concepts as zoning and contours based on strict separation of urban functions. Nowadays is argued for a more offensive approach aiming at striving for reciprocal profits by combining urban functions. In literature research on this topic seems to be conducted only in a narrow sense, focusing on a single sustainable (often ecological) profit. A more integrated approach is needed which systematically investigates the possible sustainable gains as a result of specific function combinations which meet economic, ecological and socio‐cultural values.

This research aims at filling this gap and providing a tool which generates insight into the potential sustainable profit as a result of a certain configuration of urban functions in a specific urban context. The problem statement can now be defined as followed:

Dutch planning and designing tend to apply defensive and narrowed approaches when it comes down to function allocation in urban development. An offensive and more integrated approach is needed which systematically investigates potential added value to a sustainable urban environment as result of (re)arranging urban functions.

1.5 Research Questions The primary research question is formulated as follows:

“Does intermingling of urban land uses contribute integrally to creating a sustainable urban environment and how could the resulting (potential) sustainability impacts be analyzed systematically within a specific urban context?”

The following secondary research questions should be answered in order to answer the main research question:

A. Secondary questions regarding sustainable development: 1) What is sustainable development? 2) In what way could sustainable development be measured? 3) Which criteria are considered in sustainable development and are these

criteria interrelated?

B. Secondary questions regarding functional diversity in relation with sustainable development:

1) Which land use categories can be recognized in sustainable development? 2) What is the meaning of functional diversity? 3) What is the use of creating functional diversity within an urban context? 4) Which external variables influence potential sustainability impact initiated by

(re)arranging urban functions ?


C. Secondary questions regarding analyzing the potential added value for realizing a sustainable urban environment:

1) In what way could sustainability impacts as a result (re)arranging urban land uses be analyzed systematically?

2) How much do particular function combinations contribute to each of the sustainability criteria?

3) Which singular combinations of land uses have the highest potential for contributing to a sustainable urban environment as result of (re)arranging urban functions?

4) Can functional diversity indeed be considered as a precondition for creating a sustainable urban environment?

1.5 Research Objectives The research has multiple research objectives. First, this research should provide insight in to what extent functional diversity contributes to a sustainable environment. Second, the research should provide insight in fertile urban function combinations for creating functional synergy which implies realizing and balancing sustainable added value for multiple sustainability aspects. Third, this research provides a solution for analyzing sustainable profit systematically. Finally and most importantly, this research will result in a tool which analyses the feasible sustainable added value in a specific urban context as a result of functional diversity systematically, and visualizes this feasible profit for the concerned stakeholders. Opportune synergetic scenarios will be mapped out.

Furthermore, the tool aims at operationalizing this functionalistic approach of sustainable development giving insight into the overall potential added value and what this added value is composed off. In other words, this outcome of this research will give an indication of the feasible added value for each of the parts off sustainable urban development as well as for the sum of the parts. Such a tool analyzes (re)development projects from a (functionalistic) sustainable perspective and will generate new ideas for concerned stakeholders.

1.6 Research Approach The research model, as illustrated in the diagram on the next page, consists of 4 phases: Research, Modeling Design, Data Collection and Data Processing and Modeling.

In the research phase the foundations will be laid for the modeling tool. Desk research and expert Interviews will deepen the concept of sustainable development, providing a better understanding of the underlying principles and providing insight in the criteria sustainable development addresses. In short, this part of the research will answer sub‐questions concerning sustainable development in general.

The second part of this first phase, functional diversity and functional synergy in urban development is researched using an in‐depth literature research and expert interviews. This should result in insight in the importance of functional diversity in sustainable urban development, possible fertile singular combinations of urban land uses, and aspects influencing the degree of sustainability impacts as a result of combining urban function. This research should provide answers to sub‐questions about functional synergy. Furthermore,



desk research should provide insight in possibilities for analyzing and calculating the impact of (re) arranging urban functions systematically (C1).

The output of the first phase will be the main input for the second phase, the modeling design phase. In this phase will be determined what the final tool will look will look like, which criteria and external variables will be incorporated in the sustainability calculation process for the tool and a sustainability compatibility breakdown structure will be created giving an overview of all the sustainability aspects influenced as a result of (re)arranging functions. Finally, required input from experts is decided upon and questionnaires for gathering this input will be designed. The actual data collection is done in the third phase.

In the fourth phase the gathered data is analyzed and processed into the final model which should be a tool for providing insight into sustainability impacts as a result of a specific configuration of urban functions. This research is concluded with data analysis and model testing. The process plan is schematically visualized in figure 1.2 which also indicates which parts will give answer to which (secondary) questions highlighted in red.

Figure 1.2: Research approach visualized

1.7 Research Relevance The research relevance is already described in detail in the introduction and will be shortly recapped in this paragraph. Urban development is to be redevelopment. Many researchers have argued for urban diversity to create a vital urban environment. Combining urban land uses will create opportunities for realizing sustainable added value. In scientific papers researchers primarily choose for the narrow approach, focusing on a specific combination of two urban functions and/or on a particular effect. A broadened approach is needed which systematically visualizes the feasible sustainable profit as a result of spatial configuration of functions in an urban context.

This research aims at developing a systematic approach for visualizing feasible sustainable added value as a result of (re)arranging urban functions. Such a tool might be useful in the start‐up phase of urban development projects. In the project definition phase this tool might assist in defining the program of requirements from of functionalistic and sustainable perspective. And in the (preliminary) design phase this tool might assist in positioning functions. Both the functionalistic program of requirements as the positioning of the functions in relation to each other will influence the feasible sustainable added value.


1.8 Research Delineation Sustainable development is obviously a very broad concept. When addressing such a broad concept in a research like this delineation is essential.

First of all, the scope of this research will be limited to the Dutch situation although the urgency of sustainable development is globally recognized nowadays. Urban development will require different approaches since each country has different characteristics. The functionalistic approach addressed in this research suits the Dutch situation because of its distinctive high building density. Space scarcity has urged the Dutch government to forge underlying departments to focus on densification in urban policies. The resulting high density can be regarded as an essential precondition for operationalizing this functionalistic approach.

Second, as will be described in chapter 2.6, the approach needed in this matter depends on the scale level on which it will be applied. Consequently, the research will focus on developing a functionalistic approach on district level as will be explained in the aforementioned chapter.

Third, allocation of functions in urban areas is prescribed in the Netherlands in land use plans limiting the number of functions in a specific area or on a specific plot. This research assumes no limitations when it comes down to function allocation.

Fourth and finally, the success of implementation of this functionalistic approach highly depends in practice on the willingness to cooperate of concerned stakeholders. For the sake of convenience, the preparedness to cooperate falls outside the scope of this research. However, the influence of stakeholders’ requirements and values is certainly recognized and will be incorporated in the tool development.

1.9 Royal HaskoningDHV This research is executed at Royal HaskoningDHV, a company which is the result of a recent merger between Royal Haskoning and DHV. The employees of Royal HaskoningDHV works annually on more than 30.000 projects in the field of planning, transport, infrastructure, water, maritime, aviation, mining and buildings. Consequently, Royal HaskoningDHV can be seen as a fully‐filled well of knowledge in many areas. This research requires input from experts with different backgrounds and expertise and can therefore be considered as the ideal location for executing this research.

1.10 Guide The next section starts with the results of the desk research about sustainable development and functional diversity. In chapter 4 the tool is introduced and explained extensively. Subsequently, the date collection and analysis is described in chapter 5, presenting some interesting results. In chapter 6 the developed will be tested and applied in a case study. This reports ends with conclusions and recommendations



2. Sustainable development

In this chapter the concept of sustainable (urban) development in detail and will give more insight in this broad concept within the urban environment. Firstly, the history of sustainable development is addressed, highlighting the origin and the urgency of sustainable development. Next, the definition of sustainable development is explained in more detail, followed by the relation with urban development resulting in a better understanding of sustainable urban development. Finally, the vague concept of sustainable development is concretized by introducing sustainable development measures.

2.1 The Genesis of Sustainable Development Sustainability was first introduced by the Club of Rome who published the report Limits to Growth (1972). Triggered by environmental disasters (like acid rain, deforestation and oil disasters) the Club of Rome revealed exhaustion issues by comparing the economy and population growth to the available finite resources. Although widely criticized, the report initiated ecological awareness all over de world.

The Brundtland commission, named after the chairman of the World Commission of Environment and Development created by the United Nations in 1983, took ‘sustainability’ to the next level by integrating ecological values in new models of social advancement.

The World Commission of Environment and Development expanded the Limit by Growth‐thinking of the Club of Rome with the challenge for developing a new type of responsible growth integrating ecological, economic and social values. The term Sustainable Development which was introduced and defined as:

“Sustainable development is development that meets the needs of the present without compromising the ability of future generations to meet their own needs.” (World

Commission of Environment and Development, 1987)

The concept of sustainable development has been elaborated further ever since the publication of the report of the Club of Rome and the Brundtland Commission, but the concept of sustainable development remained abstract (Dorst, 2005). Consequently, a integral political agenda has never been reached. Al Gore’s An Inconvenient Truth (Gore, 2006) reinforced the position of sustainable development on the political agenda by exposing the climate change our planet faces as a result of elevated levels of greenhouse emissions (Bouwfonds Ontwikkeling, 2009).

Most recently, the urgency for sustainable development was emphasized in the Living Planet Report (Wereld Natuur Fonds, 2010) which explored the ecological footprint of mankind. The WNF calculated that with an unchanged policy calculated in their business as usual‐scenario three times the planet earth is needed to support our current lifestyle. The urgency for sustainable development is thus beyond dispute.

16| Chapter 2. – Sustainable Development

2.2 Understanding Sustainable Development The definition of the Brundtland Commission for sustainable development described in the previous paragraph is still widely approved and the most quoted definition for sustainable development in literature. In this paragraph the concept sustainable development is examined more thoroughly.

The goal of the Brundtland commission by introducing the concept of sustainable development was to increase the amount of people living a decent live and this quality of live level will be maintained for future generations. The concept of sustainability has a geographical and a time dimension (Dorst, 2005). The definition implies on the one hand a decent live for growing part of mankind meaning a distribution of prosperity from here to elsewhere. On the other hand the definition aims at preventing offloading to next generations, describing a now and later. This part of the definition clearly tries to incorporate a long term vision, safeguarding the quality of live for future generation.

Figure 2.1: here and now vs. elsewhere and later (Roorda, 2010)

This concept of here and now versus elsewhere and later is illustrated in figure 2.1. The here and now covers the utility and experiential value, in other words value which meet current demands. The elsewhere and later addresses the future value: developments should be future‐proof safeguarding the quality of live for future generations (Puylaert & Werksma, 2011).

The focus on offloading issues makes the concept of sustainable development particularly interesting for urban planners and developers who currently face the challenge to prevent future generations from facing similar urban issues, such as deterioration of urban areas and high vacancy levels, as described in chapter 1.

2.3 The Triple Bottom Line Sustainable development is the art of connecting people, planet and profit (Ministerie van Infrastructuur en Milieu, 2011b). John Elkington leveraged the phylosophy of the Brundtland Commission and introduced the Triple Bottom Line: People, Planet & Profit (Elkington, 1998). Elkington describes sustainable development as finding a balance between the three pillars people, planet and profit.



Figure 2.2 The three pillars of the Triple Bottom Line

According to Elkington companies should not only be jugded on profitability, but also on their contribution to social justice and ecological quality. People represents the socio‐cultural dimension, Planet represents the ecological dimension and Profit represents the economic dimension. Elkington describes sustainable development as finding a balance between the three pillars people, planet and profit.

Later on, the term Profit was replaced by the broader concept Prosperity in several publications. Prosperity is a broader concept that not only addresses the profitability of companies but also the economic and financial concerns of individuals and of countries.

2.4 Sustainable Urban Development In the legacy of Elkington’s Triple Bottom Line sustainable urban development could be defined as a balance between People, Planet and Profit in the spatial domain. Elaborating on this theory, Werksma entitled urban development as being sustainable when the social component and the spatial component reinforce each other and when this results in spatial quality (Werksma, 2002).

A sustainable urban development should add value to each of the three P’s without causing an imbalance between the P’s. An added value is sustainable when meeting the needs of the current users in the ‘here and now’ without jeopardizing the ability of future generations their needs in the ‘elsewhere and later’. Kees Duijvestein, pioneer in the field of sustainable building, connects the three P’s with the spatial domain which should result in spatial quality. Duijvestein therefore developed the sustainability‐tetrahedron adding a fourth P which stands for Project (Duijvestein, 2002).

According to Werksma (2002) utility value, experiential value and future value form the three pillars for spatial quality, which are derived from Vitruvian Triad (utilitas, firmitas, venustas). Utility value represents the functional use of an urban area. The experiential value refers to a subjective experience of an urban area in the present. Future value concerns the appreciation of spatial functions through time. These three pillars together determine the spatial quality. Utility value and experiential value represent the ‘here and now’ and future value incorporates the ‘elsewhere and later’.


Elkington describes sustainable development as finding a balance between the three pillars people, planet and profit. For sustainable urban development, in addition, also a balance between people, planet & profit, a balance also have to be found within the spatial component, between utility value, experiential value and future value (VROM‐raad, 2011). The relation between the social and spatial component is depicted in figure 2.3 which illustrates that the common denominator of the two tetrahedrons is spatial quality.

2.5 The relevance of scale Spatial planning knows different scale levels and each scale level requires a different approach. In this paragraph two different scale levels will be addressed: spatial development at structure level and spatial development at area level (Ministerie van Infrastructuur en Milieu, 2011b).

In spatial development at structure level – usually captured in a structure vision in Dutch practice – it’s about areas and places, about flows and structures, and about demand and functions. The quality of areas, including flows and structures make up the playground for spatial development at this level. The identity of an area is often an important starting point. The challenge at structure level is to provide a place to demands and functions in conjunction in order to create sustainable urban quality. At this level boundaries are set for developments at smaller scales with special focus on the interrelationship between urban areas. Governments play a central role at this level by setting the boundaries for urban developments. Plans are usually plotted for the long term at this scale level.

At the second scale level, it is about the development of areas, and is called urban development. The realization of a change in the urban environments is the main challenge in urban development. This changes need to be implemented within the boundaries set at the overlying structure level. The process is characterized by collaboration between public and private parties. Sustainable urban development at area level is about adding values and quality to these areas and safeguarding these values and qualities for the future.

Although both scale levels are interconnected, different approach are required for each of the scale levels. At structural level, places should be interlinked while complying with flows of people, energy, information, sources, water, waste, etc. The spatial organization of urban spaces runs via the interlinkage of these flows. And these flows are influenced in turn by the quality of spaces: the attractiveness, the identity and functionality of spaces determine the course of the flows. An adequate flow and space management can contribute to a sustainable environment by interconnecting spaces and flows (VROM‐raad, 2010). Tjallingii and Jonkhof (2011) investigated flow management and succeeded in finding synergetic solution between different flows.

Figure 2.3 the spatial and the social component within urban development (Puyleart & Werksma, 2011)



At the lower scale level another approach is required. At area level the challenge is to find the right combination and configuration of urban land uses. This will result in an improved quality and identity of a place. At this level is essential to analyze an area extensively in order to be able to make the right choice for intervening. Sophisticated (re)positioning of urban functions will result in sustainable added value in terms economic, ecologic and socio‐cultural values (VROM‐raad, 2010). An integral approach is essential for succeeding in sustainable urban development. The consequences for people, planet and profit of an intervention need to be investigated thoroughly.

2.6 Concretizing Sustainable Development One of the disadvantages of an integral approach for sustainable development is that it tends to become abstract because it takes everything into account. The abstract concept of sustainable development becomes even more vague when it is described it in soft terms of happiness, well‐being and freedom. So, how to measure sustainable development? In literature several attempts have been made concretize sustainable development.

The Capitals Approach was developed to give more substance to the concept of sustainable development. This approach is based on the Triple Bottom Line and distinguishes three capitals: the ecological (planet), the socio‐cultural (people) and the economical capital (profit). Sustainable development implies improving each of the capitals without creating growth of one capital at the expense of another.

Each capitals is still rather vague and complex and are therefore decomposed into so‐called stocks (Telos, 2011) as depicted in table 2.1. Next, indicators have been allocated to each of the stocks in order to make the stocks, capitals, and thus sustainable development measurable (Telos, 2006).

People Planet ProfitSocial participation Soil spatial establishment conditions

Health Air Capital

Art and Culture Nature Knowledge

Living Environment Surface water Energy, Natural Resources

Safety Ground water Labor

Education Landscape Economical Structure

Economical and Political

Participation

Infrastructure and Accessability

Table 2.1 Capitals and Stocks (Telos, 2011)

Hooijmeijer et al. (2001) went one step further by developing a framework in which requirements in spatial requirements (utility value, experiential value and future value) have been interlinked to social, cultural, ecological and economic interest. This is basically a combination of the Triple Bottom Line and the Vitruvian Triad resulting in a matrix with twelve characteristics for spatial quality. The result is matrix with requirements and values on the axes as illustrated table 2.2.


Economic Social Ecological

Utility Value Functionality: Availability: Viability:

Multi‐purpose Services Clean

Accessability Safe

Healthy

Experiential Value Attractiveness: Vitality: Diversity:

market value function diversity variation in landscape and

species

livelyness

Future Value Flexability: Stability: Robustness:

Adaptability Preventing abrupt

changes

Stable Structures

Table 2.2 Matrix Sustainable Spatial Quality

The Vitruvian Triad is translated by Hooijmeijer et al. into utility value, experiential value and future value. But several options for creating a division based on the Vitruvian Triad seem to be conceivable.

Royal Haskoning works with a slightly different division using a technical value instead of future value (Royal Haskoning, 2011). Epema et al. (2011) distinguishes a utility value in which the experiential value is incorporated and a system value which similar to the technical value of Royal Haskoning.

2.7 Sustainability Themes and Aspects Sustainability and urban development are in inextricable connected nowadays. Sustainability has been raised from ambition to standard over the recent decade. Stakeholders involved in the development of urban areas attach great value to sustainable buildings and a sustainable environment. Consequently, a need has arisen to measure sustainability on both building and area level. At area level several labels have been developed in order to measure and classify sustainability. The main labels applied in urban development in the Netherlands are BREEAM, LEED and GPR Stedenbouw. Another tool is DPL, which was developed as a communication, ambition and monitor tool to measure and provide insight in the degree of sustainability in an urban area. The three labels and DPL are briefly elaborated below.

GPR Stedenbouw is a complement to GPR Gebouw, an instrument which has become leading Nederland over de last decade was developed by a consultancy firm in cooperation with several municipalities. GPR Stedenbouw provides insight to the user in aspects of sustainability and sustainability performances in an urban area. GPR Stedenbouw visualizes several sustainable aspects: energy, spatial lay‐out, health, utility value and future value. GPR is developed as evaluation tool (W/E Adviseurs, 2011).

BRE Environmental Assessment Model (BREEAM) was developed by the Building Research Establishment (BRE). BREEAM is a tool for analyzing and improving the environmental performance of offices. BREEAM‐NL Gebied is derived from BREEAM but focuses on the sustainable performance of entire urban areas. The evaluation framework compiles 6 categories: sources, spatial development, urban climate, well‐being, management and synergy (DGBC, 2011).



LEED stands for Leadership in Energy & Environmental Design. This tool is developed in 2000 and was based on BREEAM. LEED distinguishes primary requirements, basic requirements and innovation aspects. LEED evaluation the following aspects: urban design, water efficiency, energy & climate, materials & resources, internal climate and innovative usage (USGBC, 2006).

DPL stands for DuurzaamheidsProfiel van een Locatie which means Sustainability Profile for a Location. DPL was developed as a communication, ambition and monitor tool to measure and provide insight in the degree of sustainability in an urban area. DPL is – contrary to GPR Stedenbouw, BREEAM and LEED – not a label but a tool for measuring sustainability of urban areas by comparing it to reference areas. The purpose of this tool is to provide insight in the strong and weak points of an urban area. DPL uses indicators to concretize sustainability and elaborates sustainability in terms of People, Profit and Planet.

Several sustainability themes, aspects and indicators form the basis for each of these instruments. The interrelationships between these three elements are depicted in figure 2.4. Themes are composed of aspects, aspects are in turn composed of indicators. By measuring or rating these indicators the performance on aspects and theme level can be determined.

The basic principle of each of the instruments is very similar. Scores in the field of each of the sustainability theme or aspect are accumulated to get an overall score. Weight factors allocated to each of the aspects affect the final outcome.

Figure 2.4 Sustainability themes, aspects and indicators

Table 2.3 depicts an analysis compiled by comparing the four instruments resulting in an overview of which sustainability aspects are incorporated in which instruments. The main purpose of analyzing these instruments is to get a clear and complete overview of aspects considered in measuring sustainability in urban development, therewith concretizing the concept of sustainable urban development. The analysis resulted in a list of in total 15 themes and 33 aspects. The sustainability aspects are allocated to overlying sustainability themes in order to provide structure therewith enhancing susceptibility. Furthermore, the sustainability themes and underlying aspects have been subdivided using a combination of the triple bottom and the Vitruvian triad according to the principle introduced Hooimeijer et al. (2001), as described above.


Sustainability

Capitals

Devision based on the

Vitruvian Triad Themes Sustainability Aspects BREE

AM

LEED

GPR Sted.

DPL

A. Resources X X X Xa1 Energy X X X Xa2 Material X X Xa3 Food X Xa4 Water X Xa5 Waste X X

B. Environmental Quality X X X Xb1 Air X X Xb2 Surface Water X X Xb3 Soil X X

C. Diversity X X X Xc1 Abiotic Structure X Xc2 Ecological Value X

D. Sustainable Living and Building X X X Xd1 sustainable living and building

E. Accessability to Social Services and Recreational facilities X X Xe1 Accessability to Social Services and Recreational facilities X

F. Availability Grenery and Water X X X Xf1 Accessability Grenery and water X X X X

G. Safety X X Xg1 Social Safety X Xg2 External Safety X X Xg3 Traffic Safety X

H. Convenience & Nuisance X X X Xh1 Noise nuisance X X Xh2 Smell nuisance X Xh3 Wind nuisance Xh4 Heath nuisance X Xh5 Light nuisance X Xh6 Insolation X Xh7 Water nuisance X X

I. Area and Identity X Xi1 Area and Identity X X

J. Social Cohesion X Xj1 Social Cohesion X X

K. Space and Land usage X X Xk1 space and land usage X X X

L. Sustainable Transportl1 Sustainable Transport X X X X

M. Economic Atrractiveness X X Xm1 Loval Economic Diversity X Xm2 Local Employment X X Xm3 Accessability Xm4 Quality perception area X

N. Flexability X Xn1 Flexibility X X

O. Economic Vitality X Xo1 Economic Vitality X X

Planet

Future Value

Utility Value

Experiential Value

Future Value

Future Value

Utility Value

Experiential Value

Experiential Value

Utility Value

People

Profit

Table 2.3 Sustainable themes and aspects



2.8 Conclusions In this chapter, the concept of sustainable urban development is introduced and extensively discussed. In doing so, answers have been found to all secondary questions regarding sustainable development:

1) What is sustainable development? 2) In what way could sustainable development be measured? 3) Which criteria are considered in sustainable development and are these

criteria interrelated?

The Brundtland commission answered the first question by introducing and defining sustainable development as “Sustainable development is development that meets the needs of the present without compromising the ability of future generations to meet their own needs.” (World Commission of Environment and Development, 1987). This definition dates from 1987 but is still widely excepted today.

For measuring sustainable development at area level several labels have been developed in order to measure and classify sustainability. The main labels applied in urban development in the Netherlands are BREEAM, LEED and GPR Stedenbouw. Another tool is DPL, which was developed as a communication, ambition and monitor tool to measure and provide insight in the degree of sustainability in an urban area.

An comparison of the four instruments provided a clear and complete overview of aspects considered in measuring sustainability in urban development, therewith concretizing the concept of sustainable urban development, as illustrated in table 2.3. Each of these aspects have been allocated to people, profit or planet, and to utility value, experiential value or future value based on the principle introduces by Hooijmeijer (2011). This categorization indicate how each of these aspects are interrelated.

24| Chapter 3. – Functional Diversity and Sustainable Development



3. Functional Diversity and Sustainable Development The previous chapter introduced the concept of sustainable development in a spatial context. This requires an integral approach that incorporates ecological, economical and socio cultural values, in mutual consideration.

The VROM‐raad (2010) argues for reconsidering the way of positioning urban functions within the urban environment and the way this affects the impact on economical, ecological and socio‐economic values. Ideally, a configuration of functions leads a fusion of different values, a point in which people, planet and profit come together synergetically. Smart urban development prevents undesired impacts and establishes connections between stakeholder values in order to create mutual gains (Nirov, 2011). This research aims at analyzing potential added value to each of the three sustainability capitals as a result of rearranging urban functions in a sustainable development. Functional diversity is logically an essential precondition in this functionalistic approach.

This chapter is devoted to the concept of functional diversity. But first of all, urban land uses are introduced and an overview is presented. Next, the concept of functional diversity is explained in detail. Furthermore, the relationship between functional diversity and urban development is investigated, focusing on how functional diversity is embedded in urban development over the past century. Subsequently, the usefulness of functional diversity is discussed. Functional offers opportunities for positive sustainability impacts. Restrictions to functional diversity which limit the potential added value will be discussed as well, followed by the variables influencing the potential added value. This chapter ends with enumerating the answers to sub‐questions B1 to B4 in the conclusion.

3.1 Urban Land Uses

An urban environment is characterized by huge variety of land uses. An urban land use refers to main type of utility of a delineated peace of urban area, usually referred to as parcel or plot. Within the framework of this research the land uses will be classified. For practical reasons only a limited number of functions can be considered in the sustainability impact calculation process which will be described in the next chapter.

The land use classification principle is based on the one applied by municipalities to compose land use plans. Land use plans are composed by municipalities by means of a manual land use plans (Gemeente Zeeland, 2007). This manual prescribed all possible land uses which can exist within the city’s boundaries. Each land use is allocated to parent land use groups. The process of allocating land uses to parent land use groups is referred to as land use classification. The main land use groups presented in this manual are companies, urban green areas, retail, services, catering, offices, social facilities, relaxation, recreation, sport, transportation, water and living (Gemeente Zeeland, 2007).

3.2 Functional Diversity “Cities and city districts are in need of a most intricate and close‐grained diversity of uses which give each other constant mutual support, both economically and socially. “

Jane Jacobs (1961)


In this first paragraph the concept of diversity within the spatial domain is introduced using the four conditions defined by Jane Jacobs has defined four indispensible conditions needed for generating exuberant diversity in a city’s streets and district (Jacobs, 1961):

1. The district, and indeed as many of its internal parts as possible, must serve more than one primary function; preferably more than two. These must ensure the presence of people who go outdoors on different schedules and are in the place for different purposes, but who are able to use many facilities in common.

2. City blocks should be short, giving people reason to turn corners frequently. Long city blocks obstruct an effective intermingling and the potential advantages which city offer. Long city blocks is one of the characteristics of monotonous city districts. Short city blocks stimulate social and economic exchange.

3. The district must mingle buildings that vary in age and condition, including a good proportion of old ones so that they vary in the economic yield they must produce. This mingling must be fairly close‐grained. A variety in buildings of different ages is needed to cultivate the intermingling of primary and secondary functions. A variety of old buildings with corresponding living expenses and tastes is needed for creating stability and diversity in the demographic structure and economic diversity.

4. There must be a sufficiently dense concentration of people for whatever purposes they may be there. People concentration should be considered as the source of vitality and represent the opportunities and discrepancies which are unique and unpredictable according to Jacobs.

Using these conditions, Jacobs indicates that cities are in need of extreme complex and close‐grained diversity of primary and secondary utilities which support each other continuously which will contribute to the cities vitality. In healthy city there is a constant replacement of less intensive uses by more intensive uses which requires diversity. Primary land use is the main land use within in urban area which overrules other functions in terms of quantity. Secondary land use is a land use which is outnumbered by primary land uses and has a supportive role to those primary land use(s).

Diversity is about the intermingling of at least two primary utilities supported by a complex system of secondary utilities which serve people, originative from the primary utilities. The resulting movement of people fosters the urban complexity. Strategic positioning of the primary and secondary functions is crucial to strengthen and expand the existing urban vitality (Jacobs, 1961).

Detroit (Michigan, USA) is an example of a city which lacks diversity and vitality. This city is known for her depopulation as a result of a unilateral dependency on the car industry which collapsed totally since the beginning of the economic crisis. Diversity of primary functions and granularity was lacking on a city level resulting in a mass exodus of her inhabitants. Jacobs already warned for this threat back in the sixties.

Amsterdam on the other hand, shows that freedom of parcel usage is the fundamental principle in realizing a vital urban environment. The close‐grained mix of functions allows an optimal space for functional intermingling. The mansions along the canals in Amsterdam go back 200 years and have proven to be very sustainable in this regard. Although not scoring



very high in terms of energy efficiency, these mansions are considered to be more sustainable than the Dutch green VINEX‐districts which will not be able to meet future living demands (Nirov, 2011).

The first condition basically covers the definition for functional diversity. Functional diversity exists if a city district has more than one primary function. Primary functions are those which, in themselves, bring people to a specific place because they are anchorages. Urban planning distinguishes six primary functions: living, working, recreation, nature, water management and transport. The primary functions are often referred are often referred to as red, green, blue and grey functions. Secondary functions are those that grow in response to the presence of primary functions, to serve the people the primary functions draw. Secondary functions include inter alia healthcare, culture, education, religion, retail and food production.

In Dutch practice of spatial planning functional diversity is often referred to as functional intermingling. Functional intermingling is defined as the degree to which functions are intertwined. The former Dutch Ministry of Spatial Planning and Environment has developed 5‐piece typology for urban areas in the Netherlands and is depicted in table 3.1 (VROM).

Very strong functional intermingling 3 á 4 functions, mainly primary functions

Strong functional intermingling 2 á 4 functions, severak primary and or secundary functions

Moderate functional intermingling 1 primary function, 2 secundary functions

Weak functional intermingling 1 primary function, 1 secundary function

Monofunctional 1 primary function

Table 3.1 A 5‐piece scale for functional intermingling (VROM)

Functional diversity within the framework of this research can now be described as the intermingling of two or more land uses within a urban area in which land uses can be both primary and secondary.

3.3 History Functional Diversity Function segregation is a recent phenomenon when considering a long period of time. Functional intermingling used to be common until the end of the 19th century. Functions like living and working used to be combined within a building or in buildings side by side. As a result of the industrial revolution large‐scale industrial complexes arose. Initially, environmental impacts were ignored but the economies of scale were followed by an increase in pollution and soon complaints of nearby residents followed. Environmental and health issues obstructed functional intermingling. At the end of the 19th century the first workers villagers were build, away from the polluting industrial complexes. This point in time basically marks the emergence of function segregation.

At the start of the 20th century the garden city movement gains popularity among city planners. Although the garden city was initially meant to be a new city away from the polluted industrial cities, this was soon translated in garden city expansions connected to the polluted cities. New districts were erected at a distance from the polluting industrial areas resulting in function separation.

Between 1923 and 1927 the principle of the functional city was introduced by Cornelis van Eesteren (Pols, Amsterdam, Harbers, Kronberger, & Buitelaar, 2009). The functional city is


shaped using four main functions: living, working, recreation and transport. These functions were separated strictly from each other. Optimization of each of the functions resulted in a physical separations of the individual functions. The functional city is subject at the first CIMA (Congres International d’Architecture Moderne) in 1928 indicating the international character of the functional city. The legacy of the functional city has great influence on the urban design for several decades in the Netherlands.

After the World War II many districts are erected according this principle of functional separation. Using land‐use plans, environmental pollution categories and zoning the separation is institutionalized.

In the early sixties a first counter movement arises led by Jane Jacobs among others. Mono‐functionality affects the living quality and the sustainability according to Jacobs in both residential and industrial districts (Jacobs, 1961). Jacobs formulates several rules of thumb for vital urbanism, functional intermingling plays a key role in them.

Following the example of Jacobs, several concepts have been developed in the following decennia, like the recreational city, the compact city and all sorts of initiatives which contribute to functional intermingling. In practice however, developments based on functional separation continue to have the upper hand.

The necessity for functional separation seems to have diminished over the last decennia as a result of shift in economic activity towards a service economy. The number of sole proprietorships, the service related economic activities, and office bounded employment have increased over the years, while the share of industrial economic activities declines. The original motive for functional separation – nuisance as a result of the emergence of industrial buildings – has therewith become due, clearing the path for the comeback of functional diversity. This new development is especially in urban areas that show an increase in economic diversity. Preserved Institutional mechanisms prevent full exploitation of the opportunities this economical change offers which will be discussed later on in this chapter.

3.4 The usefulness of Functional Diversity: Opportunities en Threats

In chapter 2 is shown that sustainable urban development is about the balance of the Triple Bottom Line (people, planet, profit) and (a derivative of) the Vitruvian triad (utility value, experiential value, future value). Functional diversity is a possible way to realize the ambition of sustainable urban development. In this paragraph, the use of functional diversity is deepened in more detail.

Opportunities The Dutch market currently faces problems like high vacancy in the office market and deterioration on industrial areas as described in chapter 1. The challenge for urban planners and developers is to prevent future generations form facing similar problems. Preventing these offloading issues is in line with the definition of sustainable development. Jane Jacobs already advocated for functional diversity for creating urban vitality back in the sixties, using the inner‐city of Amsterdam as an example. Vital cities are characterized by functional diversity (Jacobs, 1961). Strategic positioning of the primary and secondary functions is crucial to strengthen and expand the existing urban vitality according to Jacobs. The chance for continuity in usage of buildings will grow as a result of functional diversity according to



Pols et al. (2009). Diversity stimulates the possibilities to take in social, technological and economic developments. A multi‐functional urban area decreases the chance for vacancy because of the presence of a higher number of potential users (functions) resulting in a higher degree of urban vitality.

The spatial interaction between functional diversity and urban vitality is just a single example of a positive impact as a result of combining urban functions. In terms of sustainable aspects as introduced in the previous chapter, the flexibility of an urban area will improve as a result of functional diversity. (Re)positioning urban functions will therefore offer opportunities for realizing added value from a sustainable perspective.

Pols et al. (2009) recognize opportunities driven by functional diversity. Interaction between urban function offer opportunities in the field of land and space usage. A synergetic solution might arise when stakeholders require similar utilities which imply a higher level of support for realizing shopping and catering facilities. Functional diversity will increase the number of stakeholders, increasing the chance for reaching a higher level of support.

Snellen (2001) argues that functional diversity shortens displacement distance. In other words, functional diversity reduces mobility. Reduction of mobility has several sustainable benefits like an improvement of the viability of the urban area and a reduction of the environmental impact.

A sophisticated study has been performed by the University of Technology in Delft et al. (2011) about how residual heat can be reused for heating in nearby buildings with different functionality using principles of heat cascading, heat exchange and individual self‐sufficiency. This study makes use of the fact that different functions require different temperatures for heating. Residual heat produced in an industrial building can be used to heat nearby dwellings for instance using the principle of cascading of heat exchange. Cooled air which is released in a supermarket could be used for cooling nearby office. These examples contribute to both ecological and economic benefits.

Spatial synergy arises when facilities, like for instance parking facilities, are being shared which influences the space and land usage efficiency positively. Urban functions like working and living are able to share parking facilities because each function requires parking facilities at different times of the day. The potential added value highly depends on which functions are combined within an urban area. When dwellings and offices share parking facilities, the required space for parking is 25 to 35 percent lower than the accumulated required space for parking of both urban functions (Lamens, Jongen, & Heiden, 2008).

Functional diversity offers also opportunities in the social field. Functional diversity increase social safety for instance. More people populate the urban area at different times of the day due to functional diversity, increasing the social control in these areas. Children will come into daily contact with the phenomenon of working, which contributes to their general knowledge.

The examples given above provide an indication of the enormous potential of the contribution functional intermingling might offer to sustainable urban development. Contributions to the economic, ecological and the socio‐economic pillar are more than conceivable based on the research presented above. However, Kong et al. (2007) pointed out that functional intermingling can result in both positive and negative impacts. When


assessing the positive impact of functional intermingling, the negative impacts need to be incorporate as well in order to get a realistic view of the sustainable potential.

Threats Besides lots of opportunities, functional intermingling might cause threats which have to be guarded for. Not all urban functions can be classified as mixable. Especially in the field of nuisance and viabilities threats are lurking. These threats are also recognized by the Association for Dutch Municipalities (VNG) who formulates functional intermingling categories to sort urban functions which serves as a mean to avoid mutual nuisance between functions. Environmental aspects like smell, noise nuisance, air quality and external safety are considered in this judgment. Functional diversity’s influence on the viability should be considered as one of the main threats (VNG, 2007).

Another threat could be traffic nuisance. Car mobility might increase as result of combining functions like housing and offices. When infrastructure is not equipped to deal with an increase in parking and traffic pressure traffic nuisance will emerge.

3.5 Functional diversity in urban planning practice: search of synergy

The challenge is to find synergetic combinations of functions in order to optimize the potential added value from a sustainable perspective. It is vital to exploit opportunities to the fullest which are dictated by specific function combinations, while guarding for potential undesirable side‐effects.

The term synergy comes from the Greek word 'synergos' and implies cooperation in order to reach a common goal or accomplishment. Synergy results in a whole which is more than the sum of the parts which is usually explained using the sum 1+1=3. Synergy is reached when the combinations of functions result in added value which would not have been reached in a mono‐functional area carrying just one of the distinct functions.

Synergetic function combinations can contribute to a sustainable urban environment. The goal of this research to systematically analyze the potential sustainable impacts in terms of ecological, economical and socio‐cultural values, offered by a specific urban configuration. In other words: which spatial configuration of urban function result in ecological, economical and socio‐cultural added value? A goal which can only be reached by (re)positioning urban functions within a specific urban context.

The flexibility of a designer is limited to the boundaries of the project area. Adjacent buildings and functions are a fact though might offer opportunities for creating synergetic function combinations. Matching the new functional configuration of the project area with its surroundings will ideally result in added value for both the project area and its surroundings. De Jong (2006) states that especially in the gradient between homogeneous environments possibilities arise.

3.6 Influential Variables There are different external variables that influence the synergy aspects by (re)positioning urban functions, four of them will be discussed successively: infill occupation layer, stakeholders’ values and requirements, the subsurface, and scales.



Infill occupation Layer The occupation layer is known as one of three components of the layer approach, a tool which is increasingly applied in Dutch urban planning (Nijs & Kuiper, 2006). The layer approach is used in practice for preparing and updating spatial visions by municipalities and provinces. The approach provides a framework for inventorying information about the subsurface and to describe characteristics about the soil. The output can be used to support decision‐making about the organization of urban space (VROM, 2006). Using the layer approach a link is established between spatial and sustainable development agenda in recent years (VROM‐raad, 2010).

The basic principle of the layer approach (figure 3.1) is the ability to unfold space into three layers: the occupation layer, the network layer and the subsurface layer. Each layer is subject to change, but the speed in which this occurs differs. The latter is the most stable layer which can be described as a coherent system of soil, water and the live contained in it. Changes in this layer take ages. The second layer knows a time dynamic of 25 to 100 years and consists of physical networks encompassing traffic, transport and communication infrastructure. The top layer is formed by space for living, working and recreating. This final is characterized by a relatively rapid changing pattern.

The occupation layer is the main focus within the scope of this research and therefore the most important variable. Function combinations will be forged at this level. The freedom of functional infill is partly limited by the plan size. A large plan size obviously offers more opportunities for combining functions and allows a higher degree of flexibility. In case of a relatively small plan size the influence of the functional infill of the adjacent urban area will be significantly larger. Consequently, possible function combinations will be largely dictated by urban functions in the surrounding urban area.

Stakeholders’ values and requirements The Dutch real estate market is currently shifting from supply‐oriented to demand‐oriented. The large‐scale developing which characterized the Dutch market ever since the Second World War is transforming to a more differentiated, tailored approach with a higher degree of stakeholder participation (VROM‐raad, 2010). The involvement of share‐ and stakeholders in urban development will increase significantly. Companies and citizens ask for quality and identity and ignore anonymous areas. This requires early involvement of share‐ and stakeholders in urban development. A shift is needed from informing stakeholders to participation of stakeholders (Puyleart & Werksma, 2011).

An integral approach with a high degree of stakeholder participation contributes to creating commitment among stakeholder, connecting short term and long term and solving problems like split incentive. An integral approach requires identification and specification of values in

Figure 3.1 The three layers of the layer approach (VROM)


de field of people, planet and profit (Agentschap NL, 2011). Thorough appraisal of hard and soft values is essential in this process. Previously, the focus in decision‐making was laid upon the hard, financial values, ignoring soft values. The new way of developing requires incorporating soft values which include among others health, comfort, quality of surrounding, social cohesion and safety. Most of these values can also be in the sustainability aspects, listed earlier in table 2.3.

In the new bottom‐up developing approach end‐users and stakeholders need to determine which values are important to them. The outcome of this process will differ in each project depending on stakeholders’ preferences. In urban development project four types of stakeholder group are usually involved: governments, commercial participants, civil society organizations and citizens. Excluding one of these stakeholders results in a smaller chance for sustainable urban development. Incorporating these stakeholders and merging their values is therefore essential in sustainable urban development (Puyleart & Werksma, 2011). The end‐user will also influence the programming of the project significantly therewith limiting the number of functions described in the previous paragraph, indicating the importance of stakeholders’ values and requirements as an essential variable within urban development and within the scope of this research.

Subsurface The subsurface of a project area should be considered as a fact considering its static character. The conditions of the subsurface might differ dependent on the location of a project area. Consequently, the subsurface is to be considered as a variable.

The subsurface might offer possibilities or set boundaries for creating a sustainable environment. The availability of surface for instance increases the possibilities for thermal storage. Soil contamination might limit opportunities for creating a sustainable urban environment.

The characteristics of the subsurface might also contribute to the identity of an area. Peatlands, dune areas are able to contribute to the singularity of an urban area. Historians and designers describe identity of an area as “genius loci”, in other words the protective spirit of an area. Maintenance and recovery of historical structures contributes to a sustainable environment. It is key to differences between area and places and to emphasize the differentiation (Ministerie van Infrastructuur en Milieu, 2011a).

Scale The fourth and final variable is scale. The impacts of functional synergy can relate to different scale levels. For instance, a rail road might produce some negative externalities in terms of noise nuisance on residential uses nearby, on micro scale. On the other hand, the accessibility of the area is improved at macro‐scale. The Dutch association for municipalities developed a database of disturbing distances of all kind of economic activities to provide insight the reach of negative externalities in terms of noise, smell, dust and danger (VNG, 2007). The reach of possible positive externalities might also be limited. The reach of possibilities of heat exchange is larger than the reach of common space usage which is usually bounded to building level. The actual reach of impacts as a result of functional combinations will be different depending on the sustainable theme or aspects and will have to be determined for each of them.



3.7 Conclusions This chapter discusses the phenomena functional diversity within the spatial domain and presents to answers to the following research questions:

A. Secondary questions regarding functional diversity in relation with sustainable development:

1) Which land use categories can be recognized in sustainable development? 2) What is the meaning of functional diversity? 3) What is the use of creating functional diversity within an urban context? 4) Which external variables influence potential sustainability impact initiated by

(re)arranging urban functions ?

The answer to the first question was found In a manual used by municipalities for composing land use plans. These manuals prescribe all acknowledged land uses in an urban area. Each of these land uses are allocated to main function groups. This functional classification shows the following main land use groups presented in this manual are companies, urban green areas, retail, services, catering, offices, social facilities, relaxation, recreation, sport, transportation, water and living (Gemeente Zeeland, 2007).

Functional diversity exists if a city district has more than one primary function. Primary functions are those which, in themselves, bring people to a specific place because they are anchorages. Urban planning distinguishes six primary functions: living, working, recreation, nature, water management and transport. Secondary functions are those that grow in response to the presence of primary functions, to serve the people the primary functions draw.

In Dutch practice of spatial planning functional diversity is often referred to as functional intermingling. Functional intermingling is defined as the degree to which functions are intertwined. The former Dutch Ministry of Spatial Planning and Environment has developed 5‐piece typology for urban areas in the Netherlands and is depicted in table 3.2.

Economical shifts make way for a comeback of functional diversity in urban planning. Functional diversity offers many opportunities for creating added value in field of sustainable development. Functional intermingling increases the chance for continuity in usage of buildings according to Pols et al. (2009). Diversity stimulates the possibilities to take in social, technological and economic developments. Another major opportunity is the possibility for stakeholders to share facilities like parking, conference space and catering facilities resulting in economical and spatial synergy. Besides these examples about respectively flexibility and space usage other sustainable fields (among others) like mobility, social cohesion, social safety and service accessibility might also be positively affected.

On the other hand, urban planners should also guard for the few downsides of functional diversity. Sustainable aspects like smell, noise nuisance, air quality and external safety might be affected negatively.

There are four external variables that influence the synergy aspects by (re)positioning urban functions, four of them have been discussed. The main variable within the scope of this research is the infill of the occupation layer since function combinations will be forged at this level. Second, the outcome is highly affected by stakeholders’ values and requirements.


Companies and citizens ask for quality and identity and ignore anonymous areas. This requires early involvement of share‐ and stakeholders in urban development. Third, the subsurface might offer opportunities or set limitations. The conditions of the subsurface will differ in each project. The fourth and final variable is the distance between functions. Increasing distance between functions is expected to lower the potential impact in many situations. To what extent the potential will be reduced depends on the concerned aspect. The reach of possibilities of heat exchange is larger than the reach of common space usage which is usually bounded to building level.



4. Sustainability Impact Assessment In this chapter a solution for systematically analyzing potential sustainable impacts as a result of functional intermingling. This will be done by developing a Sustainability Impact Assessment Model (SIAM). SIAM will assess sustainability impacts as a result of (re)arranging urban functions. The functionalistic approach presented in this chapter will be applied at building, location and area level (micro scale) as explained in chapter 2.5. The potential sustainability impact will be systematically analyzed and visualized by means of this comprehensive model. Obtained knowledge as presented in previous chapter about sustainability aspects, function classification and external variables will be incorporated in the model.

One of the few good examples of assessment tools is the Compatibility Evaluation Model ( (Taleai, Sharifi, Sliuzas, & Mesgari, 2007). The answer to this question has partly been found in a study performed by Taleai et al. (2007) who developed a model for evaluating the compatibility of multi‐functional and intensive urban land uses. Taleai et al. developed a comprehensive model through the combination of a suite of existing methods and tools: geographical information systems (GIS), Delphi Methods and spatial decision support tools: multi‐criteria evaluation analysis, analytical hierarchy process and ordered weighted average method. The developed model has the potential to calculate compatibility in both horizontal and vertical directions.

The Compatibility Evaluation Model (CEM) has been designed to explore the impacts of spatial externalities among neighboring land uses at a micro‐scale. The model simulates general land use compatibility at a micro‐scale level where potential conflicts among different land use types determine their compatibility. The model detects and visualizes these potential conflicts. Because of the focus on negative consequences, this approach could be characterized as defensive.

The concept of compatibility matrix has been used as a basis to develop the CEM. The Delphi method is used as a framework for constructing the detailed compatibility matrix. The Delphi method is an iterative process design to achieve consensus among a group of experts on a particular topic, in this case, the impact of spatial externalities among neighboring land uses. The resulting matrix is the main input for the CEM.

The methodology used by Taleai et al. has proven to be very useful for assessing compatibility impacts us a result of co‐existing land uses in densely built‐up urban areas. This methodology is therefore adopted for the purpose of this research. Contrary to the defensive approach of Taleai et al.(2007), SIAM will be applied for a more offensive approach, for visualizing and analyzing potential sustainability impacts systematically and will enable the user to do research on which arrangement of functions optimizes the sustainability impacts in a specific urban context. Applying the Delphi Method for composing the founding matrix would imply that the group of experts would have to consider a huge number of criteria, 33 in total. Reaching consensus on the overall sustainability impact level without overlooking one or multiple of the 33 criteria is equally impossible as it is time‐consuming. The solution for preventing this from happening is decomposing sustainability and assessing the sustainability impacts for each of the aspects independently. This will not

36| Chapter 4. – Sustainable Impact Assessment

only ensure that all aspects will be considered but also enables the model user to explore the sustainability affects of a specific functionalistic configuration systematically. The impacts on each of the sustainability aspects will be visualized separately or aggregated, depending on the user preference.

In this chapter, the usefulness of SIAM as well as the various steps of developing the sustainability impact assessment model and all its components will be described thoroughly, starting with an overall picture of the components. Furthermore, the manner in which obtained knowledge by means of desk research and expert interviewed is incorporated in the model development, is explained explicitly. In addition, the improvements and deviations compared to the model developed by Taleai et al. will be elaborated and substantiated.

4.1 Sustainability Impact Assessment Model (SIAM) The objective of this research is to develop a comprehensive tool which systematically analyses the potential sustainability impacts as a result of a (re)arrangement of urban land uses in a densely built‐up urban area.

Current practice in the process of composing a program of demands for an area of building starts with mapping of stakeholders’ values and wishes in the process of composing a program of demands for an area of a building. Subsequently, concrete solutions are developed based on knowhow and intuition. SIAM is a comprehensive model which will be very helpful in this process, by mapping out the opportunities and by enabling simulation of alternatives. SIAM can be used to measure sustainability impacts as a result of co‐existence of certain land uses. Furthermore, thorough analysis of the outputs will create a better understanding of how land use interaction can contribute to sustainability. SIAM will deliver a complete overview of potential solutions and will make the intuition factor redundant.

SIAM can be used both as measurement tool, as described above – and as communication tool. Potential impacts can be communicated using visualization and graphs produced in SIAM to other concerned stakeholders. The results of alternative analysis in SIAM may give rise to approach certain stakeholders. SIAM will then come in handy as a communication tool to present the sustainability potentials of certain land use configurations.

For the development of SIAM two methodologies have been combined: Analytical Hierarchy Process (AHP, elaborated op page 51) and an aggregation methodology developed by Taleai et al., although the latter has been slightly adjusted for the purpose this research. The aggregation methodology is used to calculate the sustainability impact values of land uses for each of the sustainability aspects. AHP (Saaty, 2008) will help to determine weights for each of these aspects in order to calculate a final sustainability impact value. The interaction between both methodologies is elaborated in chapter 4.5.

The structure of the Sustainability Impact Assessment Model is illustrated in figure 4.1, on the next page. Basically the model consists of several inputs, a calculation process and several outputs. All of the components of SIAM will be elaborated successively in the next paragraphs. But the description of SIAM starts with describing the sustainability aspects that are incorporated in the model based on the outcomes of chapter 2.



Figure 4.1 flow diagram of SIAM


4.2 Selected sustainability aspects The analysis presented in chapter 2 resulted in no less than 33 aspects which together make up the concept sustainability. Within the limited time frame for executing this research incorporating all these aspects is unfortunately utopian. Therefore, for the sake of manageability, the list of 33 aspects has to be reduced. Only these aspects which are highly effected by (re)arranging urban functions will be incorporated. By assessing to what extend indicators, and therewith the overlying sustainability aspects, are affected on a scale from 1 to 5 a careful and balanced selection can be made. The BREEAM‐expert at Royal HaskoningDHV was appointed for taking up this challenge. Using this evaluation (Appendix II) the list has been reduced to 11 aspects as being the most affected criteria: Energy, Air, Accessibility to social services and recreational facilities, Social Safety, Noise, Area and Identity, Social Cohesion, Space and Land Usage, Sustainable Transport, Quality Perception Area and Flexibility. Each of these aspects will be elaborated below.

Planet People Profit

Energy Accessability to Social Services and

Recreational facilities

Space and Land Usage

Material Accessability Grenery and water Sustainable Transport

Food

Water

Waste

Air

Surface Water

Soil

Abiotic Structure Social Safety Loval Economic Diversity

Ecological Value External Safety Local Employment

Traffic Safety Accessability

Noise Nuisance Quality Perception Area

Smell Nuisance

Wind Nuisance

Heath Nuisance

Light Nuisance

Insolation

Water Nuisance

Sustainable Living and Building Area and Identity Flexibility

Social Cohesion Economic Vitality

Experiential Value

Utility Value

Future Value

Table 4.1 Aspect reduction depicted in matrix

Energy refers to the energy usage in the operational phase of an urban area and the associated carbon dioxide emissions. The purpose is to prevent depletion of finite fuel supplies, to use renewable energy sources and to minimize harmful emissions. The main indicators are:

‐ The primary energy usage (of buildings, processes and public space) ‐ The use of renewable energy sources ‐ And sustainable energy production

Air refers to the air quality of a location. The purpose is to prevent occurrence of air pollution and to improve the air quality if possible by reducing the level of fine particles and nitrogen dioxide. These levels are also the main indicator for air quality.



Accessibility of services represents the viability of an urban area which is determined by the level of local services. The goal is to optimize this level. This aspect is directly determined by the number of services within in radius of 200 meter and indirectly by the public support for services.

Social safety refers to the protection or the feeling of protection from harm caused by human behavior in public space. The objective is to improve the social safety. The most important indicators are:

‐ The feeling of safety among users ‐ The number of crime victims ‐ Hourly activity in the public space

Noise deals with the noise level in an urban area. The objective is to minimize the noise nuisance and the number exposed individuals. The main indicators are noise production in dB and the number of exposed individuals.

Area and Identity represents the socio‐political, cultural and physical space conditions and is formed by the relationships and interaction between them. The location, the spatial shape of an area, its use by the residents, their characteristics and value orientations, their way of dealing with each other, and the atmosphere together determine the identity of an area. The objective is to protect and to strengthen the identity of an area. The general characteristic, the spatial structure, the economic activities, the social structure, cultural heritage and the quality perception of the area are the most important indicators.

Social cohesion refers to the extent in which people and groups interact with each other. The objective is to intensify the social cohesion. The main indicators are labor participation, participation in social organizations and interaction and the number of encounters between different users of an urban area.

Land‐ and space usage stands for the careful use of scarce space by reusing existing land, closing commodity cycles and by multiple use of space in space and time. The objective is to optimize land and space usage. The main indicators within the scope of this research are urban density and multiple land use (opportunities).

Sustainable transport refers to the extent in which transportation of people and goods strain on the environment. The objectivity is to minimize environmental impacts. The main indicators are the following:

‐ The distance between work, living and services for users ‐ The distance to public transport hubs ‐ Discouragement of car usage

Perception of area quality represents the degree to which users experience and appreciate the surroundings, and the extent in which this contributes to the well‐being of users. The main indicators are green diversity, building diversity, presence of surface water, opportunities for recreation, and functional lay‐out and accessibility.


Flexibility refers to the ability of an urban area to absorb change as a result of social and economic fluctuations. The objective is to improve this ability. The main indicators are the flexibility of buildings, temporary buildings and functional diversity.

4.3 Model inputs SIAM requires in total four inputs. These inputs are a calculation method, sustainable impact matrices, stakeholders’ values, case study data and the main variable of the model: land use alternatives. The matrices capture the effect of functional diversity; case study data describes local (functionalistic) characteristics of an urban area and stakeholders’ values represent the stakeholder participation in urban development. Project Alternatives allows the user to analyze the potential sustainability impacts of several scenarios. Each of these inputs can be either project‐dependent or project‐independent. Whether inputs are project‐dependent or –independent is indicated in figure 4.1 using the colors dark blue and light blue respectively. Each of the inputs will be described successively.

Land use impact assessment The concept of a compatibility matrix has been adopted to develop this model similar to the one developed by Taleai et al.(2007). This concept has been adjusted to meet the requirements for the purpose of this research. The functional breakdown structure has been tailored to the Dutch context using manuals for composing Dutch land use plans as a guideline.

Land use plans are composed by municipalities by means of a manual land use plans (Gemeente Zeeland, 2007) in accordance with prescribed main function groups. This classification used by municipalities has been slightly adapted after consulting several sustainable urban development experts. The main change was decomposing Social functions into Healthcare, Education and Cultural & Recreational facilities. The final overview shows a mix of fourteen red, green, blue and grey functions groups as illustrated in table 4.2. This overview will be guiding in classifying specific functions in urban development projects.

The purpose of a compatibility matrix is to assess to what extent every unique function combination is compatible. Compatibility can be defined as the degree to which co‐existence of two or more land use types result in positive sustainability impacts. In other words, it shows the degree of synergy as a result of functional diversity. These impacts might affect multiple scale levels and the magnitude of this impact might differ for each scale level. The scope of this research is limited to building level, location level and (local) area level.

This research will only incorporate the 11 sustainability aspects presented in the previous section. For each of these sustainability aspects a sustainability matrix will have to be constructed, providing insight into sustainability impacts as a result of co‐existence of specific urban land uses in regard to a single sustainability aspect. The data collection process and analysis will be addressed in the next chapter.

The data collection methodology deviates from the methodology used in the reference study. Instead of using the Delphi method this research relies on individual expert judgments. For each sustainability aspect an expert is selected based on his or her knowledge and experience in this specialization. At Royal HaskoningDHV about 8000 people



are employed in numerous professional fields which makes it the ideal location for executing this research.

The focus on a single aspect should result in sharp and accurate assessments. Experts will be able to rely on their own expertise without having to acquire knowledge about other related aspects, thus enabling a sharp and accurate judgment. The sustainable impact in regard to a single sustainability aspect of pair‐wise function combinations have been assessed by experts specialized in the field of this particular aspect. The experts have judged the sustainability impact using a five‐point scale:

Highly Positive Impact (HPI): intermingling of those land uses which lead to high positive impacts in regard to a particular sustainability aspect.

Moderate Positive Impact (MPI): intermingling of those land uses which lead to moderate positive impacts in regard to a particular sustainability aspect.

Neutral Impact (NI): intermingling of those land uses which lead to negligible impacts in regard to a particular sustainability aspect.

Moderate Negative Impact (MNI): intermingling of those land uses which lead to moderate negative impacts in regard to a particular sustainability aspect.

Highly Negative Impact (HNI): intermingling of those land uses which lead to high negative impacts in regard to a particular sustainability aspect.

Table 4.2 Compatibility matrix in regard to the sustainability matrix Energy

Functions Description Underlying functions

1 ResidentialDiverging types of housing Single family and multi‐family

housing

2 Offices

The provision of services commercially while the general

public is not or only to a minor degree helped directly.

Offices in all sizes, conference

facil ities.

3Companies &

Industry

The commercial production and processing of goods and

articles. Industry is characterized by a high degree of

automation.

Industrial companies, util ity

companies, SMEs.

4 Retail

The commercial sale, rent and supply of goods to persons

who rent or buys these goods for personal use. This refers

to various industries including the food industry, the

fashion industry and the housing industry.

Supermarkets, butchers, bakeries,

fashion stores, garden centres,

home interior stores.

5 Catering

The commercial provision of food and beverages which

are consumed on the spot. Including, bed & breakfast,

disco's and party facil ities.

Hotels, Bed & Breakfast,

Restaurants, Lunchrooms, Coffee

spots.

6 Services

The commercial provision of services while the general

public is helped directly. Including banking services,

personal services and ICT services.

banking office, hair dressers,

beauty salons, internet cafes.

7 EducationalOrganisations specialized in transferring knowledge,

skil ls and attitudes according to pre set objectives.

primary schools, secondary

schools and universities.

8 HealthcareThe whole of activities aimed at improving the health of

people.

hospitals, medical centres and

dentists.

9Cultural &

Recreational

Recreation in which relaxation stands for enjoying

(whether or not cultural activities passively or

participating actively.

museums, theatres, recreational

dwell ings and day recreation.

10 SportPhysical activities for fun or for profession. fitness centres, golf courts, tennis

courts and gymnasiums.

11 AgriculturalGrowing food in and around cities for both non‐

commercial and commercial objectives

agricultural greenhouses and

kitchen gardens.

12Urban green

areas

Public and private greenery in an urban environment with

a viewing and / or use function.

visually dominant tree, a park, a

park or a private garden.

13 Water(retention)Surface water whether or not specially meant for water

storage.

canals, ponds, wades.

14 Transportation

Movement of people and goods by rail, road or

waterways.

public transport station, public

transport, parking lots, parking

garages.


The data found in this process is project‐independent. The sustainability impact values do not depend on certain project characteristics. Experts have been asked to judge function combinations in ideal circumstances. The found potential impact value might be restricted by spatial characteristics of a specific project. This needs to be investigated in the subsequent process, after calculating the potential sustainability impact values.

For processing purposes, these impact levels resulting from the qualitative assessment by the different sustainability experts will have to be quantified. Analytical Hierarchy Process (AHP) and structured pair‐wise comparison have been used as a framework for quantifying the sustainability impact levels. AHP is a theory of measurement through pair‐wise comparisons and relies on the judgments of experts to derive priority scales. It is these scales that measure intangibles in relative terms. The comparisons are made using a scale of absolute judgments that represents how much more one element dominates another with respect to a given attribute (Saaty, 2008).

For the purpose of quantification, a structured pair‐wise comparison has been used in order to eliminate inconsistency issues which might occur with regular pair‐wise comparisons. Structured pair‐wise comparison is done in two successive steps. First, all criteria need to be ranked in order and subsequently, adjacent criteria will be compared based on the ranking made previously. Since the criteria are ranked in order, the difference between the adjacent criteria can be considered as weak or strong because the most important criterion is not compared to the least important one and only the two adjacent ones are compared with each other. In doing so, preference for criteria can be expressed.

The aim of this research is, inter alia, visualizing the potential benefits of the resurrection of functional diversity in the urban environment. Therefore, the emphasized will be placed on positive sustainability impacts resulting in higher relative importance for positive impacts as illustrated in table 4.3. Using the specific AHP methodology the compatibility levels can be quantified by calculating standardized scores which represent the weights for each of the levels.

Stakeholders’ Values Stakeholders’ values are a very important variable in determining the optimum composition of urban land uses for specific urban area which is the second part of the input for SIAM. In chapter 2 is argued that a higher level of stakeholder participation ( by inter alia Laglas, 2011) is expected to result in a higher level of quality. Composing programs of requirement and concretizing the

Compatibility Level HPI MPI NI MNI HNI Geometric mean Standardized

Score

HPI Highly Positive Impact 1 3 5 6 7 3,63 0,53

MPI Moderate Positive Impact 0,33 1 3 4 5 1,82 0,27

NI Neutral Impact 0,20 0,33 1 2 3 0,83 0,12

MNI Moderate Negative Impact 0,17 0,25 0,50 1 2 0,53 0,08

HNI Highly Negative Impact 0,14 0,20 0,33 0,5 1 0,34 0,05

Table 4.3 Quantification of compatibility levels using AHP



sustainability ambition of stakeholders starts in practice with the inventory of stakeholders’ values. The objective is to retrieve what involved stakeholders desire and what is important to each of the stakeholders groups, both on the short term and the long term. The difficulty in passing through such a process is the huge number of stakeholder groups involved in urban developments with diverging values. In general, the stakeholders involved in urban development can be divided into four categories: governments, commercial participants, civil society organizations and citizens. Incorporating each of these stakeholders and merging their values is essential in sustainable urban development (Puyleart & Werksma, 2011). The challenge is to match these diverging values of each of the stakeholder categories.

The way of matching stakeholders’ values is a study in itself and is therefore excluded from the scope of this research. However, the importance of the influence of stakeholders in contemporary urban development is certainly recognized. The stakeholders’ values are represented in SIAM by weight factors which can be allocated to each of the incorporated sustainability as visualized in figure 4.2. Consequently, the output of alternative analysis will be matched to stakeholders’ values. This will be elaborated in the calculation process in the next section of this chapter. The values of stakeholders are highly project‐dependent and will differ in each project.

Figure 4.2 Weight allocated to sustainability aspects

Case Study Data This third part of the input concerns data related to project characteristics, referring to the infill of the occupation layer, one of the main variables found in the desk research phase. This infill offers opportunities for realizing positive sustainability impacts as described in the previous chapter. Several steps need to be passed for catching all required data regarding the functionalistic arrangement of the case study area.


The first step is to identify all parcels within the project area and to identify all associated urban functions of these parcels by means of a basic parcel map. This data then needs to be restructured. Land uses for each floor at each parcel in the project area should be joined in land use table. Sometimes different land uses exit in the same floor. In that case, the floor’s use reflects the major land use type found on that specific floor resulting in an abstraction of the actual functional arrangement in horizontal direction on building level. In vertical direction, a different kind of abstracting has been implemented. In this direction, land uses will be classified based on the classical division of buildings in a plinth, center section and top layer. A common function division in inner‐cities in the Netherlands is a deviating plinth land use (e.g. commercial functions) and residential land uses on top of that, in the center section. A basement function has been added to this classical division which enables incorporation of underground functions as well. This classical way of floor classification has been illustrated in figure 4.3.

Figure 4.3 floor classification

Neighborhood land uses need to be classified following the principle described in chapter 3.1 by means of a derivative of the manual used by Dutch municipals for composing land use plans. All land uses in the project area need to be classified using the function classification division presented in table 4.2. Each sub‐function will be allocated to one of the main function groups. The resulting thematic function map, which could be characterized as an abstraction of the functional urban environment, enables calculation of sustainability impacts based on specific function combinations.

The final step in the process of preparing case study data is defining the scale levels. In SIAM three levels are distinguished: building level, location level and (local) area level. Building level is for this purpose directly related to the parcellation of an area. The building level is equal the parcel size, regardless the exact size of the parcel. The area level is to be determined by the user of SIAM but a radius of approximately 300 meters around the subject parcel suffices. Finally, by means of a neighborhood assessment the neighborhood level for each parcel in the project area is defined. Neighboring parcels are any parcels that are adjacent to or directly opposite or diagonal to the subject parcel which may or may not be contiguous to the subject parcel. Defining these scale levels enables calculation and visualization of sustainability impacts on each of these levels. The scale levels refer to the distance between urban land uses. The distance will affect the potential sustainability impact as a result of interlinkage of these land uses on each of the scale levels. To what extent the impact will be affect will differ for each sustainability aspect. The calculation process in this regard will be elaborated in the next section of this chapter.



Land Use Alternatives The final and main variable is the land use alternatives input. The purpose of SIAM is to analyze and visualize potential sustainability impact as a result of (re)arranging urban land uses. The alternatives are operationalized in land use alternatives. SIAM allows the user to test and compare the outcomes of four land use alternatives. Comparing and analyzing each of the alternatives will help the user in selecting the best alternative. Furthermore, analysis will provide the user with essential knowledge about potential sustainability impacts as a result of intermingling specific urban functions. The calculation process will be described in the next chapter and will clarify the functioning of SIAM further.

4.4 Sustainability Impact Calculation All the inputs described in the previous section will be incorporated in the calculation methodology which is the engine of SIAM. Using the detected and classified neighborhoods, the stakeholders’ values and the compatibility matrices as input, a sustainability impact value is calculated for each floor of each parcel. This calculation process will be repeated for each land use alternative and subsequently for each sustainability aspect. The goal of this process is aggregating the various impact values offered by co‐existence of multiple land uses to a single sustainable impact value which represents the degree to which positioning the particular land use in a specific urban area result in sustainability impacts. These values – retrieved from sustainability matrices – are considered as a measure for the impact level in regard to multiple sustainability aspects as a result functional diversity. The calculation process used in this research is largely derived from the one used by Taleai et al. Only small adjustments have been made to this calculation in order to tailor the calculation methodology to the purpose of this research. These improvements will be clarified and substantiated explicitly in this section.

Calculation model of the reference study Taleai et al. used the majority additive‐ordered weighted averaging (MA‐OWA) and AHP methods as a theoretical base for developing an aggregation method. Their suggested methodology first aggregates the compatibility values at floor level (horizontal aggregation). These values are offered by all adjacent land use placed at various floors of adjacent parcel. The horizontal aggregation aggregates all of the values belonging to the same floor and produces one value for each neighboring floor resulting in a single compatibility value for each floor. At the next step, these values are aggregated in vertical direction to produce a unique value that indicates aggregated compatibility value based on the vales offered by land uses placed at different floors of all adjacent parcels. This unique value represents the compatibility of the subject land use in relation to its surroundings at location level.

The next part of the calculation process concerns the aggregation of values of compatibility value that are offered by land uses that are placed in the same parcel. This calculation is also carried out in vertical direction and produces another unique value based on the values offered by all land uses place at different floors of the subject parcel. This unique value


Figure 4.4 Schematic representation of the calculation process



represents the compatibility of the subject land use in to its overlying and/or underlying neighboring land uses at building level.

The final step in this calculation process is aggregating the two acquired values for the two scale levels to one as the final compatibility value for subject land use. Deviations and similarities compared to reference calculation model The calculation model as suggested by Taleai et al. is largely adopted, although some changes has been deemed as desirable. The objective of the assessment model differs, in this research a sustainable impact value needs to be calculated, instead of a compatibility value. This only requires a change in terminology though; no change is needed in the calculation process in this regard.

This different objective requires a deviation in the calculation method though. For the purpose of this research a third scale level has been added to the calculation methodology. Besides aggregating at building and location level, aggregation at area level will be executed as well. Co‐existence of land uses on this third and larger level might also affect the potential sustainability affect which is why this third level needs to be incorporated in the calculation model as well. The calculation methodology is exactly the same, only the input values will differ and consequently the area impact value will too.

The horizontal aggregation methodology as suggested for the location value calculation is also in need of minor alternations. The compatibility values incorporated in the Taleai approach are derived from co‐existence of land uses in horizontal and vertical direction without entangling the diagonal direction. Overlooking of impact values found in the diagonal direction might affect the final outcome significantly. Therefore, the calculation method has been adjusted in such a way that function combinations in horizontal, vertical and diagonal direction are incorporated in the calculation methodology.

The resulting sustainable impact calculation methodology suggested for the development of SIAM has been visualized in a schematic representation in figure 4.4. The first step is threefold: the aggregation of the sustainable impact values on building, location and (local) are level. The next step is to aggregate these three to single indicator that will represent the impact assessment in the field of a particular sustainability aspect for the subject floor. This process will be repeated for each floor, for each parcel and for each sustainability aspect. Each of the steps is explained below in more detail.

Building, Location and Area Value Calculation In this step sustainability impact values as a result of co‐existence of land uses at various scale levels are aggregated to a single sustainability impact value for each of the scale levels. Three scale levels which have been defined earlier will be considered: building level, location level and area level. The aggregation methodology for each of the scale level values is similar. The aggregation methodology will be explained using the calculation of the location value as an example.

The process starts with selecting a sustainability aspect, a subject parcel and subject floor sequentially for which the aggregated sustainability impact value on location level will be calculated, by means of the structured spatial parcel data as main input. Once a subject floor is selected the primary (horizontal) aggregation process starts.


Primary (horizontal) aggregation In the primary (horizontal) aggregation process aggregates sustainability impact values from neighboring parcels at location level that are located at the same level and produce one value in comparison with the subject floor’s land use. The process is illustrated in figure 4.5 using a hypothetical example which shows a subject parcel and floor highlighted in red. A comparison is firstly made with the neighboring land uses on basement level (8 in total in the example) resulting in a set of eight sustainability impact values which need to be aggregated using the primary aggregation methodology. Each of these values is derived from the sustainability impact matrix for the subject sustainability aspect. This process is repeated for each floor level resulting in four floor values provided that at all levels neighboring land uses exist. The process shows aggregation in both diagonal and horizontal direction, depending on the subject land use and the neighboring land use(s) which may or may not be on the same level.

The aggregation method is based on the majority additive‐ordered weighting averaging (MA‐OWA). The MA‐OWA operator is a modification of the arithmetic mean. Majority aggregation processes should be completed as flows: (i) select an element from each group and aggregate the elements; (ii) subtract 1 from the cardinality of each group and eliminate those groups with a cardinality of 0; (iii) with the results of the aggregation in the first two steps, create a new group with a cardinality of 1; and (iv) repeat the previous steps until only one group remains (figure 4.6). The result is an aggregation value that represents the majority and more or less indicating the influence of the minority, thus creating a more precise aggregation value (Taleai, Sharifi, Sliuzas, & Mesgari, 2007).

The primary aggregation method functions as follows (Taleai, Sharifi, Sliuzas, & Mesgari, 2007): First Ai has to be determined by retrieving sustainability impact values for the land use combinations from the sustainability impact matrix. The size of the set depends on the number of neighbors. The example given in figure 4.5 would result in a set of 8 values for each floor level.

Ai a1i, a2i, . . . , ani is a set of sustainability impact values from floor level offered to a specific subject floor and aji [0.05, 0.08, 0.12, 0.27, 0.53], then the primary horizontal aggregate value is:

Figure 4.5 Representation of the classical and MA‐OWA aggregation



, , … , · , , … , ·

Where [0,1] , ∑ = 1 and is the floor level. Furthermore, is the th largest of

the and:

, … , 1

∏ ,… ,

Where is a function that indicates when the element is used in the aggregation

process. The is a function that indicates the number of elements in each step in the aggregation process. Therefore,

, … ,

1

1

1 1 1 1 1 0

Secondary (vertical) aggregation The primary aggregation process produces four floor impact values which reflects the potential sustainable in regard to neighboring land uses. One value for each floor level is produces provided that neighboring land uses exist at each of the levels. The next step is to aggregate those acquired floor values to a, in this case, location sustainability impact value. In this process several assumptions are considered:

The weight of the aggregated floor values calculated using the primary aggregation process for each neighborhood floor, will decrease when the floor distance between the neighborhood floor and the subject floor increases.

The number of neighboring land uses applied to produces aggregated values prior to this stage should be considered.

According to the assumptions above, first the weight factors related to the floor distance between neighborhood floor and the subject floor should be determined. Once again Analytical Hierarchy Process is applied for this matter. Table 4.4 shows the resulting importance of each floor distance in comparison with others. To determine weight, the assumption was made that one unit increase in distance between the subject floor and another land uses will result in one level decrease in importance. Determination of weights is done on the basis of a calculation of the distance between the neighborhood floor and the subject floor ( ).


The next step is the calculation of the vertically aggregated values. Weighted average operator is used to produce vertically aggregated sustainability impact value. The secondary (vertical) aggregation method functions as follows:

∑ · ⁄ ·∑ · ⁄

In which is the number of adjacent land uses used in the primary aggregation process of floor level , and ∑ . Furthermore, is the weight factor for the floor

sustainability impact value ( ) needed in this level of aggregation procedure. And where,

| |

In which is the distance between the neighborhood floor and the subject floor, the floor number of subject land use and the floor number of the comparison floor of the primary aggregation process.

The calculation process for the location sustainability impact value and the area sustainability impact value is practically identical. However, instead of making a comparison with subject parcel’s neighbors, a comparison is made with the parcel’s neighbors’ neighbors for calculating the area sustainability impact value. The aggregation methodology is exactly the same though, only the input differs and thus the output as well (illustrated in fig. 4.4). The calculation process for the building sustainability impact value deviates since only one impact value for each floor has to be aggregated, thus making the primary aggregation superfluous. Subsequently, the vertical aggregation method for calculating on building level differs as well:

∑ ·∑

In which is the sustainability impact value for the land use on floor level in comparison with land use on subject floor.

Tertiary aggregation The process described above results in three sustainability impact values on building, location and area level for the subject sustainability aspect. The next step is to aggregate these three values to single sustainability impact value for the subject sustainability aspect ( ). Desk research has shown that scale levels are an important variable when it comes down to assessing sustainability impacts. The importance of each of the scale levels are assumed to differ to one another and will vary for each sustainability aspect. Using the following formula, the sustainability impact for a particular sustainability aspect can be calculated:

Criteria d*=0 d*=1 d*=2 d*=3 Geometric

mean

Eigenvector

ω d

d*=0 1 2 3 4 2,21 0,47 ω 1

d*=1 0,50 1 2 3 1,32 0,28 ω 2

d*=2 0,33 0,50 1 2 0,76 0,16 ω 3

d*=3 0,25 0,33 0,50 1 0,45 0,10 ω 4

Table 4.4 Weights for secondary aggregation Figure 4.6 Distance determination



∑ ·∑

In which represents the importance of the scale level value and is the sustainability impact value on scale level . The weight factors for the scale levels for each of the sustainability impact values will be determined by sustainability expert as will be described in the next chapter. This entire calculation needs to be repeated for each sustainability aspect, for each parcel and for each floor, resulting in a complete overview of sustainability impact value for each floor and parcel broken down to sustainability aspects.

Alignment to stakeholders values The described calculation process will result in sustainability impact score for each of the sustainability aspects in figure 4.8.The final step is to align the sustainability impact values to stakeholders’ values. The importance of stakeholders’ values has been discussed extensively in the previous chapter and is thus beyond dispute. The stakeholders can be incorporated in SIAM by allocating weight factors to each of the sustainability aspects. The summed product of the weights and the various sustainability impacts result in a final sustainability impact for each floor in each parcel aligned to stakeholders’ values. Evaluating several land use alternatives allows the user to pick the best alternatives. However, SIAM allows the user to analyze the output thoroughly by providing several outputs which will be described in the next paragraph.

Figure 4.7 AHP structure of weighted sustainability aspects.


Analytical Hierarchy Process:Decisions involve many intangibles that need to be traded off. To do that, they have to be measured alongside tangibles whose measurements must also be evaluated as to, how well, they serve the objectives of the decision maker. The Analytic Hierarchy Process (AHP) is a theory of measurement through pair‐wise comparisons and relies on the judgments of experts to derive priority scales. It is these scales that measure intangibles in relative terms. The comparisons are made using a scale of absolute judgments that represents, how much more, one element dominates another with respect to a given attribute. The judgments may be inconsistent, and how to measure inconsistency and improve the judgments, when possible to obtain better consistency is a concern of the AHP. The derived priority scales are synthesized by multiplying them by the priority of their parent nodes and adding for all such nodes. (Saaty, T. 2008)

To make a decision in an organized way to generate priorities we need to decompose the decision into the following steps: (Saaty, T. 2008)

1. Define the problem and determine the kind of knowledge sought. 2. Structure the decision hierarchy from the top with the goal of the decision, then the

objectives from a broad perspective, through the intermediate levels (criteria on which subsequent elements depend) to the lowest level (which usually is a set of the alternatives).

3. Construct a set of pair‐wise comparison matrices. Each element in an upper level is used to compare the elements in the level immediately below with respect to it.

4. Use the priorities obtained from the comparisons to weigh the priorities in the level immediately below. Do this for every element. Then for each element in the level below add its weighed values and obtain its overall or global priority. Continue this process of weighing and adding until the final priorities of the alternatives in the bottom most level are obtained.

To make comparisons, we need a scale of numbers that indicates how many times more important or dominant one element is over another element with respect to the criterion or property with respect to which they are compared.

AHP Calculation Theory: Consider n elements to be compared, C1 … Cn and denote the relative ‘weight’ (or priority or significance) of Ci with respect to Cj by aij and form a square matrix A=(aij) of order n with the constraints that aij = 1/aji, for i ≠ j, and aii = 1, all i. Such a matrix is said to be a reciprocal matrix. (Coyle,G. 2004)

The weights are consistent if they are transitive, that is aik = aijajk for all i, j, and k. Such a matrix might exist if the aij are calculated from exactly measured data. Then find a vector ω of order n such that Aω = λω . For such a matrix, ω is said to be an eigenvector (of order n) and λ is an eigenvalue. For a consistent matrix, λ = n . (Coyle,G. 2004)

For matrices involving human judgment, the condition aik = aijajk does not hold as human judgments are inconsistent to a greater or lesser degree. In such a case the ω vector satisfies the equation Aω= λmaxω and λmax ≥ n. The difference, if any, between λmax and n is an indication of the inconsistency of the judgments. If λmax = n then the judgments have turned out to be consistent. Finally, a Consistency Index can be calculated from (λmax ‐n)/(n‐1). That needs to be assessed against judgments made completely at random and Saaty has calculated large samples of random matrices of increasing order and the Consistency Indices of those matrices. A true Consistency Ratio is calculated by dividing the Consistency Index for the set of judgments by the Index for the corresponding random matrix. Saaty suggests that if that ratio exceeds 0.1 the set of judgments maybe too inconsistent to be reliable. In practice, CRs of more than 0.1 sometimes have to be accepted. A CR of 0 means that the judgments are perfectly consistent. (Coyle,G. 2004).



Eigenvector: There are several methods for calculating the eigenvector. Multiplying together the

entries in each row of the matrix and then taking the nth root of that product gives a very good approximation to the correct answer. The nth roots are summed and that sum is used to normalize the eigenvector elements to add to 1.00. In the matrix below, the 4th root for the first row is 0.293 and that is divided by 5.024 to give 0.058 as the first element in the eigenvector. (Coyle,G. 2004)

The table below gives a worked example in terms of four attributes to be compared which, for simplicity, we refer to as A, B, C, and D.

Table 4.5 :Example of Eigenvector calculation

The eigenvector of the relative importance or value of A, B, C and D is (0.058,0.262,0.454,0.226). Thus, C is the most valuable, B and D are behind, but roughly equal and A is very much less significant.

Consistency: The next stage is to calculate λmax so as to lead to the Consistency Index and the Consistency Ratio. (Coyle,G. 2004)

We first multiply on the right the matrix of judgments by the eigenvector, obtaining a new vector. The calculation for the first row in the matrix is:

1*0.058+1/3*0.262+1/9*0.454+1/5*0.226 = 0.240

and the remaining three rows give 1.116, 1.916 and 0.928. This vector of four elements (0.240,1.116,1.916,0.928) is, of course, the product Aω and the AHP theory says that Aω= λmaxω so we can now get four estimates of λmax by the simple expedient of dividing each component of (0.240,1.116,1.916,0.928) by the corresponding eigenvector element. This gives 0.240/0.058=4.137 together with 4.259, 4.22 and 4.11. The mean of these values is 4.18 and that is our estimate for λmax. If any of the estimates for λmax turns out to be less than n, or 4 in this case, there has been an error in the calculation, which is a useful sanity check.

The Consistency Index for a matrix is calculated from (λmax ‐n)/(n‐1) and, since n=4 for this matrix, the CI is 0.060. The final step is to calculate the Consistency Ratio for this set of judgments using the CI for the corresponding value from large samples of matrices of purely random judgments using the table below, derived from Saaty’s book, in which the upper row is the order of the random matrix, and the lower is the corresponding index of consistency for random judgments. (Coyle,G. 2004)

Table 4.6: index of consistency

For this example, that gives 0.060/0.90=0.0677. Saaty argues that a CR > 0.1 indicates that the judgments are at the limit of consistency though CRs > 0.1 (but not too much more) have to be accepted sometimes. In this instance, we are on safe ground.

A CR as high as, say, 0.9 would mean that the pair‐wise judgments’ are just about random and are completely untrustworthy.


The entire calculation process has been programmed in Visual Basic and Excel. The choice for these programs is based on the abilities and familiarity of the author with these programs and the ability to acquire the necessary programming skills within a limited time frame. After running the simulations outputs will be generated and presented in Excel. Each of possible output is presented below.

4.5 Model Outputs The Sustainable Impact Assessment Model (SIAM) will offer the user several types of producible outputs which will be presented in this paragraph successively. The outputs will show the final the impact values for each of the alternatives, presented in tables, graphs and visualizations. Based on the generated outputs, the best alternative can be selected which optimizes the sustainability impacts on building, location and area level. Furthermore, output will be generated which will help de user to understand the formation of the final impact value(s) which is rather complex, thus creating an understanding about which function combinations affects which sustainability aspect in what manner. A thorough analysis can be made by comparing results for various sustainability aspects or parent sustainability capitals. Each of possible outputs will be presented successively below.

Overall Impact values This first output generates a total overview of sustainability impact values for each floor on each parcel within the delineated urban area. The overview shows what the sustainability impact values is for each floor of each parcel. Average scores on project (c.q. building), location and area level indicate the consequences on each of these levels from different perspectives. The underlying scores of each sustainability aspects are also given as well as the accumulated scores for people, profit & planet and utility value, experiential value and future value.

Table 4.7 Screenshot overall impact values for alternative A

Avarage Compatibility Value

Energy

Air

Accessability to services

Social Safety

Noise nuisance

Area and Identity

Social Cohesion


Sustainable Transport

Quality perception Area

Flexability

Planet

People

Profit

Utility Value

Experiential Value

Future Value

Weights >> 1,00 1,00 1,00 1,00 1,00 1,00 1,00 1,00 1,00 1,00 1,00

Project Project Average 0,17 0,28 0,10 0,14 0,12 0,11 0,20 0,17 0,15 0,20 0,10 0,28 0,19 0,15 0,18 0,17 0,11 0,20

Surroundings SurroundinAverage 0,17 0,26 0,08 0,21 0,13 0,11 0,22 0,16 0,15 0,25 0,11 0,21 0,17 0,17 0,18 0,19 0,11 0,18

Area Area Average 0,18 0,21 0,10 0,18 0,18 0,11 0,21 0,15 0,21 0,24 0,13 0,30 0,15 0,17 0,22 0,19 0,14 0,21

1 1 Basement 1BasemenProject

2 1 Plinth 1Plinth Project 0,21 0,24 0,11 0,16 0,14 0,08 0,27 0,13 0,26 0,26 0,17 0,50 0,18 0,16 0,30 0,21 0,13 0,28

3 1 Center 1Center Project 0,18 0,26 0,10 0,17 0,15 0,10 0,21 0,18 0,17 0,21 0,10 0,33 0,18 0,16 0,20 0,18 0,12 0,22

4 1 Top 1Top Project 0,18 0,26 0,10 0,17 0,14 0,11 0,20 0,18 0,16 0,20 0,09 0,31 0,18 0,16 0,19 0,18 0,12 0,21




8 2 Top 2Top Project 0,16 0,27 0,10 0,12 0,12 0,12 0,18 0,17 0,13 0,17 0,09 0,26 0,19 0,14 0,16 0,16 0,11 0,19




12 3 Top 3Top Project 0,17 0,28 0,10 0,13 0,12 0,12 0,18 0,17 0,13 0,19 0,09 0,25 0,19 0,14 0,16 0,17 0,11 0,18

13 4 Basement 4BasemenSurroundings

14 4 Plinth 4Plinth Surroundings 0,22 0,12 0,10 0,39 0,13 0,08 0,12 0,27 0,27 0,39 0,25 0,48 0,11 0,20 0,35 0,26 0,15 0,23

15 4 Center 4Center Surroundings 0,20 0,19 0,10 0,18 0,13 0,09 0,19 0,22 0,22 0,33 0,15 0,42 0,15 0,16 0,28 0,21 0,13 0,24

16 4 Top 4Top Surroundings

Tripple Bottom Line Vitruvian ClassificationScenario

A(Incorporated) Sustainability Aspects



These output values can be used to compile impact maps in order to show the relative severity of sustainability impact values. A threshold method is needed to define various sustainability impact classes as follows:

Highly positive impact: 0.53 0.40 Moderate positive impact: 0.40

0.19 Neutral impact: 0.19 0.10 Moderate negative impact: 0.10 0.7 Highly negative impact: 0.07 0.05

Using this classification methodology, a 3D sustainability impact map (fig. 4.8) of the area can be drawn up by means of another program (like SketchUP e.g.). These 3d maps will indicate which neighboring land uses will affect sustainability positively or negatively. Insight is provided at a single glance about the sustainability impacts as a result of a certain functionalistic arrangement. By comparing alternatives, insight is provided in which alternative scores best on project, location and/or area level.

Detailed Alternative Comparisons In this output sustainability impact values of alternatives are compared by means of tables and graphs. This comparison can be made for project, location and area level as well as for a single floor of a specific parcel. Radar graphs show how the impact values will differ from one to another. These graphs catch the sustainability impact scores of the four alternatives for all the sustainability aspects and their overlying classifications, indicating which alternative scores best for what aspect and at which level. Interpretation of these graphs will be clarified in the case study (chapter 6).

Figure 4.9 output graphs

Figure 4.8 Example of 3D visualization (Taleai, Sharifi, Sliuzas, & Mesgari, 2007)


Detailed plot analysis This output generates a detailed overview for single floor of a particular parcel. The overview encompasses all the aggregated sustainability impact values; all the single impact values produced as a result of the land uses of the subject floor in comparison with all other functions; and the function combinations counts indicating the number of existing function combinations for each scale level visualized in plots. This output allows the user to retrieve and analyze the underlying impact values for each of the aggregated values in order to get a better understanding of the dynamics in the area. An example of such a detail plot analysis is added in appendix VII.

4.6 Conclusions In this chapter the Sustainability Impact Assessment Model (SIAM) and all its components have been presented. For the development of SIAM two methodologies have been combined: Analytical Hierarchy Process (AHP) and an aggregation methodology developed by Taleai et al. (2007) although the latter has been slightly adjusted for the purpose this research. SIAM systematically analyzes potential sustainability impacts as a result of urban diversity, therewith answering sub‐question C1.

AHP is used here as multi‐criteria decision‐making tool. AHP structures a decision problem into a hierarchy with a goal, decision criteria, and alternatives. In the AHP, each element in the hierarchy is considered to be independent of all the others—the decision criteria are considered to be independent of one another and the alternatives are considered to be independent of the decision criteria and of each other. The AHP‐structure is illustrated in figure 4.8. Pair‐wise comparisons should be used to measure the weights of the components of the structure, and finally to rank the alternatives in the decision.

For the aforementioned ranking of alternatives, the aggregation methodology of Taleai et al. has been adopted broadly, only minor adjusted were deemed to be necessary. Aggregation at area level has been added to the methodology and the calculation procedure has been adjusted slightly in order to consider function combinations in the diagonal direction. The aggregation methodology utilizes AHP and majority additive‐ordered weighted averaging (MA‐OWA). The result is an aggregation value that represents the majority and more or less indicating the influence of the minority, thus creating a more precise aggregation value.

The aggregation methodology is founded on sustainability impact matrices which contain impact values for each unique function combination. One sustainability matrix for each of the eleven considered sustainability aspects will have to be constructed using expert judgments. Another important input for the aggregation methodology is the case study data. SIAM requires detailed and structured spatial data about the project surroundings which will be constructed using land use and floor classifications. Furthermore, the aforementioned stakeholders’ values represented by weight factors for each of the sustainability aspects should be entered. And finally, the project alternatives have to be determined.

This combined methodology then calculates a sustainability impact value aligned to stakeholders’ values for each floor of each parcel within a delineated urban area. This process is repeated for all the alternatives. The outputs of SIAM will indicate what the impact is of each alternative on building (c.q. project), location and area level, allowing the user to make a weighed choice for the best alternative. Furthermore, the outputs will enable



the user to analyze the outcome thoroughly, providing the user insight about opportunities for a specific project with specific opportunities.

Expert interviews revealed that sustainability experts usually start with mapping of stakeholders’ values and wishes. Subsequently, concrete solutions are developed based on knowhow and intuition. SIAM is a comprehensive model which will be very helpful in this process, by mapping out the opportunities and by enabling simulation of alternatives. Furthermore, thorough analysis of the outputs will create a better understanding of how land use interaction can contribute to sustainability. SIAM will deliver a complete overview of potential solutions and will make the intuition factor redundant.

SIAM can be used both as measurement tool, as described above – and as communication tool. Potential impacts can be communicated using visualization and graphs produced in SIAM to other concerned stakeholders. The results of alternative analysis in SIAM may give rise to approach certain stakeholders. SIAM will then come in handy as a communication tool to present the sustainability potentials of certain land use configurations.

It’s important to emphasize that SIAM will only calculate potential sustainability impacts. These potential values might be restricted and in some case reinforced by local characteristics (e.g. the subsurface of an area as described in chapter 3.6). SIAM will give clear indications of potential sustainability impacts and will give rise to investigate certain alternatives further. One other important aspect in this subsequent process is the willingness of stakeholders to cooperate. Incorporating these variables in the development is unfortunately unfeasible. However, SIAM can once again be used in this process as a communication tool to present the potential of possible collaboration.

Expert judgments for constructing each of the sustainability impact matrices is needed to operationalize SIAM. Analysis of the different judgments will also give interesting insights in fertile singular land use combinations. This data collection and analysis will be presented in the next chapter.

58| Chapter 5. – Data collection & Analysis



5. Data collection & Analysis This chapter will describe the data collection and analysis for the development of SIAM. Firstly, the data collection methodology for constructing the sustainability impact matrices is addressed. The resulting matrices, one for each sustainability aspect, are the main input for SIAM and will actually utilize the tool. Reviewing each of the constructed matrices will provide interesting insights into what extent the subject sustainability aspect is affected. In‐depth analysis of the combined matrices will provide insight in fertile single land use combination on the one hand, and incompatible land use combinations on the other hand. Furthermore, the determination of the weight factors of the scale levels for each sustainability aspect will be described. These weight factors are relevant in aggregating the building, location and area impact scores as described in the previous chapter. This chapter ends with concluding remarks about the data collection and analysis.

5.1 Data collection The sustainability matrices will be the main components of the engine of SIAM. These matrices will indicate to what extent sustainability impacts will occur in the field of a single sustainability impact as a result of co‐existence of particular land uses. For each sustainability aspect, a sustainability impact matrix will be constructed. SIAM will retrieve impact scores from each of these matrices for relative land use combinations and will process these scores in order to calculate an aggregated sustainability impact score as described in the previous chapter.

The data collection methodology deviates from the methodology used in the reference study. Instead of using the Delphi method this research relies on individual expert judgments. Decomposing sustainability into several aspects enables approaching experts who are specialized in the field of one single particular aspect, to focus on the aspect which lies in their field of expertise. Eleven experts, all with different backgrounds and expertise, have been approached for assessing the sustainability impact level in the field of their expertise. The experts have judged the sustainability impact using a five‐point scale as presented and elaborated in the previous chapter:

Highly Positive Impact (HPI)

Moderate Positive Impact (MPI)

Neutral Impact (NI)

Moderate Negative Impact (MNI)

Highly Negative Impact (HNI)

In total 105 unique land use combinations have been assessed by each expert, which is a rather time‐consuming task. Only one expert for each aspect has been approached. It would have been better to approach more experts but this was unfortunately not possible within the limited timeframe available for conducting this research. An extensive elaboration about the contents of the research and the objective of the questionnaire has been added to the questionnaire, ensuring a thorough understanding about how to fill in the questionnaire, thus safeguarding the results. Furthermore, the experts have been thoroughly screened to ensure that the background of each expert matches the required profile for composing the matrix. An overview of the 11 selected experts and their backgrounds is shown in appendix I. Finally, the assessment have been checked on irrationality, meaning that by means of logical


reasoning the result should be explainable and results should not show any signs of indifferent answers. These measures were taken in order to enhance the reliability of the outcomes, despite the limited number of experts. The final outcomes are presented and explained in the next paragraph.

5.2 Data review Using the data collected by means of expert judgments the eleven sustainability impact matrices haven been constructed. Subsequently, each of the matrices has been quantified using the method described in the previous chapter. Reviewing each of these quantified matrices provide interesting insights which will be presented in this chapter. All the constructed matrices have been added to appendix III, as well as the quantified matrices.

Energy In the field of energy, the cascading principle as presented in the study REAP (TU Delft, DWA and DSA, 2011) is very interesting in regard to this research, when it comes down potential synergy between urban land uses. REAP shows the potential of heat exchange and cascading between various urban land uses and distinguishes suppliers and purchasers of either high, medium or low temperature. According to the cascading principle, e.g. a purchaser of high temperature heating can act as a supplier of medium temperature heating for another land use. These principles are based (re)use of residual heating and thus lowering the primary energy usage, one of the main indicators of the sustainability aspect energy as described earlier. Intermingling of land uses enables utilization of these principles.

With this knowledge in mind, the sustainability impact matrix for energy (figure 5.1) can be explained. This matrix shows positive impacts (impact score ≥ 0.27) when suppliers of a certain level temperature heating are matched with purchaser of this temperature heating. Companies and industries are known for being a high temperature supplier which explains why many combinations – which require lower temperature heating – with this land use category result in high impacts. Existing (relatively low insulated) residential buildings and offices could act as suppliers of medium temperature heating for e.g. recent build (proper insulated) housing and offices. Agriculture (greenhouses) could be described as a low

Table 5.1 Sustainability impact matrix for Energy

Residential

Offices

Companies & Industry

Retail

Catering

Services

Educational

Healthcare

Cultural &

Recreational

Sport

Agricultural

Urban green areas

Water(retention)

TransportationQauntification

1 Residential 0,12 0,27 0,53 0,12 0,12 0,12 0,12 0,12 0,27 0,12 0,27 0,12 0,12 0,12

2 Offices 0,27 0,27 0,53 0,27 0,12 0,27 0,27 0,27 0,27 0,12 0,27 0,12 0,12 0,12

3 Companies & Industry 0,53 0,53 0,27 0,27 0,27 0,27 0,53 0,53 0,27 0,12 0,27 0,12 0,12 0,12

4 Retail 0,12 0,27 0,27 0,12 0,12 0,12 0,12 0,12 0,12 0,12 0,12 0,12 0,12 0,12

5 Catering 0,12 0,12 0,27 0,12 0,12 0,12 0,12 0,12 0,27 0,12 0,27 0,12 0,12 0,12

6 Services 0,12 0,27 0,27 0,12 0,12 0,12 0,12 0,12 0,27 0,12 0,27 0,12 0,12 0,12

7 Educational 0,12 0,27 0,53 0,12 0,12 0,12 0,12 0,12 0,12 0,12 0,27 0,12 0,12 0,12

8 Healthcare 0,12 0,27 0,53 0,12 0,12 0,12 0,12 0,12 0,12 0,12 0,27 0,12 0,12 0,12

9 Cultural & Recreational 0,27 0,27 0,27 0,12 0,27 0,27 0,12 0,12 0,12 0,12 0,27 0,12 0,12 0,12

10 Sport 0,12 0,12 0,12 0,12 0,12 0,12 0,12 0,12 0,12 0,12 0,27 0,12 0,12 0,12

11 Agricultural 0,27 0,27 0,27 0,12 0,27 0,27 0,27 0,27 0,27 0,27 0,12 0,12 0,12 0,12

12 Urban green areas 0,12 0,12 0,12 0,12 0,12 0,12 0,12 0,12 0,12 0,12 0,12 0,12 0,12 0,12

13 Water(retention) 0,12 0,12 0,12 0,12 0,12 0,12 0,12 0,12 0,12 0,12 0,12 0,12 0,12 0,12

14 Transportation 0,12 0,12 0,12 0,12 0,12 0,12 0,12 0,12 0,12 0,12 0,12 0,12 0,12 0,12



temperature purchaser resulting in positive combinations with high temperature suppliers like housing and companies & industry.

Further remarkably is the absence of negative impact values (impact score ≤ 0.08), indicating that only positive impact can occur in the field of energy as a result of intermingling urban land uses.

In densely build urban areas a phenomena called urban heat islands ( (Perez Arrau & Peña, 2011) might arise. Densely build urban area showing an increase in air temperature, thus requiring a higher primary energy usage for cooling in buildings during warm seasons. Adding water and urban green areas to these densely build urban areas could counteract this phenomenon by decreasing the air temperature and thus lowering the demand for energy usage for cooling. However, given the Dutch context with relatively small cities and the moderate climate this is not likely to have significant impacts on the primary energy usage which is why this phenomenon is not notable in the sustainability matrix.

Air Air refers to the air quality of a location, measured using the levels of fine particles and nitrogen dioxide as indicators. A review of the sustainability matrix of air shows both positive and negative impacts as a result of intermingling of specific urban land uses. Known air polluters are transportation and industry, known air cleaners are green areas. Combinations with these land uses will result in respectively negative and positive impacts.

Air quality could also be affected indirectly as a result of functionalistic intermingling. Co‐existence of certain land uses might result in increase of traffic pressure which will affect the air quality in these urban areas negatively. These affects are visible in the sustainability impact matrix for air as well. Especially the combinations with the residential land use are sensitive for this phenomenon.

Accessibility of Services Accessibility of services represents the viability of an urban area which is determined by the level of local services. This measured by the distance between users and services. Functional intermingling will decrease the distance between services and users which is especially visible in the sustainability impact matrix in land use combination with the residential land use, explaining the positive impacts.

Social Safety Social safety refers to the protection or the feeling of protection from harm caused by human behavior in public space. One of the main criteria for this sustainability aspect is hourly activity in the public space. An abandoned industrial area in the evening and night is a good example of an area which lacks social safety, especially at these hours of the day. Functional intermingling will in many cases lead to an increase in street activity, and thus in an increase in social safety. This is confirmed by the sustainability matrix for social safety. However, negative impacts are noticeable as well. One of downsides of adding urban green to an urban area is the negative impact on social safety. Central Park in Ney York city is a well‐known example, a place one might want to avoid after sunset. But in many cases intermingling will lead to more social safety. Think of inner‐cities with lots of services and catering functions which will sometimes even result in a 24‐7 activity pattern.


Noise Noise deals with the noise level in an urban area. The main indicators are noise production in dB and the number of exposed individuals. The degree to which land use intermingle positively depends on the noise production of each land use, the combined number of exposed people and the acceptance level of noise of users of both land uses. Residential land use is in general known for its vulnerability for noise which has partly contributed to current zoning area development principles.

The acceptance level varies from person to person. In this regard, the BSR‐model developed by SmartAgent (Smart Agent, 2011) might be interesting, in which two main dimensions in social science are combined: the sociological and psychological dimension. This study produced four quadrants, four worlds of experience, from which people act and think, but also the level of acceptance are related to these worlds. People living ‘in the red world’, characterized as dynamic, adventurous and living one day at a time, would probably have a higher level of level with regard to noise then people living ‘in the green world’ who are predominantly tranquil and prefer peace in the area. However, this has not been incorporated in this research because of the broadly defined land uses. Nevertheless it is worthwhile mentioning.

Reviewing the matrix for noise indicates the vulnerability of the residential land use for noise; many combinations show a negative impact. The same applies for natural areas like the urban green areas. The most important noise producers are companies & industry, transportation and catering (think of crowded terraces) and education (think of school yards) which is indicated by the compatibility matrix for noise.

Area and Identity Area and Identity represents the socio‐political, cultural and physical space conditions and is formed by the relationships and interaction between them. The location, the spatial shape of an area, its use by the residents, their characteristics and value orientations, their way of dealing with each other, and the atmosphere together determine the identity of an area. Land uses can strengthen or weaken the identity of an area, represented by positive (impact score ≥ 0.27) and negative impacts (impact score ≤ 0.08). The matrix indicates industries and buildings as being one of the main threats in this regard.

Social Cohesion Social cohesion refers to the extent in which people and groups interact with each other. The main indicator which is affected by functional intermingling is the number of encounters between different users of an urban area. The sustainability impact matrix for social cohesion indicates the enormous potential of functional intermingling. Especially combinations with the residential land use seem to result in positive impacts in regard to social cohesion. Furthermore, the catering function is obviously the ideal place for facilitating those encounters which to a lesser extent also implies for urban green areas and sport.

Land‐ and space usage Land‐ and space usage stands for the careful use of scarce space by reusing existing land, closing commodity cycles and by multiple use of space in space and time. The main indicator affected by functional intermingling is multiple land use (opportunities). The sustainability impact matrix for land‐ and space usage indicates the enormous potential in this regard. The



challenge is to find opportunities to share facilities, intensifying the land usage. Parking lots can be shared by offices and residential land uses; urban green area can be used for sports, recreation and water retention; and classrooms can also be used for childcare or for activities for the elderly. Just to give a few arbitrary examples.

Sustainable Transport Sustainable transport refers to the extent in which transportation of people and goods strain on the environment. The challenge is to decrease the distance between services and users which can be achieved by functional intermingling. Decreasing this distance will decrease the transport need and discourage car usage. The matrix especially indicates the potential of function combinations with residential land use.

Area perception Perception of area quality represents the degree to which users experience and appreciate the surroundings, and the extent in which this contributes to the well‐being of users. The main indicators are green diversity, building diversity, presence of surface water, opportunities for recreation, and functional lay‐out and accessibility. A lot of these indicators are positively affect by functional diversity which explains why the matrix shows mainly positive sustainability impact, Only the combinations with companies and industries might result in negative impacts.

Flexibility Flexibility refers to the ability of an urban area to absorb change as a result of social and economic fluctuations. The main indicators relevant for this research are the flexibility of buildings and functional diversity. This is of course one of the main aspects which will be primarily positively affected by functional intermingling. As described extensively in the first chapter functional diversity will improve the resilience to socio‐economic changes. Especially intermingling of ‘red’ functions will counteract vacancy among these land uses. Water and Urban green areas on the other hand will improve the overall quality of urban areas.

Remarkably, the land use combinations with companies & industry score negatively in the field of flexibility. This is probably related to the buildings structure and contamination level of this function category which makes it less suitable for other land uses, and thus less flexible.

5.3 Data Analysis Reviewing each of the sustainability impact matrices separately provide insight in how particular land use combinations score in terms of sustainability impacts in the field of a single sustainability impact. The next step is to perform an in‐depth analysis of all the matrices which should provide insight in fertile function combination on the one hand, and incompatible function combinations on the other. Land use combinations might realize a positive sustainability impact for one sustainability aspect and negative impact for another. It is equally interesting as it is important to analyze all matrices in order to get insight in to the total sustainability impact for each land use combination.

Fertile land use combinations The aim of is this research is partly to explore to what extent functional diversity can contribute to realizing a sustainable environment. In this regard, it is interesting to analyze


which single land use combinations results in the highest (potential) sustainability impact and could therefore be labeled as the most fertile land use combinations.

Table 5.2 gives insight into the most fertile land use combinations by indicating for each land use combination in the field of how many aspects a positive sustainability impact could be realized. For example, the 6 for the combination between residential and retail indicates that this specific function potentially results for six out of the eleven matrices in either a moderate or high positive sustainability impact.

Based on the analysis presented in table 5.2 several conclusions can be drawn:

None of the land use combination creates a positive impact for all eleven sustainability impacts.

The most fertile function combinations are the residential land use in combination with cultural & recreational and agriculture which result in positive impacts for 9 out of 11 aspects.

4

Residential

Offices


Retail

Catering

Services

Educational

Healthcare

Cultural &

Recreational

Sport

Agricultural

Urban green areas

Water(retention)

Transportation

1 Residential 7 7 3 6 7 8 7 7 9 7 10 7 6 6

2 Offices 7 5 3 2 7 8 5 4 5 6 6 8 5 7

3 Companies & Industry 3 3 5 2 7 2 4 1 2 1 2 5 2 6

4 Retail 6 2 2 2 6 5 2 3 3 3 5 5 3 5

5 Catering 7 6 6 6 3 6 4 5 8 6 7 7 6 5

6 Services 8 8 2 5 6 1 4 5 6 4 5 4 3 5

7 Educational 7 5 4 2 3 4 3 6 5 7 8 7 5 6

8 Healthcare 7 4 1 3 5 5 7 3 4 6 6 7 5 5

9 Cultural & Recreational 9 5 1 3 8 5 4 4 2 6 6 7 6 5

10 Sport 7 7 1 3 6 2 7 6 6 4 4 7 6 5

11 Agricultural 9 6 3 4 5 3 8 6 5 4 2 6 5 2

12 Urban green areas 8 8 4 4 7 4 6 7 6 7 6 5 6 3

13 Water(retention) 6 5 1 3 6 3 5 5 6 6 5 6 3 2

14 Transportation 5 7 6 5 5 5 6 5 4 5 2 3 2 2

Table 5.2 Matrices analysis of positive impacts, indicating how many sustainability aspects are affected positively for each land use combination.

2

Residential

Offices


Retail

Catering

Services

Educational

Healthcare

Cultural &

Recreational

Sport

Agricultural

Urban green areas

Water(retention)

Transportation

1 Residential 1 1 6 1 2 1 1 0 1 0 0 1 1 2

2 Offices 1 1 3 1 1 0 1 0 1 1 1 1 1 1

3 Companies & Industry 6 4 1 3 1 1 3 5 5 5 3 3 3 1

4 Retail 1 1 4 1 0 0 1 0 0 1 0 1 1 1

5 Catering 2 1 1 0 0 1 1 1 0 0 0 2 1 1

6 Services 1 0 2 0 1 0 0 0 0 0 0 1 1 1

7 Educational 1 1 4 1 1 0 0 0 0 1 0 2 1 1

8 Healthcare 0 0 5 0 1 0 0 0 0 0 0 1 1 1

9 Cultural & Recreational 1 1 5 0 0 0 0 0 0 0 0 0 0 2

10 Sport 1 0 5 1 0 0 1 0 0 0 0 0 0 1

11 Agricultural 0 2 3 1 0 1 0 0 1 2 0 0 0 2

12 Urban green areas 1 1 4 2 2 1 3 1 0 1 0 0 0 2

13 Water(retention) 1 1 4 1 1 1 1 1 0 1 0 0 0 2

14 Transportation 3 1 1 1 1 1 2 1 2 1 4 3 3 1

Table 5.3 Matrices analysis of negative impacts, indicating how many sustainability aspects are affected negatively for each land use combination.



Functional intermingling with residential land use on the one side seems to offer the best chances for positive sustainability impact. Most of the combinations with the residential land use proof to be highly fertile except for the combination with companies and industry.

Other prominent land uses which – to a lesser extent – seem to guarantee positive sustainability impact in combination with other land uses are offices, educational land use and urban green areas.

Incompatible land uses Table 5.2 gives insight into the most incompatible land use combinations by indicating for each land use combination in the field of how many aspects a moderate or high negative sustainability impact could be realized. The higher the number, the higher the level of incompatibility for the concerned land uses. Most striking, yet not surprisingly, are the combinations with companies & industries as being relatively incompatible. For some combinations this results in negative sustainability combinations for 5 out of 11 sustainability aspects. The combination with residential land uses even results in negative sustainability impacts for 6 sustainability aspects. This land use combination can therefore be labeled as the most incompatible land use combination. The combinations with transportation also show also a relatively high level of incompatibility.

Note: these conclusions are drawn based on the assumption that all sustainability aspects are equally important, thus have all the same weight. This research has shown though, that stakeholder participation is of the essence in contemporary urban developments. Concerned stakeholders are the ones to determine the relative importance of each sustainability aspects and to what extent negative impacts for certain sustainability impacts are acceptable. Incorporating the values of concerned stakeholders, which vary from project to project, might result in a totally different evaluation. In the influence of this very important external variable will be illustrated in the case study described in the next chapter.

5.4 Scale factor determination Besides stakeholders’ values, scale is also recognized as an important variable in determining the sustainability impact level as described earlier in chapter 3. The impacts of functional of functional synergy can relate to different scale levels. To what extent the distance between land uses actually affects the sustainability impact level is expected to vary from one sustainability aspect to another.

The same sustainability experts were approached to asses to what extent scale matters for their subject sustainability aspect which lies in their field of expertise. A pair‐wise evaluation is conducted by each of the experts. Subsequently, weight factors (eigenvectors) were calculated using analytical hierarchy process (AHP). The calculation process has been illustrated in the box on page 51. and the resulting weight factors have been depicted in table 5.4. The final result indicates that the weights differ for each sustainability aspect. For only 4 out of 11 aspects the weights for building, location and area level are equal. These weights will be used for the tertiary aggregation process as described in the previous step. This was the last step in operationalizing SIAM.


Energy

Air

Accessibility of Services

Social Safety

Noise

Area & Identity

Social Cohesion

Land‐ and Space Usage


Area Perception

Flexibiliy

Building 0,43 0,20 0,14 0,33 0,64 0,33 0,33 0,65 0,33 0,33 0,64

Location 0,43 0,40 0,43 0,33 0,26 0,33 0,33 0,28 0,33 0,33 0,26

Area 0,14 0,40 0,43 0,33 0,10 0,33 0,33 0,07 0,33 0,33 0,10

Table 5.4 Scale Weight Factors for each sustainability aspect

5.5 Conclusions This chapter has presented the data collection needed for the operationalization of SIAM. The main input components are the eleven sustainability matrixes for each of the incorporated sustainability aspects. Individual expert judgments have formed the basis for each of the matrices. Analysis of the combined matrixes has provided insight in both fertile and incompatible land uses. Companies and Industry can based on the matrices analysis be labeled as the most incompatible land use. Most possible combinations with residential land use and offices seem to be the fertile land use combinations. In this analysis the sustainability aspects are considered to equally important. In practice, the concerned stakeholders will determine the relative importance of each the sustainability aspects and whether negative sustainability impacts for certain aspects are acceptable or not. This external variable will probably have great influence on the optimum configuration of functions.

In short, this chapter answers the following research questions:

1) How much do particular function combinations contribute to each of the sustainability criteria?

2) Which singular combinations of land uses have the highest potential for contributing to a sustainable urban environment as result of (re)arranging urban functions?

The answer to the first questions can be found in the sustainability impact matrices (appendix III). These matrices indicate to what extent co‐existence each of the 105 possible land use the impact in the field the considered sustainability aspect. Analysis of these matrices has shown that the most fertile function combinations are the residential land use in combination with cultural & recreational and agriculture which result in positive impacts for 9 out of 11 aspects (table 5.2).

Furthermore, functional intermingling with residential land use on the one side seems to offer the best chances for positive sustainability impact. Most of the combinations with the residential land use proof to be highly fertile except for the combination with companies and industry. Other prominent land uses which – to a lesser extent – seem to guarantee positive sustainability impact in combination with other land uses are offices, educational land use and urban green areas. On the other land use combinations with companies and industries seam to result in negative impacts quite frequently (table 5.3)



6. The utilization of SIAM SIAM has become operational by the implementation of the sustainability impact matrices and the scale factors. The final step is to put SIAM into practice in order to test the ability of the tool and to explore the sustainability impact of several degrees of functional diversity. This chapter starts with an exploration of the effect of functional diversity on sustainability impact levels. Using a fictional parcellation, the effect of several degrees of functional diversity will be simulated and analyzed. Subsequently, a case study in the city of Rotterdam in which SIAM is tested extensively, will provide more insight in the operation and potential of SIAM as well as in the sensitivity of the generated results.

6.1 Simulating functional intermingling As described in the first chapter of this report, many researchers and urban developers argue for functional diversity as mean for creating a more sustainable environment. But does functional diversity indeed result in a more sustainable environment, opposed to mono‐functional environments? And to what extent is sustainability influenced by the degree of diversity. It is interesting to find out whether SIAM is able to assist in answering these questions. For this purpose, a fictional simplified parcellation of 7 x 7 plots, each occupied by a single urban function which are located on the same level, is used to simulate sustainability impacts as a result of several degrees of functional diversity.

In the Netherlands, three main mono‐functional environments in densely build urban areas can be identified. First of all, mono‐functional residential districts can be found in urban environments which are usually located in the suburbs of Dutch cities. The second mono‐functional areas are (originally) industrial areas, although many industrial areas start showing some degree of functional intermingling. Sports and recreational facilities have also found their ways to these areas already. The third and final mono‐functional areas in the Netherlands are offices clusters. A famous example is the office cluster next to Central Station in Rotterdam which often shows sign of desertion, despite of its central position in a densely populated area.

The results of simulating each of these three mono‐functional areas are presented in figure 6.1., illustrating the final sustainability impact values for each of the parcels in the fictional environment. Remarkably, the values are almost similar in each of the scenarios; in all scenario and show a slightly positive impact value for each of the parcels since a value of 0.12 represents a neutral sustainability impact as described in chapter 4.

(a) (b) (c)

Figure 6.1 sustainability impact scores for each of the 49 parcels in a mono‐functional environment: (a) residential, (b) companies & industrial and (c) offices

0,14 0,14 0,14 0,14 0,14 0,14 0,14

0,14 0,14 0,14 0,14 0,14 0,14 0,14

0,14 0,14 0,14 0,14 0,14 0,14 0,14

0,14 0,14 0,14 0,14 0,14 0,14 0,14

0,14 0,14 0,14 0,14 0,14 0,14 0,14

0,14 0,14 0,14 0,14 0,14 0,14 0,14

0,14 0,14 0,14 0,14 0,14 0,14 0,14

0,14 0,14 0,14 0,14 0,14 0,14 0,14

0,14 0,14 0,14 0,14 0,14 0,14 0,14

0,14 0,14 0,14 0,14 0,14 0,14 0,14

0,14 0,14 0,14 0,14 0,14 0,14 0,14

0,14 0,14 0,14 0,14 0,14 0,14 0,14

0,14 0,14 0,14 0,14 0,14 0,14 0,14

0,14 0,14 0,14 0,14 0,14 0,14 0,14

0,15 0,15 0,15 0,15 0,15 0,15 0,15

0,15 0,15 0,15 0,15 0,15 0,15 0,15

0,15 0,15 0,15 0,15 0,15 0,15 0,15

0,15 0,15 0,15 0,15 0,15 0,15 0,15

0,15 0,15 0,15 0,15 0,15 0,15 0,15

0,15 0,15 0,15 0,15 0,15 0,15 0,15

0,15 0,15 0,15 0,15 0,15 0,15 0,15

68| Chapter 6 – The Utilization of SIAM

Suppose some office land uses will be added to a residential district, what would happen in terms of potential sustainability impact? Intermingling of those land uses creates opportunities in the field of social safety, energy, land‐ & space usage and accessibility to services as indicated in chapter 1. Intermingling of those functions should therefore result in higher (potential) sustainability impact values. Figure 6.2b illustrate the result of calculating the impact values for residential area to which some office functions are added as a secondary functions, resulting in an residential area with weak functional intermingling (table 3.1.). The plot division is presented in figure 6.2a in which the numbers refer to land uses as presented in table 3.2. The results confirm the positive impacts on sustainability impact values for the offices (0.23) which are significantly higher opposed to the values in mono‐functional areas of either of the two land uses (0.14, fig. 6.2). These results indicate the positive impact of functional diversity.

(a) (b)

Figure 6.2 Weak functional intermingling of residential land uses and offices (b) result in an increase in sustainability impact values (a)

Next, the degree of functional intermingling is increased. A parcellation in which residences (1.) and offices (2.) are both primary land uses and urban green areas (12.) and catering (5.) are secondary land uses is illustrated in figure 6.2a. Such a parcellation would be qualified as strong functional intermingling (table 3.1). The results (fig. 6.3) look promising; the impact values of each of the parcels have increased considerably. Furthermore, the amplitude of the values also increased which now fluctuate between 0.19 and 0.32 which represent considerable sustainability impacts.

(a) (b)

Figure 6.3 Strong functional intermingling of residential land uses and offices (b) result in higher sustainability impact values (a)

1 1 1 1 1 1 1

1 1 1 1 1 1 1

1 1 2 1 2 1 1

1 1 1 2 1 1 1

1 1 2 1 2 1 1

1 1 1 1 1 1 1

1 1 1 1 1 1 1

0,14 0,14 0,14 0,14 0,14 0,14 0,14

0,14 0,14 0,14 0,14 0,14 0,14 0,14

0,14 0,14 0,23 0,15 0,23 0,14 0,14

0,14 0,14 0,15 0,21 0,15 0,14 0,14

0,14 0,14 0,23 0,15 0,23 0,14 0,14

0,14 0,14 0,14 0,14 0,14 0,14 0,14

0,14 0,14 0,14 0,14 0,14 0,14 0,14

2 2 1 2 2 12 1

1 2 5 2 1 2 1

2 2 12 1 2 5 1

1 2 1 1 5 2 2

1 2 12 2 1 1 2

5 1 1 2 1 12 1

2 5 1 2 12 1 1

0,21 0,21 0,19 0,22 0,19 0,29 0,22

0,22 0,19 0,25 0,20 0,20 0,19 0,23

0,18 0,18 0,29 0,22 0,21 0,25 0,19

0,19 0,19 0,21 0,20 0,26 0,21 0,19

0,20 0,20 0,32 0,18 0,18 0,21 0,19

0,24 0,19 0,18 0,21 0,20 0,32 0,20

0,22 0,24 0,20 0,21 0,29 0,22 0,24



Finally, a parcellation, in which the primary functions residences (1.), offices (2.) and cultural and recreational facilities (9.) are intermingled with secondary functions urban green areas (12.) and retail (4.), has been simulated. This very strong intermingling results in the highest average potential sustainability values as illustrated in figure 6.4b. However, the amplitude of the values generate in this simulation are identical to the ones generated in the previous simulation.

(a) (b)

Figure 6.4 Very strong functional intermingling (b) result in an relatively high sustainability impact values (a)

Analysis of the sustainability impact matrices (table 5.2) has shown that the land use

1 2 8 2 1 12 9

1 2 1 9 1 12 2

1 9 1 2 1 12 9

2 2 1 9 8 9 1

8 5 2 1 9 2 1

9 8 2 12 1 2 1

9 8 1 12 2 2 5

0,22 0,21 0,19 0,21 0,28 0,32 0,25

0,22 0,21 0,24 0,29 0,28 0,30 0,24

0,23 0,29 0,25 0,21 0,29 0,31 0,24

0,20 0,21 0,24 0,28 0,19 0,25 0,28

0,18 0,26 0,20 0,26 0,23 0,21 0,22

0,22 0,18 0,21 0,32 0,24 0,20 0,23

0,21 0,19 0,28 0,32 0,22 0,20 0,25

(a) (b)

(c) (d)

Figure 6.5 Several functionalistic configurations (a,c) and there corresponding impact calculation (b,d)

1 3 1 3 3 1 3

1 3 1 1 3 1 3

1 1 3 1 1 3 1

3 1 3 3 1 1 3

1 3 3 1 3 3 3

1 3 1 1 3 1 1

3 1 1 1 3 3 1

0,09 0,06 0,09 0,06 0,06 0,09 0,06

0,10 0,07 0,10 0,10 0,06 0,09 0,06

0,10 0,10 0,06 0,10 0,10 0,06 0,09

0,06 0,09 0,07 0,07 0,10 0,09 0,08

0,09 0,07 0,07 0,09 0,06 0,07 0,06

0,09 0,06 0,10 0,10 0,07 0,09 0,09

0,06 0,10 0,09 0,10 0,06 0,06 0,10

3 4 10 3 4 3 3

10 3 4 4 10 10 3

4 3 10 3 3 10 4

3 4 4 10 3 10 4

3 4 10 3 3 10 4

10 4 3 3 4 10 4

3 4 3 10 10 3 10

0,14 0,15 0,16 0,14 0,15 0,14 0,14

0,15 0,14 0,15 0,14 0,16 0,16 0,14

0,15 0,14 0,16 0,14 0,13 0,17 0,15

0,14 0,15 0,14 0,15 0,13 0,17 0,15

0,14 0,15 0,16 0,14 0,14 0,16 0,15

0,16 0,15 0,14 0,14 0,15 0,17 0,15

0,14 0,15 0,14 0,15 0,17 0,13 0,16


combinations used in the tests above have been found as being relatively fertile. But does this mean that the final sustainability impact value is proportional to the level of functional diversity? In order to draw conclusion in this regard, it is also interesting to analysis unfertile land use combinations. Combinations with companies & industries have proven to be less compatible, especially in combination with residences, cultural & recreational facilities and sport facilities (table 5.3). Several configurations with different degrees of diversity using these land uses have been simulated. The results, illustrated in figure 6.5, indicate that functional intermingling of urban land uses not necessary result in positive sustainability impacts. The first configuration – a mix of residences and industrial land uses – even potentially result in high negative sustainability impacts. But also same parcels in the second configuration show a lower value compared the mono‐functional areas.

Based on these findings can be concluded that functional intermingling does not automatically result in (potential) positive impacts. The first series of tests does indicate that there is relationship between the number of different function and the height of the potential impact value. Various land uses often score higher then two identical land uses as depicted in the sustainability impact matrices. Therefore, a higher degree of diversity might result in a higher sustainability impact value. However, the challenge is to find the right configuration on urban functions. The case study described in the next section will give insight in how to achieve this.

6.2 Case Study: Europoint Rotterdam Three office towers are located next to the Marconi‐square in western Rotterdam, and are known as the Europoint‐buildings (Fig. 6.1), also popularly known as ‘The Peak’ (Dutch: de Punt). The complex consist of a building named ‘Overbeekhuis’ (Europoint I) build in 1965 and three office towers of 90 meters high build in the period 1971‐1975: Europoint II, III and IV (Wikipedia, 2011). These 22‐story buildings, each offering 33.000 square meter of rentable space, are located at the edge of Merwe‐Vierhavens, a port area mainly equipped for the transshipment of fruit. However, this is likely to change in the near future as this industrial area will be ‘returned’ to the city.

The Europoint complex is located next to an important public transport junction: Marconi square. The location is encapsulated by an industrial area to the south and three (mainly) residential areas: Witte Dorp, Tussendijk and Spangen. However, the project is separated from these residential areas by the S114, which can be characterized as a barrier (Fig. 6.2).

Figure 6.6 Europoint II, II and IV Figure 6.7 The location of the Europoint Towers



To the south‐east of the location Dakpark Vierhavenstrip has been realized only recently; a huge shopping boulevard with an urban green park on top of it.

At the time of the build of Europoint II and III, the real estate market collapsed, and for some the towers stood vacant. Surprisingly, the municipality decided to purchase the buildings in 1976 and established two departments in the two towers (Gemeente Rotterdam, 2012). The municipality was hoping for a catalytic effect on the development of the adjacent industrial area. The allocation of 2800 employees was expected to lead to small scale service establishments and stimulate urban activity in the area which would increase the urban quality significantly. Unfortunately, the municipality did not succeed in their objective and will now move the departments to another location, leaving 66.000 square meters of empty office space behind.

Europoint IV has recently been baptized to Rotterdam Science Tower (RST). This tower provides accommodation for several companies in the field of Health & Life Science (Gemeente Rotterdam, 2012). The Initiators – the municipality of Rotterdam and Erasmus MC – have so far successfully established five companies which are active in this professional field in the RST. Furthermore, an academy of Zadkine is also located in the building. Nevertheless, 8000 square meters of rentable space is still vacant.

Given the current market conditions, it will be a huge challenge to find new occupants for the vacant space of these three buildings. Therefore, all possibilities will have to be considered, including redevelopment for other utilities. This actuality of this task, the scale of the towers, the functional diversity of the neighborhood and the absence of a specified program of demands makes this case study the ideal testing ground for SIAM. Furthermore, SIAM will give insight to the contribution of the project’s surroundings in terms of urban quality which was the initial object of the municipality in the first place.

6.3 Project data In order to calculate the potential sustainability impacts, several project data inputs are required. First of all, the parcels which will be incorporated in the calculation process need to be identified by the user. In this case, the project boundary is set by drawing a circle with a radius of approximately 300 meters around the project (fig. 6.8). Land uses of each parcel located within this boundary will be considered in the calculation process. Also the project surroundings have been determined for analysis purposes. For this case study, a total of 71 parcels have been identified as illustrated in the parcel ID Map in appendix IV.

Next, all land uses within this perimeter need to be identified and subsequently classified by means of the floors classification and land use classification procedures as described in chapter 4. The function map in figure 6.9 illustrates the main functions surrounding the project area. Although located at the edge of an industrial area, not all land uses have been classified as Companies & Industrial. The industrial area also houses a bar, a nightclub (both catering), some offices and a large retail company. The three residential areas to the north and to east of the project, are mainly residential but also house a certain degree of services, educational facilities, offices and retail. A detailed ID‐table which includes all land uses of all considered parcels has been added to appendix V.


Figure 6.8 Neighborhood Assessment: project (1.), Project Surrounding (2.) and Project Area (3.)

Figure 6.9 Function Map



6.4 The Alternatives For testing SIAM using this particular case study, four alternatives for the functional arrangement of the three towers will have to be composed. Analyzing these alternatives will give insight to which alternative anticipates on its surroundings the best and why. The knowledge about fertile land use combinations acquired by means of data analysis as described in the previous chapter, comes in hand for composing the alternatives. Each of the alternatives will be described below and an overview is depicted in table 6.1.

Alternative A ‐ ‘Business as Usual’ Alternative A can be described as the business as usual alternative, or the zero alternative. No land use changes have been implemented for this alternative; the office and partly educational function for all towers have been retained. This alternative therefore assumes an interested party will be found for letting all vacant offices space, despite the difficult market conditions.

Alternative B ‐ ‘Rotterdam Science Complex’ This second alternative builds on the initiated idea of creating a science tower. This concept is extended over all of towers in this alternative, thus creating a science complex in multiple field of expertise. This might be an interesting alternative since research indicated a high compatibility level of the combination between educational and companies & industry. This alternative therefore tries to connect and take advantage of its surroundings. Alternative C ‐ ‘Crossing the Barrier’ This third alternatives foresees in a high degree of residential functions. The towers rise high above its surrounding making it an interesting for residents to live in. Residents who cross the barrier and enter this urban area might have positive impacts for the urban quality of the area. However, the data analysis in the previous chapter has indicated the incompatibility of residential land use and companies & industry. The highly industrial surrounding may result in conflicts in terms of sustainability. The success of this alternative highly depends on the various other land uses in the neighborhood which will have to balance out the negative impacts which will occur as a result of the intermingling with companies & industries.

Business as Usual Science Complex Crossing Barrier Unité d'Habitation

Location Level Alternative A Alternative B Alternative C Alternative D

Plinth Offices Educational Residentual Catering

Center Section Offices Offices Residentual Residentual

Top Section Offices Offices Residentual Residentual

Europoint III ‐ low rise Plinth Offices Offices Services Urban Green

Plinth Offices Healthcare Residentual Residentual

Center Section Offices Healthcare Residentual Residentual

Top Section Offices Offices Residentual Agricultural

Europoint IV ‐ low rise Plinth Offices Catering Urban Green Area Retail

Plinth Educational Educational Residentual Education

Center Section Offices Educational Residentual Offices

Top Section Offices Offices Residentual Sport

Europoint IV ‐ high rise

Europoint III ‐ high rise

Europoint II ‐ high rise

Table 6.1 Land use Overview for each of the alternatives


Alternative D ‐ ‘Unité d’Habitation’ This fourth and final alternative presents a combination of alternatives A, B and C. A balanced mix of urban land use might result in relatively high sustainability impacts by trying to connect to neighboring land uses in all direction. This alternative is named after a living complex designed by Le Corbusier which contained internal shopping street and facilities on the roof for its inhabitants. The high level of functional diversity on project level might result in high sustainability impact values.

6.5 Results After simulating all alternatives a comparison can be made and the best alternative can be selected. For this simulations each of the aspects are assumed to have equal weight factors. Figure 6.10 presents the average sustainability impact values for the all floors at project level (as depicted figure 6.8). These values indicate to what extent sustainability impact can be realized as a result of a certain functional arrangement which obviously differs in each alternative. The results presented below designate alternative D as being the best alternative since the high average sustainability impact score is obtained using this specific functional arrangement. However, the radar graph indicates that alternative D is not superior for every sustainability aspect. Especially in the field of energy other alternative score evidently higher. In the field of flexibility and social safety alternative D is outclassed by alternative C. The PPP and Vitruvian graph on the right show only little, negligible differences.

Figure 6.10 Alternative comparisons on project level

Energy

Air

Accessability to

services

Social Safety

Noise nuisance

Area and Identity

Social Cohesion



Quality perception

Area

Flexability

5 6 7 8 9 10 11 12 13 14 15

Alternative A 2 0,28 0,10 0,14 0,12 0,11 0,20 0,17 0,15 0,20 0,10 0,28

Alternative B 1 0,23 0,11 0,16 0,17 0,10 0,22 0,17 0,25 0,22 0,15 0,35

Alternative C 11 0,14 0,11 0,16 0,24 0,12 0,16 0,16 0,16 0,23 0,16 0,44

Alternative D 7 0,17 0,14 0,21 0,19 0,10 0,21 0,19 0,31 0,30 0,21 0,40

Sustainability Aspects

0,18

0,21Avarage Compatibility

Value

3 3

0,17

0,19

Energy

Air


Social Safety

Noise nuisance

Area and IdentitySocial Cohesion




Flexability

Planet

People Profit

Utility Value

Experiential Value

Future Value



In practice, the weights for each of the sustainability will not be equal. The influence of involved stakeholders has been discussed extensively in this chapter and the values of these stakeholders will be decisive in selecting the best alternative.

Example: The case introduction already mentioned the municipality as being an important stakeholder because of their involvement in the science tower. Moreover, municipalities are always involved in urban development projects in the Netherlands, usually as one of the main stakeholders. Suppose the municipality of Rotterdam has decided to focus the future value of an area, as a response to the vacancy issues described in the first chapter of this report. Using the pair‐wise comparison methodology of AHP the weight factors have been calculated by displacement in this municipality point of view (appendix VIII and framed in red in table 6.2). The future‐minded approach has resulted in relatively high weights for the aspects Area & Identity, Social Cohesion and Flexibility, which make sense as these values together determine the future value (figure 4.8). Weights for the parents People, Profit & Planet are assumed to be equal in order to ensure the balancing of these capitals (Elkington, 1998). In this way the earlier presented outcomes of SIAM will be matched to stakeholders’ values. Nevertheless, alternative D still comes out best (table 6.2).

It is interesting to find out to what extent the model changes as a result of alternating weight factors. This can be analyzed using a sensitivity analysis (Dalalah, AL‐Oqla, & Hayajneh, 2010) which will illustrate the effect of altering weight factors. First, consider the sustainability aspect energy. The share of this aspect is increased to an extreme of 90% of the mail goal, leaving 10 % for the others in the same group to share while keeping the proportionality between each. In this case, the outcome is exactly the same since the weight factor for energy was already 80%.

This weight increase process has been repeated for each of the sustainability aspects (Table 6.2). Extreme increase of each of the aspects has resulted for two scenarios in different outcomes: an increase for social safety and noise nuisance which is explainable by observing the results presented in figure 6.10. Alternative D is superior for almost every single aspect. However, alternative C outclasses alternative D when it comes down to social safety. By increasing the relatively low weight factor for social safety extremely, alternative C comes out best. This sensitivity analysis confirms the high influence of stakeholders in contemporary urban development. A more varied alternative comparison outcome for the

Table 6.2 Results sensitivity analysis

Energy

Air

Accessability to

services

Social Safety

Noise nuisance

Area and Identity

Social Cohesion

Space and Land

Usage

Sustainable

Transport

Quality perception

Area

Flexability

A B C D

0,80 0,20 0,07 0,13 0,05 0,31 0,45 0,08 0,24 0,13 0,54 0,20 0,20 0,21 0,22

0,90 0,10 0,07 0,13 0,05 0,31 0,45 0,08 0,24 0,13 0,54 0,20 0,20 0,21 0,22

0,10 0,90 0,07 0,90 0,05 0,31 0,45 0,08 0,24 0,13 0,54 0,15 0,17 0,20 0,21

0,80 0,20 0,90 0,01 0,01 0,03 0,05 0,08 0,24 0,13 0,54 0,20 0,20 0,21 0,23

0,80 0,20 0,01 0,90 0,01 0,03 0,05 0,08 0,24 0,13 0,54 0,18 0,20 0,23 0,22

0,80 0,20 0,01 0,01 0,90 0,03 0,05 0,08 0,24 0,13 0,54 0,19 0,18 0,18 0,19

0,80 0,20 0,01 0,02 0,01 0,90 0,06 0,08 0,24 0,13 0,54 0,21 0,21 0,20 0,22

0,80 0,20 0,01 0,02 0,01 0,06 0,90 0,08 0,24 0,13 0,54 0,19 0,20 0,21 0,22

0,80 0,20 0,07 0,13 0,05 0,31 0,45 0,90 0,03 0,01 0,06 0,18 0,19 0,18 0,22

0,80 0,20 0,07 0,13 0,05 0,31 0,45 0,01 0,90 0,02 0,07 0,20 0,20 0,21 0,23

0,80 0,20 0,07 0,13 0,05 0,31 0,45 0,01 0,03 0,90 0,06 0,17 0,18 0,17 0,19

0,80 0,20 0,07 0,13 0,05 0,31 0,45 0,02 0,05 0,03 0,90 0,21 0,20 0,22 0,23

Sustainability Aspects Alternative Impact Values

Sensitivity Analysis


alternatives would probably have resulted in more diverse range of outcomes in the sensitivity analysis. Stakeholder will decide which alternative suits them best based on their own preferences.

Furthermore, it’s interesting to analyze how individual land uses do in terms of sustainability impact value. Table 6.3 depicts an overview of all sustainability impact values of each individual land uses within the project area. Underlying building, location and area values (figure) are also included in the overview in order to enable the user to analyze which subject floor score relatively good on what level. E.g. the plinth function of parcel 5 (urban green area) generates a relative high sustainability impact value on location level, indicating that this functions is highly compatible with its direct surroundings in terms of sustainability (table 6.3). An extensive analysis output sheet for this specific subject floor (appendix VII) shows that this is mainly due to the high sustainability impact values for land‐ & space usage, quality area perception and flexibility as a result of adjacent offices and residences. It’s also possible to generate these outputs for a single aspect opposed to the overall impact values, allowing the user to focus on a single aspect.

This example shows how the combined outputs of SIAM provide insight about potential sustainability impacts and provides insight in the formation of these values, indicating to what extent land uses benefit from its surroundings.

Table 6.3 Detailed overview of sustainability impact values for each subject floor

Final Sustainability Im

pact Value

Building Su

stainability Im

pact Value

Location Sustainab

ility Im

pact Value

Area Su

stainability Im

pact Value


pact Value

Building Su

stainability Im

pact Value

Location Sustainab

ility Im

pact Value

Area Su

stainability Im

pact Value


pact Value

Building Su

stainability Im

pact Value

Location Sustainab

ility Im

pact Value

Area Su

stainability Im

pact Value


pact Value

Building Su

stainability Im

pact Value

Location Sustainab

ility Im

pact Value

Area Su

stainability Im

pact Value

1 1 Basement P

2 1 Plinth P 0,21 0,21 0,21 0,19 0,20 0,20 0,19 0,19 0,18 0,17 0,19 0,16 0,22 0,23 0,20 0,20

3 1 Center P 0,18 0,18 0,16 0,19 0,21 0,21 0,19 0,20 0,18 0,17 0,18 0,16 0,21 0,23 0,19 0,19

4 1 Top P 0,18 0,17 0,16 0,19 0,20 0,21 0,17 0,19 0,17 0,17 0,18 0,16 0,22 0,25 0,19 0,22

5 2 Basement P

6 2 Plinth P 0,16 0,15 0,16 0,18 0,19 0,17 0,18 0,22 0,18 0,17 0,19 0,15 0,21 0,22 0,23 0,15

7 2 Center P 0,16 0,15 0,15 0,19 0,19 0,17 0,18 0,23 0,17 0,17 0,19 0,16 0,21 0,24 0,22 0,16

8 2 Top P 0,16 0,15 0,15 0,19 0,18 0,18 0,17 0,19 0,17 0,17 0,18 0,16 0,28 0,31 0,26 0,27

9 3 Basement P

10 3 Plinth P 0,17 0,15 0,17 0,19 0,21 0,21 0,19 0,20 0,17 0,17 0,16 0,16 0,20 0,23 0,18 0,19

11 3 Center P 0,17 0,15 0,16 0,19 0,18 0,18 0,17 0,20 0,17 0,17 0,17 0,16 0,18 0,20 0,18 0,16

12 3 Top P 0,17 0,15 0,16 0,19 0,18 0,17 0,17 0,19 0,17 0,17 0,17 0,16 0,18 0,19 0,19 0,16

13 4 Basement S

14 4 Plinth S 0,22 0,25 0,22 0,18 0,21 0,25 0,20 0,18 0,21 0,25 0,19 0,20 0,21 0,25 0,20 0,19

15 4 Center S 0,20 0,25 0,16 0,19 0,20 0,25 0,16 0,19 0,21 0,25 0,19 0,20 0,21 0,25 0,19 0,20

16 4 Top S

17 5 Basement P

18 5 Plinth P 0,17 0,00 0,16 0,18 0,17 0,00 0,16 0,18 0,20 0,00 0,22 0,19 0,26 0,00 0,26 0,27

19 5 Center P

20 5 Top P

21 6 Basement P

22 6 Plinth P 0,18 0,00 0,18 0,18 0,18 0,00 0,19 0,18 0,22 0,00 0,19 0,27 0,16 0,00 0,15 0,20

23 6 Center P

24 6 Top P

1

Alternative A Alternative B Alternative C Alternative DAvarage Compatibility

Value



For creating an easier readable overview of all sustainability impact values to create 3D map which places the values for the subject floor in their actual surroundings (Figure 6.11). However, this is not within the abilities of SIAM which will only deliver the values for each floor. An external visualization program is needed to produce such a 3D map.

Figure 6.11 Sustainability impact 3D map for alternative D

6.6 Conclusion The chapter has presented an answer to the final sub‐question: Can functional diversity indeed be considered as a precondition for creating a sustainable urban environment?

Experimentation with SIAM has shown that functional diversity not necessarily results in positive sustainable impacts. It is the challenge to combine those land uses which together create a synergetic solution. The matrices analysis made earlier will be helpful in finding the right land use combinations which actually result in positive impacts. It is essential to interact with land uses ‘offered’ by the surroundings of a specific project. Only when acted upon those opportunities optimum sustainability impacts can be realized.

The case study Europoint was found as the ideal testing ground for SIAM. Several alternatives have been simulated: ‘business as usual’, ‘science center’, ‘crossing barriers’ and ‘Unité d ‘Habitation’. The configuration of each of the alternative is partly based on knowledge gained in the matrices analysis about fertile function combinations and partly based on functionalistic characteristics of the Europoint area. The generated outputs of SIAM indicated that the functional arrangement of Alternative D will (potentially) result in the highest sustainability impact values. The mix of land uses on project level respond better to its surroundings opposed to the other alternatives.

Sensitivity analysis has confirmed stakeholders’ values as a very important variable. Stakeholders highly affect the outcomes of SIAM depending on their own values and each of the sustainability impact scores. Incorporating these values enables the user to match the acquired sustainability impacts to stakeholders’ interests. Thus the sustainability impacts are tailored to the wishes of (a) involved stakeholder(s), providing insight to what extent a functionalistic arrangement can be beneficial for them.


In conclusion, this case study has revealed the enormous potential of SIAM. This tool not only simulates sustainability impacts, but also enable the user the compare alternatives and match them to stakeholders’ values. Furthermore, the outcomes can be analyzed thoroughly, providing insight about the formation of values and thus creating a better understanding in how sustainability impacts as a result of functional intermingling in a complex urban environment come about.



7. Conclusion and Recommendations

7.1 Conclusions A systematic analysis of possible synergetic solutions by (re)positioning functions in an urban environment is missing. The challenge is to comprehend the effect of possible function combinations on economic, ecological and socio‐cultural values in relation to each other.

The added value of functional diversity and the opportunities offered by intermingling of urban land uses is widely acknowledged. Dutch planning and designing tend to apply defensive and narrowed approaches though when it comes down to function allocation in urban development. An offensive and more integrated approach is needed which systematically investigates potential added value to a sustainable urban environment as result of (re)arranging urban functions.

This research is aimed at filling this gap by providing a tool which provides insight into the potential sustainability impacts as a result of a certain configuration of urban functions in a specific urban context. Current practice in the process of composing a program of demands for an area of building starts with mapping of stakeholders’ values and wishes in the process of composing a program of demands for an area of a building. Subsequently, concrete solutions are developed based on knowhow and intuition. A comprehensive model could be very helpful in this process, by mapping out the opportunities and by enabling simulation of alternatives. The tool which measures sustainability impacts as a result of co‐existence of certain land uses. The tool which generates a complete overview of potential solutions would make the intuition factor in urban development redundant.

For the development of a sustainability impact assessment model (SIAM), two methodologies have been combined: Analytical Hierarchy Process (AHP) and an aggregation methodology developed by Taleai et al. (2007) although the latter has been slightly adjusted for the purpose this research.

AHP is used as multi‐criteria decision‐making tool. Research has shown that many criteria have to be considered in sustainable urban development: a total of 33 sustainability aspects have been identified. It is impossible for aspects to consider every individual aspect Applying AHP ensures that each of these aspects will be incorporated. AHP structures a decision problem into a hierarchy with a goal, decision criteria, and alternatives. Within the framework of this research, the goal is to maximize positive sustainable impacts by strategically arranging urban functions. The criteria are the 11 selected sustainability aspects. And the alternatives are multiple functional arrangements for a specific urban development project. By assessing the sustainability impacts in the field of each of the sustainability aspects, alternative can be compared on sustainability impacts levels.

For assessing the impacts in the field of a single sustainability aspect the aggregation methodology of Taleai et al. has been adopted broadly, only minor adjustments were deemed to be necessary. Aggregation at area level has been added to the methodology and the calculation procedure has been adjusted slightly in order to consider function combinations in the diagonal direction. The aggregation methodology utilizes AHP and

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majority additive‐ordered weighted averaging (MA‐OWA). The result is an aggregation value that represents the majority and more or less indicating the influence of the minority, thus creating a more precise aggregation value.

The aggregation methodology is founded on sustainability impact matrices which contain impact values for each unique function combination. One sustainability matrix for each of the eleven considered sustainability aspects has been constructed using expert judgments. Analyze of these matrices have confirmed the enormous potential of functional diversity which is described in literature (chapter 3).

Another important input for the aggregation methodology is the case study data. SIAM requires detailed and structured spatial data about the project surroundings which will be constructed using land use and floor classifications. Furthermore, the aforementioned stakeholders’ values represented by weight factors for each of the sustainability aspects should be entered. And finally, the project alternatives have to be determined.

The final and highly significant input is the stakeholders’ values. The participation and power of stakeholders in urban development is increasing as described in chapter 1. Stakeholders will have a decisive role in urban development. Incorporating their requirements and values is therefore essential. SIAM foresees in this by enabling definition of weight factors for each of the criteria. The user of SIAM is expected to retrieve these values which could be done using AHP and pair‐wise comparison as described in the case study.

This combined methodology then calculates a sustainability impact value aligned to stakeholders’ values for each floor of each parcel within a delineated urban area. This process is repeated for all the alternatives. The outputs of SIAM will indicate what the impact is of each alternative on building, location and area level, allowing the user to make a weighed choice for the best alternative. Furthermore, the outputs will enable the user to analyze the outcome thoroughly, providing the user insight about opportunities for a specific project with specific opportunities

Based on testing and utilizing SIAM in several studies the main research question can be answered, which is:

“Does intermingling of urban land uses contribute integrally to creating a sustainable urban environment and how could the resulting (potential) sustainability impacts be analyzed systematically within a specific urban context?”

The answer to the second part of the question, concerning the systematical analysis of functional diversity, has been found in the development of SIAM. Calculating and visualizing sustainability impact for each of the individual aspects allows the user to analyze the effect of functional intermingling systematically.

The first part is answered by means of testing and experimenting with SIAM. The results have shown that functional diversity not necessarily results in positive sustainable impacts. It the challenge to combine those land uses which together create a synergetic solution. The matrices analysis made earlier will be helpful in finding the right land use combinations which actually result in positive impacts. It’s essential to interact with land uses ‘offered’ by the surroundings of a specific project. Only when acted on those opportunities optimum sustainability impacts can be realized.



SIAM can be used both as measurement tool, as described above – and as communication tool. Potential impacts can be communicated using visualizations and graphs produced in SIAM to other concerned stakeholders. The results of alternative analysis in SIAM may give rise to approach certain stakeholders. SIAM will then come in handy as a communication tool to present the sustainability potentials of certain land use configurations.

It’s important to emphasize that SIAM will only calculate potential sustainability impacts. These potential values might be restricted and in some case reinforced by local characteristics. SIAM will give clear indications of potential sustainability impacts and will give rise to investigate certain alternatives further.

7.2 Recommendations For constructing the sustainability matrices – which form the foundations of SIAM – only one expert has been approached for each sustainability aspect. This was a conscious choice made for manageability purposes. Although several measures have been taken to ensure the reliability of these single data inputs, it would be better to involve multiple experts for each individual sustainability aspect in order to enhance the reliability of this important data. Several scientific methodologies are available to check or to ensure the reliability of the data provided by a limited number of experts, like the Delphi method or Cohen’s Kappa.

Second, combinations of the broadly defined land use categories were sometimes different to assess according to some of the experts. Educational land uses for instance could refer to a small elementary school or a huge university. This is obviously a huge difference which might effect the assessment of impacts as a result of certain functional combinations with education. Decomposing the broadly defined land use categories into smaller specified land use categories would sharpen the assessments of experts, thus sharpen the output of SIAM. Moreover, once again was chosen for these broad definitions for manageability issues.

Third, the number of sustainability aspects considered in this research was limited to 11. These were selected after consultation with several experts as the most sensitive aspects for functional diversity. However, increasing this number would result in more precise outputs, thus giving a better indication of potential sustainability impacts. It will not be necessary to incorporate all aspects since some of them or not at all affect by urban land use combinations, like wind for instance. However, it is conceivable to increase the number of considered aspects in order to sharpen the outcomes of SIAM.

These are three recommendations in regard to the quality and reliability of SIAM. Additional research would also improve the use of SIAM. For incorporating stakeholders’ values correctly in SIAM, it might be interesting to some additional research about how to match these stakeholders’ values. AS described in this report, many stakeholders are usually involved in urban development, often with diverging values. Such a research might be beneficially for the utilization of SIAM in order to incorporated these values correctly.

Finally, a practical recommendations: the way of entering the project data in SIAM is somewhat old fashion and time‐consuming. It would be interesting to connect SIAM to Geographical Information Systems (GIS) in this regard. This would simplify the processing of project data, therewith increasing the ease of use of SIAM.

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Overall can be concluded that a good foundation is created for SIAM, based on literature and expert interviews. However, there is certainly room for improvement. Processing these recommendations described above would result in the perfect tool which systematically analyses the potential sustainability impacts as a result of a (re)arrangement of urban land uses in a densely built‐up urban area, allowing the user to experiment with various land use configurations in order to find the perfect balance.



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Expertise

List of interviewed experts

Date Expert Background

1 March 28, 2012 Josfine van der Ven Royal HaskoningDHV Sustainable Development

2 May 14, 2012 Therese van Gijn Royal HaskoningDHV (sustainable) urban development

3 May 30, 2012 Dorine Epping Royal HaskoningDHV Designer of Public Space

4 June 6, 2012 Roelof Westerhof Royal HaskoningDHV sustainable land usage

5 June 27, 2012 Jos Schild Royal HaskoningDHV BREEAM

6 various Martine Verhoeven Royal HaskoningDHV CREM and Sustainability

List of approached experts for data collection

Sustainability Aspect Expert Company Background

1 Energy Hans Peter Oskam Royal HaskoningDHV Sustainable Energy

2 Air Harrie van der Putten Royal HaskoningDHV Environmental specialist

3 Accessability to services Jos Schild Royal HaskoningDHV BREEAM

4 Social Safety Dorine Epping Royal HaskoningDHV Designer of Public Space

5 Noise nuisance Jeroen Kramer Royal HaskoningDHV Noise consultant

6 Area and Identity Maike de Lange Royal HaskoningDHV Sustainable Environments

7 Social Cohesion Martine Verhoeven Royal HaskoningDHV CREM and Sustainability

8 Space and Land Usage Therese van Gijn Royal HaskoningDHV (sustainable) urban development

9 Sustainable Transport Thijs de Bruin Royal HaskoningDHV Mobility

10 Quality perception Area Hans Buchi Royal HaskoningDHV Urban design

11 Flexability Ellis ten Dam Royal HaskoningDHV Strategic real estate development



Summary

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Appendices

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Appendix I: Scenario Output Sheet

Avarage Compatibility Value

Energy

Air


Social Safety

Noise nuisance

Area and Identity

Social Cohesion




Flexability

Planet

People

Profit

Utility Value

Experiential Value

Future Value

Weights >> 1,00 1,00 1,00 1,00 1,00 1,00 1,00 1,00 1,00 1,00 1,00

Project Project Average 0,17 0,28 0,10 0,14 0,12 0,11 0,20 0,17 0,15 0,20 0,10 0,28 0,19 0,15 0,18 0,17 0,11 0,20

Surroundings SurroundinAverage 0,17 0,26 0,08 0,21 0,13 0,11 0,22 0,16 0,15 0,25 0,11 0,21 0,17 0,17 0,18 0,19 0,11 0,18

Area Area Average 0,18 0,21 0,10 0,18 0,18 0,11 0,21 0,15 0,21 0,24 0,13 0,30 0,15 0,17 0,22 0,19 0,14 0,21




4 1 Top 1Top Project 0,18 0,26 0,10 0,17 0,14 0,11 0,20 0,18 0,16 0,20 0,09 0,31 0,18 0,16 0,19 0,18 0,12 0,21




8 2 Top 2Top Project 0,16 0,27 0,10 0,12 0,12 0,12 0,18 0,17 0,13 0,17 0,09 0,26 0,19 0,14 0,16 0,16 0,11 0,19




12 3 Top 3Top Project 0,17 0,28 0,10 0,13 0,12 0,12 0,18 0,17 0,13 0,19 0,09 0,25 0,19 0,14 0,16 0,17 0,11 0,18







19 5 Center 5Center Project

20 5 Top 5Top Project



23 6 Center 6Center Project

24 6 Top 6Top Project













37 10 Basement 10Baseme Area

38 10 Plinth 10Plinth Area 0,17 0,40 0,07 0,12 0,08 0,12 0,23 0,10 0,12 0,27 0,09 0,09 0,23 0,13 0,14 0,20 0,10 0,14

39 10 Center 10Center Area

40 10 Top 10Top Area

41 11 Basement 11Baseme Surroundings


43 11 Center 11Center Surroundings


















Tripple Bottom Line Vitruvian ClassificationScenario

A(Incorporated) Sustainability Aspects



Appendix II: Sustainability Aspects Reduction

92|



94|

Appendix III: Sustainability Impact Matrices



96|



98|



100|



102|



104|



Appendix IV: Parcel ID Map

106|

Appendix V: Land Use ID Table

1 Residential 5 Catering 9 Cultural & Recreational 13 Water(retention)

2 Offices 6 Services 10 Sport 14 Transportation

3 Companies & Industry 7 Educational 11 Agricultural

4 Retail 8 Healthcare 12 Urban green areas

71 Layer 0 (plinth)

1 7 Educational 2 Offices 2 Offices

2 2 Offices 2 Offices 2 Offices

3 2 Offices 2 Offices 2 Offices

4 5 Catering 2 Offices

5 2 Offices

6 2 Offices

7 14 Transportation 14 Transportation

8 3 Companies & Industry 14 Transportation

9 2 Offices 2 Offices

10 3 Companies & Industry

11 2 Offices




15 9 Cultural & Recreational




19 2 Offices

20 2 Offices

21 2 Offices




25 4 Retail



28 4 Retail

29 4 Retail


31 3 Companies & Industry 3 Companies & Industry



34 2 Offices

35 1 Residential

36 1 Residential

37 1 Residential

38 1 Residential

39 1 Residential

40 1 Residential

41 1 Residential

42 1 Residential 1 Residential


44 4 Retail 1 Residential

45 6 Services 1 Residential

46 6 Services 1 Residential

47 14 Transportation

48 6 Services 2 Offices


50 4 Retail



53 7 Educational 7 Educational




57 5 Catering





62 7 Educational




66 4 Retail 1 Residential



69 1 Residential

70 12 Urban green areas


Function Allocation

Layer ‐1 (basement) Layer 1+ (center section) Toplayer (top section)



Appendix VI: Detailed Alternative Comparison Sheet

Parcel / floor:

5Plinth

terdam

Energy

Air

Accessability to

services

Social Safety

Noise nuisance

Area and Identity

Social Cohesion



Quality perception

Area

Flexability

Planet

People

Profit

Utility Value

Experiential Value

Future Value

56

78

910

1112

1314

15

17

18

1921

22

23

1Alternative A

Offices

20,28

0,10

0,12

0,10

0,12

0,21

0,19

0,13

0,21

0,10

0,24

0,19

0,15

0,17

0,17

0,11

0,19

2Alternative B

Offices

20,28

0,10

0,12

0,12

0,12

0,23

0,19

0,14

0,23

0,10

0,21

0,19

0,16

0,17

0,18

0,12

0,19

3Alternative C

Services

60,18

0,08

0,24

0,26

0,12

0,21

0,20

0,25

0,31

0,20

0,35

0,13

0,21

0,28

0,21

0,19

0,23

4Alternative D

Urban

green areas

120,12

0,26

0,23

0,08

0,11

0,17

0,21

0,51

0,34

0,45

0,47

0,19

0,16

0,44

0,29

0,21

0,25

Europoint Complex Rotterdam

0,17

0,17

0,20

0,26

Alternative Analysis

3

Vitruvian Triad

Avarage Compatibility

Value

3


Triple Bottom Line

Energy

Air


Social Safety

Noise nuisance

Area and Identity

Social Cohesion




Flexability


Planet

People

Profit

Triple Bottom Line

Utility Value

Experiential

Value

Future

Value

Vitruvian Triad

108|

Appendix VII: Detailed Subject Floor Output Sheet

Plot5Plinth

Energy

Air


Social Safety

Noise nuisance

Area and Identity

Social Cohesion




Flexability

Proiect

Location

Area

12Weight factors >>

0,00

0,00

0,00

0,00

0,00

0,00

0,00

0,00

0,00

0,00

0,00

Function subject floor =Urban green areas

1Residential

0,12

0,27

0,53

0,08

0,12

0,27

0,53

0,53

0,53

0,53

0,53

426

2Offices

0,12

0,27

0,27

0,08

0,12

0,27

0,27

0,53

0,27

0,53

0,53

313

3Companies & Industry

0,12

0,12

0,12

0,08

0,08

0,08

0,12

0,27

0,12

0,27

0,08

222

4Retail

0,12

0,27

0,12

0,08

0,12

0,08

0,12

0,53

0,27

0,12

0,53

7

5Catering

0,12

0,27

0,27

0,08

0,08

0,27

0,12

0,53

0,27

0,27

0,53

12

6Services

0,12

0,27

0,12

0,08

0,12

0,12

0,12

0,53

0,27

0,12

0,53

3

7Educational

0,12

0,27

0,12

0,08

0,08

0,08

0,27

0,53

0,53

0,53

0,53

8

8Healthcare

0,12

0,27

0,12

0,08

0,12

0,27

0,27

0,53

0,27

0,53

0,53

9Cultural & Recreational

0,12

0,27

0,12

0,12

0,12

0,12

0,27

0,27

0,53

0,53

0,53

1

10Sport

0,12

0,27

0,12

0,08

0,12

0,27

0,27

0,27

0,53

0,53

0,53

1

11Agricultural

0,12

0,53

0,12

0,12

0,12

0,27

0,12

0,53

0,53

0,27

0,53

1

12Urban green areas

0,12

0,53

0,12

0,12

0,12

0,27

0,12

0,27

0,12

0,27

0,53

1

13Water(retention)

0,12

0,12

0,12

0,12

0,12

0,53

0,27

0,53

0,53

0,27

0,53

14Transportation

0,12

0,12

0,12

0,12

0,05

0,08

0,12

0,12

0,27

0,27

0,08

15

Energy

Air

Accessability to

services

Social Safety

Noise nuisance

Area and

Identity

Social Cohesion

Space and Land

Usage

Sustainable

Transport

Quality

perception Area

Flexability

Planet

People

Profit

Utility Value

Experiential

Value

Future Value

12

34

56

78

910

11

P

PP

UV

EV

FV

Sustainability Impact Values

0,12

0,26

0,23

0,08

0,11

0,17

0,21

0,51

0,34

0,45

0,47

0,26

0,19

0,16

0,44

0,29

0,21

0,25

Building Level Value

0,00

0,00

0,00

0,00

0,00

0,00

0,00

0,00

0,00

0,00

0,00

0,00

0,00

0,00

Location Level Value

0,12

0,25

0,26

0,08

0,10

0,23

0,22

0,50

0,32

0,38

0,45

0,26

0,00

0,19

0,18

0,00

0,29

0,19

Area Level Value

0,12

0,27

0,20

0,08

0,12

0,11

0,19

0,53

0,36

0,52

0,53

0,27

0,00

0,19

0,14

0,00

0,30

0,24

Europoint Complex Rotterdam

Triple Bottom Line

Vitruvian Triad

Urban green

areas

Avarage

Compatibility

Value

Alternative D

function subject floor =


26

1522

6238

115

Residential

Offices


Retail

Catering

Services

Educational

Healthcare

Cultural & Recreational

Sport

Agricultural

Urban green areas

Water(retention)

Transportation

Area Level

Residential

Offices

Companies & …

Retail

Catering

Services

Educational

Healthcare

Cultural & …

Sport

Agricultural

Urban green areas

Water(retention)

Transportation

Project Levek

9

2

1

Residential

Offices


Retail

Catering

Services

Educational

Healthcare

Cultural & Recreational

Sport

Agricultural

Urban green areas

Water(retention)

Transportation

Location Level

Energy

Air


Social Safety

Noise nuisance

Area and Identity

Social Cohesion




Flexability


Planet

People

Profit

Triple Bottom Line

Utility Value

Experiential

Value

Future Value

Vitruvian Triad



Appendix VIII: AHP Weight Calculation Overview

Documents

Eindhoven University of Technology MASTER A ... · analyses the potential sustainability impacts as a result of a (re)arrangement of urban land uses in a densely built-up urban area