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www.theinternationaljournal.org> RJSSM : Volume: 09, Number: 10, February 2020 Page 25
Interrelationship Between Brownfield development as a mitigating factor
for climate change and critical infrastructure within a metropolis: a case of
Kolkata Metropolitan Area
Mouli Majumdar1 and Joy Sen
2
1 Research Scholar, RCG School of Infrastructure design and Management,
Indian Institute of Technology Kharagpur, West Bengal , India 2Head and professor, Department of Architecture and Regional Planning, Indian institute of Technology
Kharagpur, West Bengal , India. 2Professor, RCG School of Infrastructure design and Management,
Indian Institute of Technology Kharagpur, West Bengal , India
Corresponding Author: Mouli Majumdar
Abstract: The growth of an inclusive and sustainable metropolis is motivated by a close interaction between the
(i) investment and maintenance of it’s critical infrastructure, (ii) maximisation of the available resources and
(iii) incorporation of the technological advances. This growth trajectory is often affected adversely by extreme
climate changes like rise in sea level, heat waves, scarcity of food and frequent floods or storms. One of the
major reasons for this being the negative impact of climate changes on the critical infrastructure of the city
which in turn guides its spatial form. A more compact urban form therefore has positive climate effects of low
carbon emissions, more efficient use of energy, reduced environmental costs for infrastructure, more urban
green spaces. Along with climatic benefits it reduces construction and operational cost of infrastructure,
optimises travel time and encourages interactions creating an environment for innovation.
A metropolitan area expanding at the expense of green areas faces the consequence of drastic climate changes
like frequent flooding, extreme rainfall, floods etc which further aggravates the problem by depleting its
infrastructure. Renewal of Brownfield developments encourages a compact urban form reducing the pressure on
metropolitan expansion. Brownfield development discourages urban sprawl improves environmental conditions
and has other positive economic and ecological effects.
Kolkata Metropolitan Area in this context provides an interesting study opportunity at two levels (i) Kolkata is
one of the most vulnerable flood prone coastal cities considering the hydro-geological factors that influence
climate changes like cyclones, sea-level rise, and storm surges. (ii) The trend of the metropolitan structure
interrelated with its socio-economic condition of Kolkata that is shaped by its physical –environmental setting.
The methodology has a bipartite approach of (a) exploring the factors influencing scope of Brownfield
development at a metropolis level and (b) influence of the critical infrastructure amongst the factors influencing
the Brownfield development on the same scale.
KEYWORDS: Densification, Brownfield development, climate changes, critical infrastructure, fuzzy logic
overlay.
I. Introduction
In this century of rapid urbanisation trend, 90% of the expected world’s population growth will be
absorbed by the developing world. Most of this urbanisation is expected to be in Asian and African countries
(United Nations, 2014; Kotak Institutional, n.d.). This form of urban growth in developing world is not limited
to the incremental extension of existing city or the newly planned cities but also urban fragments and corridors
growing onto dispersed opportunities or activity nodes. Along with the opportunities from agglomeration of
economies, cities today also face multifaceted challenges. These challenges now include climate change
induced vulnerability that results in risks from natural hazards and displacement of population. The conventional
challenges of accelerating demand in several sectors like infrastructure, housing, and transportation further adds
to the pressure.
It can be observed that this wave of rapid urbanisation is simultaneous with the rising impact of climate change
worldwide because as the cities grow so does its dependency on energy consumption and green house gas
emissions. In general there are two approaches observed at city level in response to climate change. One is
adaptation that tries to minimise negative effects of the green house gas and exploit the possible beneficial effect
(Hamin & Gurran, 2009). The other approach is mitigation that reduces green house gas emissions from the
sources and adopts processes or methods to reduce it from the environment.
www.theinternationaljournal.org> RJSSM : Volume: 09, Number: 10, February 2020 Page 26
The repercussions of this climate change is often expressed in terms of extreme storms and floods, heat waves,
rise in sea level etc that disrupts the critical infrastructure of the city and affecting it’s urban transition (IPCC,
2014). Some of the impacts of the variability in climate on urban areas are:
• Urban heat islands that are results of dense built environment and anthropogenic emissions. Drastic
variations in temperature may result into secondary effects of high demand of energy to cool, health related
problems from warm spells and rise in air pollution
• Rise in sea level which affects the coastal cities and low lying areas adversely. Erosion and flooding of
coastal urban areas from the rising sea level coupled with extreme storms threaten the entire coastal
ecosystem along with the population and the built forms. Presence of extensive petro chemical or energy
industries, port facilities makes the coastal city more vulnerable.
• Water scarcity in urban areas which has multiple adverse effects, like drought and shortage for human
consumption, agriculture and industry. Consumption of contaminated water in view of scarcity may lead to
health related problems. Urban areas dependent on hydropower generated source of electricity would also
suffer.
• Hydrological hazards including inland flooding, storm surges, heavy rainfall leads to destruction of built
form, livelihood, critical infrastructures and contamination of water followed by water borne disease etc.
• Adverse health impacts from various causes like extreme temperature, increasing air pollution, scarcity of
potable water and food.
• The economy of urban area is also affected by climate change induced events. The direct damage of critical
infrastructure , properties and assets, business opportunities leading to economic loss for rebuilding them
and indirectly by damaging the inputs for economic growth like resources, raw materials etc
II. Methodology
The area selected for the study consists of the urban region of Kolkata Metropolitan Area (KMA). KMA is
amongst the top five megacities in India along with Mumbai, Delhi, Chennai and Bangalore and it is the largest
urban agglomeration in eastern India. The study area specifically consists of three Municipal Corporations
(including Kolkata Municipal Corporation), thirty eight Municipalities (Kolkata Metropolitan Development
Authority, 2011). According to 2001 Census KMA has a population of 14.77 million and highest average
residential density of 8000 per square kilometres (Kolkata Metropolitan Development Authority, 2011).
Amongst the top 10 port cities that are vulnerable to flooding due to influence of climate change, Kolkata and
Mumbai are two Indian cities identified in a study by World Bank (Guerrero & Stein, N. Roberto Zagha John
Henry, 2011).Kolkata Metropolitan Area in this context is selected as a study area due to the two aspects:
(i) Considering the hydro-geological factors that influence climate changes like cyclones, sea-level rise, and
storm surges, Kolkata is observed to be one of the most vulnerable flood prone coastal cities.
(ii) Socio-economic condition of Kolkata that is shaped by its physical–environmental setting forms an
interesting trend of metropolitan structure.
The methodological approach is segmented under following heads
1 The influence of urban density on climate change and whether Brownfield Redevelopment can be a
mitigation measure is explored through a literature study as follows:
• Urban density and climate change
• Impact of climate change on critical infrastructure disruption
• Brownfield development as a mitigation measure for climate change
2 The factors influencing scope of Brownfield development at a metropolis level and
3 Influence of the infrastructure amongst the factors influencing the Brownfield development on the same
scale.
www.theinternationaljournal.org> RJSSM : Volume: 09, Number: 10, February 2020 Page 27
Figure 1: Levels of Green House Gas emissions in Kolkata, one of the major contributors of urban heat
island (compiled from data Emissions Dataset for Global Atmospheric Research (EDGAR) (2009)
The study area encompasses the urban area of KMA and includes following municipalities and municipal
corporations. The municipalities and municipal corporations are the urban areas that spread over six districts of
North 24 Parganas, South 24 Parganas, Kolkata, Howrah, Hugli and Nadia. The results for the municipalities are
agglomerated under subheads of the districts to which they belong for the ease of interpretation.
North 24
Parganas
Index
no:
South 24
Parganas
Index
no:
Baranagar 31 Baruipur 34
Barasat 26 Budge Budge 36
Barrackpore 14 Maheshtala 35
Bhatpara 8 Pujali 37
Dum Dum 30 Rajpur-Sonarpur 33
Garulia 10 Howrah
Halisahar 5 howrah B
Kamarhati 22 uluberia 38
Kanchrapara 4 bally 32
Khardah 18 Hugli
Madhyangram 25 Baidyabati 12
Naihati 7 Bhadreshwar 9
New Barrackpore 24 Bansberia 1
North Dumdum 23 Champdani 11
Panihati 20 Hugli-Chinsurah 6
Rajarhat-gopalpur 27 Konnagar 19
South Dum Dum 29 Rishra 36
Titagargh 16 Serampur 34
Bidhanagar 28 Uttarpara-Kotrang 21
Nadia Chandannagore C
Gayeshpur 3 KMC A
Kalyani 2
Figure 2 : Study Area (includes 38 municipalities and 3 municipal corporation of Kolkata Metropolitan Area)
III. LITERATURE REVIEW
0.00E+00
5.00E+05
1.00E+06
1.50E+06
2.00E+06
2.50E+06
3.00E+06
3.50E+06
4.00E+06
4.50E+06
5.00E+06
19
91
19
92
19
93
19
94
19
95
19
96
19
97
19
98
19
99
20
00
20
01
20
02
20
03
20
04
20
05
20
06
20
07
20
08
20
09
20
10
20
11
20
12
GH
G E
mis
sio
n (
ton
)
Green House Gas emission in Kolkata
CH4
CO2 exclu short cycle
CO2 short cycle
NO2
www.theinternationaljournal.org> RJSSM : Volume: 09, Number: 10, February 2020 Page 28
Urban density and climate change
The urban areas with high population density produce a large amount of greenhouse gases and anthropogenic
heat. They are also high consumers of energy and influences the micro climate of the region.(IPCC, 2014) In
most of the scenarios the urban growth is accommodated either growing outward through horizontal expansion
and urban sprawl or growing upward in form of increasing the vertical density. Both the form of spatial growth
requires support of critical infrastructure which is vulnerable to this climate change induced damages.
The influence of density of urban areas and their critical infrastructure in adapting with climate change
variations forms the premises of this study. It is observed that the large contiguous urban areas that are well
serviced by infrastructure and belong to the economically prosperous section tend to produce larger amount of
green house gases per capita compared to its densely populated counterparts that have low level of services
(Marcotullio, Albrecht, & Sarzynski, 2011)
The capacity of an urban area to adapt with the climate change induced risk depends on various dimensions as
observed in several studies. The factors influencing the adaptive capacity of a city belongs to two broad
categories, the bio-physical that includes the physical form of the city and its critical infrastructure, the second is
the socio-economic status of the population(Carter et al., 2015). Another study shows that the adaptive capacity
of the city or a community depends on its economic wealth, technology, information and skills, infrastructure,
institutions, and equity (Pouliotte, Smit, & Westerhoff, 2001). Analysis exploring the risks of a city from climate
change claims it to be the function of social, economic and political processes. It can be elaborated into factors
like economic stability, demographic structure, institutional stability, strength of public infrastructure and global
connectivity(Walsh et al., 2011) . The quality of housing and infrastructure, level of preparedness among city’s
population and key emergency services are also to be factors influence risk of a city to climate change
(Satterthwaite, Huq, Pelling, Reid, & Lankao, 2007). In a report by World Bank, the ‘ adaptation deficit’
against climate change variability is function of substantial poverty, inadequate infrastructure, environmental
degradation(The Global Commission on the Economy and Climate, 2014). So we can observe that there is
repetitive mention of the urban form and the critical infrastructure of the city playing a major role in deciding the
adaptive capacity of a city against climate change.
Impact of climate change on critical infrastructure disruption
The growth of the urban areas coincides with it its demand for critical infrastructure both in terms of scale of
requirement and dependency on other infrastructure. The density of these urban areas is higher, so it has a
concentrated demand for infrastructure and its disruption would affect more people. Sudden disruptive climatic
hazard and gradual climate change that depletes the critical infrastructure both can affect the functioning of the
society in term of its safety, security health, economic and social well being. Exposure to the climate change
stressor and how the critical infrastructure is vulnerable to it decides the probability of it’s degradation
(Wilbanks, T., & Fernandez, 2013).
Two of the major factors which makes disruption or failure of critical infrastructure severe is (i) they are often
interconnected so the failure of one may have a cascading effect , or even an escalating effect on others (Rinaldi,
Peerenboom, & Kelly, 2001). (ii) Disruption of a critical infrastructure can also lead to a trans-boundary crisis
that has impact beyond geographical, functional and time boundaries (Boin, 2009). In table number 1 the risks
faced by urban infrastructure sectors and the probable adaptation and mitigation measures are discussed.
Urban infrastructure
and service sector
Risk Mitigation or Adaptation measures
Energy Heat waves or cold waves can increase
power demand. Hydropower dependent areas
will be affected due to variations in
precipitation.
• Management to minimise the peak
demand.
• Updating network and plants to be more
resilient to extreme climate change events
like flood, rising heat waves, storms etc.
• Using more renewable sources as input
fuel
Water and Waste water Both quality and quantity of consumable
water will be affected due to occurrence of
drought and flood. Urban areas have
increased share of impervious surfaces and
with irregular precipitation drainage system
will be over burdened
Water conservation strategies like using low
flow toilet fixture, leak detection and
repairing, reuse of water for other purposes
like irrigation and gardening, rainwater
harvesting etc.
Transportation The impact on the transportation network
depends on its location (underground,
elevated, railways with overhead electrical
wires). Extreme weather conditions can
• Encouraging use of public transportation.
• Adaptation of energy efficient vehicles
and modes.
www.theinternationaljournal.org> RJSSM : Volume: 09, Number: 10, February 2020 Page 29
deform the transportation system.
Transportation services can also be affected
as a secondary effect from damage in power
and telecommunication.
Public Health Poor air quality, extreme temperatures and
vector borne health risks increase due to
climate change and it’s effects are amplified
due to high population density of urban
areas. Increased flooding and droughts are
followed by water borne health risks.
Adaptation strategies to be integrated with
other services and sectors e.g.: planting
trees, green roofs, and pervious surfaces to
reduce the effects of urban heat island.
Health surveillance , improved water supply
and energy service will also have positive
impact on public health
Urban Landuse Planning High pressure to develop lands that are
vulnerable to climate change extreme events.
Area along the coast, river basin, slide prone
areas along mountains should have restrictive
development.
Adjustment in existing building codes and
introduction of new regulations. Measures
to reduce urban sprawl by increasing the
density of building, encouraging public
transport, restricting landuse laws
Table 1: The risks faced by Urban infrastructure and service sectors due to climate change and the possible
adaptation measures (source :Wilbanks, T., & Fernandez 2013)
To sum up the points for climate change implications in context of critical infrastructures in urban areas:
• Due to high demand from growing population and rise in average standard of living, there will be a rise in
demand of critical infrastructure would be built on areas that are exposed extreme weathers and climate
change. So attempts to decrease the footprint of the critical infrastructure and making it less physical
structure intensive is important.
• The revitalization of the aging infrastructure which is stressed due to rising demand has to accommodate the
technological change and the financial investment that is needed.
Therefore with limited resources of land and finance building a compact urban form rather than a Greenfield
development is more suitable
Brownfield development as a mitigation measure for climate change
Most of the core areas of Indian cities have comparatively low floor space index or floor area ratio (1.2 -2.0)
compared to other Asian cities (5.0-15.0). This constitutes the pool of underutilized lands along with parcels of
lands in form of dysfunctional factories, large government or institutional areas etc (Idfc Foundation, 2016). So
planned densification supported by public spaces and transport infrastructure will help to promote reduction in
Greenhouse gas emissions.
For the rapidly growing Indian cities facing various challenges building critical infrastructure to support the
growth is the only way forward. But it should also be noted that reducing the carbon footprint of the
infrastructure is crucial which can be achieved by a compact city form.
It is evident that for an overall sustainable urban area many other factors are to be considered simultaneously but
densification certainly have some advantages: (i) Cities with high density consume less energy per capita when
compared to suburban areas that are low in density. Less density requires people to travel more and further
making them more dependent on vehicle.(ii) Dense areas also produce less waste and cooling or heating of
smaller spaces require lesser energy.(iii )The coordination of supply chain and infrastructure service is better for
densely populated city.(Rogers Richard & Power Anne, 2017). A city that has a compact physical form, well
connected with public transits and functions with less damage to the environment is more equipped to mitigate
the effects of climate change.
Densification should be integrated with an overall spatial planning strategy without which it may have a
contrasting effect on the adaptive capacity of the city against climate change (Cizler, 2014). To achieve it , the
underutilized land resources and buildings are to be recycled, density of development increased and sprawling
over suburbs should be discouraged(Rogers Richard & Power Anne, 2000). On one end it aims to reduce the
transformation of the green spaces, agricultural land, forest areas and peripheral lands to urban built forms,
reducing sprawl which works as an adaptation measure against climate change. On the other if not planned
properly and integrated with resilient infrastructure it might encourage over congestion leading to air pollution
and traffic, gentrification and deterioration of civil services.
Redevelopment of Brownfield can be practiced as a measure to integrate climate change mitigation concerns
with the spatial planning and policies (Fernandes, de Sousa, Brito, Neves, & Vicente, 2018). Renewal of
Brownfield encourages intense use of existing urbanised areas and an overall compact form. Benefits of renewal
of Brownfield development can be realised at multiple fronts that includes economic, environmental and
community development (Chicago Metropolitan Agency & May, 2009).
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Before we look into the benefits of a Brownfield redevelopment, it is important to point out that there is lack of
an agreed definition for the term ‘Brownfield ’,. Different countries, organisations and people offer a wide range
of interpretations and probable perspective, so it is important to reach an agreeable definition. The term evolved
from being associated with damaged and probably contaminated land due to previous industrial activities which
cannot be reused without proper treatment .It is mainly referred to land that is previously developed land
irrespective of its condition, opposite of what Greenfield land signifies (Alker et al. 2000, Adams, De Sousa, and
Tiesdell 2009)
It may be noted that the definitions of Brownfield vary according to the approach by different countries.
Countries with low population densities consider Brownfield land as contaminated land, particularly land
affected by previous industrial activities. For countries having high population density, like developing
countries, definitions of Brownfield includes a wider range. Initially it only included previously developed but
now it also includes vacant land and currently used land that has potential for further development(Tang & Paul
Nathanail, 2012) .
To sum it up the definition for Brownfield is as follows:
“Brownfield site is any land or premises which has previously been used or developed and is not currently fully
in use. It may be partially occupied or utilised or may also be vacant, derelict or contaminated. Therefore a
Brownfield site is not available for immediate use without intervention.”(Alker et al., 2000)
In the context of this study the following advantages of encouraging Brownfield development can be noted in
terms of adaptation towards climate change:
• It has existing infrastructure so building new networks of infrastructure which is energy intensive both in
construction and maintenance is less.
• It utilises the existing land resources fully and discourages urban sprawl
• A compact urban form is encouraged, which reduces the commuting distance and usage of vehicles
minimising energy consumption and greenhouse gas emissions.
• Brownfield development reduces the pressure on Greenfield development. For every hectare of
Brownfield redevelopment , it is estimated that up to 4.5 hectares of Greenfield development in an
outlying area can be saved (Heid, 2004).
The major causes of climate changes like emission of greenhouse gases, consumption of energy, depletion of
natural ecosystem can be minimised by adopting Brownfield redevelopment as a solution. Some of the measures
taken in Brownfield redevelopment and its probable impact on climate change are as follows:
Impacts of Brownfield development Anticipated influence on climate change
Land recycling Compact urban development, preservation of natural environment
Reuse of buildings Compact urban development, preservation of natural environment
Creation of green areas Preservation of the natural ecosystem
Application of renewable energy sources Reduction of emissions, reduction of energy consumption and conservation
of resources
Inclusion in public transport network Reduction of emissions through reduction in car use
Mixed-use development Reduction of emissions through reduction in car use
Table 2: Impacts of Brownfield redevelopment and its anticipated impacts on climate change (Cizler, 2014)
.
IV. FINDINGS
The starting point is to define the aim which as mentioned earlier is to find the factors influencing the scope of
Brownfield development at a metropolis level with a focus on influence on infrastructure
The basic approach for the analysis was as follows:
• Factor Identification: Identifying variables to assess the scope of Brownfield development at metropolitan
level and grouping them into categories or factors through literature studies.
• Reclassifying data within a layer using Fuzzy Membership tool: Mapping the required data and reclassify
them on a GIS interface for the year of 1991, 2001 and 2011. The process of reclassification is also known as
fuzzification using a ‘Fuzzy Membership’ function.
• Combining the layers using Fuzzy Overlay Tool: Overlay the reclassified data using ‘Fuzzy Logic Overlay’
function to find the performance of the area under each category and overall scope of Brownfield development
for the region
Factors influencing scope of Brownfield development at a metropolis level
There are two major approaches found in the literature as the process of identifying Brownfield Sites: (a) a pre
assessment in prioritization of Brownfield sites comparing it with indicators that are derived from defined
characteristics of Brownfield, (b) a post assessment that prioritize Brownfield sites based on its probable impact
www.theinternationaljournal.org> RJSSM : Volume: 09, Number: 10, February 2020 Page 31
on being redeveloped. The range of indicators varies widely depending on the aim of assessment, giving more
importance to health and environmental based indicators or based purely on economic returns. Nevertheless the
most recurring set of 35 indicators can be grouped into following categories of demographic characteristics,
urban structure, probable contamination level, availability of utilities and infrastructure and last but not the least
the probable economic returns from redevelopment of the Brownfield site.
The table number 3 summarizes the final 15 indicators that occur most frequently in the existing literature
eliminating duplicates, redundant or unavailable ones and they are grouped under broad heads of:
socioeconomic, environmental, social infrastructure, and urban environment/infrastructure.
• Socio-economic factors play a major role in prioritizing the sites for Brownfield redevelopment as the idea is
to maximise the economic and social benefits through it. Higher population density and unemployment rate
therefore means a large population might benefit though the Brownfield redevelopment (Chrysochoou et al.,
2012).
• Brownfield are often synonymous with contaminated or probably contaminated lands that may be an
environmental burden. The second factor therefore considers the maximum environmental benefit that can be
achieved through Brownfield redevelopment. The areas with higher permeability and probable contaminated
sites are preferred.
• The next two factors that include urban environment/infrastructure and social are essential for prioritizing
Brownfield areas. It is assumed that a Brownfield is already served by some basic level of physical and
social infrastructure. The urban primary core and areas served by sewer network, water supply, educational
and healthcare facilities are prioritized.
Variables Measurement Category
Population density Population per sq mile Socio-economic
Unemployment rate
Percentage of unemployed people amongst the
labour force Socio-economic
Soil type
Permeable-sand, Semi- permeable- silt,
impermeable- clay Environmental
Proximity to water source or aquifers Aquifer depth Environmental
Presence of flood prone area Availability Environmental
Presence of wetlands Availability Environmental
Threat due to former landuse/
contamination and existence of
environmental burden in official databases Number of probable contaminated sites Environmental
Parks, Open spaces & Recreation Percentage of area Environmental
Access to schools number of existing schools Social
Access to healthcare Number of (Hospitals+ dispensaries+ health
centres+ family planning centres + nursing
homes+ other institutions Social
Access to recreational-cultural-banking
facilities Number of existing facilities Social
Location in urban setting
Classification according to sequence of
development and density
Urban environment/
infrastructure
Transport accessibility
Share of area within walking distance of arterial
road
Urban environment/
infrastructure
Intersection Density Intersection/ sq mile of arterial roads within
urban footprint
Urban environment/
infrastructure
Utility Service Area Access to water supply and waste water
Urban environment/
infrastructure
Table 3: List of variables selected
Reclassifying data within a layer using Fuzzy Membership tool The next step was to get an idea how the Kolkata Metropolitan Area performs when assessed through the factors
of socio-economic, environmental, infrastructure, social. The data was obtained for the year 1991, 2001 and
2011 through various sources and mapped on a GIS interface.
It is followed by an overlay analysis that allowed combining the data to give a single output. The values that
were mapped consisted of various data levels of measure like nominal, ordinal interval and ratio. The nominal or
ordinal scale data (eg: location in urban setting is defined as primary urban core, secondary urban core, suburban
fringe and dispersed development zones) cannot be defined into specific categories but one is preferred over the
other and can guide in decision-making process (MesgariI, Pirmoradi, & Fallahi, 2008). So here fuzzy overlay
function is used which works on fuzzy membership logic in determining the level of confidence that the area is a
preferred for Brownfield redevelopment. The data is therefore reclassified and fuzzy membership function is
used. The values returned ranges from 0 to 1 where 0 indicating low possibility of membership and 1 indicating
www.theinternationaljournal.org> RJSSM : Volume: 09, Number: 10, February 2020 Page 32
higher possibility of membership. The variables are first overlaid to assess the performance of the study area in
the four categories identified. Finally the four factors were integrated using fuzzy overlay function to get a
conclusive result.
Combining the layers using Fuzzy Overlay Tool
In the final overlay the layers are combined using the Fuzzy logic and it explores the possibility of an area to
belong in different categories which are unlike Boolean or Index logic where the boundaries are well defined
(Raines, Sawatzky, & Bonham-Carter, 2010). The first level of overlay is done by combining variables to get
results under the four major categories. The results are grouped against the four categories of socio-economic,
environmental, infrastructure, social versus the six districts namely North 24 Parganas, South 24 Parganas,
Kolkata, Howrah, Hugli and Nadia.
Table number 4 shows the results through soft scoring with low, medium and high scores denoted by +, ++, +++
signs. The four layers are finally combined to get the scenarios for the scope of Brownfield redevelopment for
the years 1991, 2001 and 2011. For the final combination the type of Fuzzy overlay used was ‘AND’ to identify
locations that meet all the categories of suitability. The purpose was that all the categories namely
socioeconomic, environmental, and social and infrastructure find equal importance in the area identifications.
V. CONCLUSION For better interpretation the results from the fuzzy overlay was tabulated into categories along with districts to
which the municipalities belong. Following observation can be made from the table number 4:
• North 24 Parganas has high scores under environmental category and medium scores for socioeconomic, social
and infrastructure.
• South 24 Parganas: Follows a similar trend like North 24 Parganas with medium scores in all factors except
environment where it scores high.
• Kolkata : It is a high scorer in all the categories except in socioeconomic. In the 2011 it scores low in the
socioeconomic category which may be low unemployment rate.
• Howrah scores medium in all the categories except the environmental. It may be attributed to location of a
number of sites that are probably contaminated.
• Hugli also shows similar trend as Howrah with high scores in environmental category and a more or less
medium scores in all other.
• Nadia score high on infrastructure and environmental categories. It has a medium score in socioeconomic and
social categories.
Districts Year Socio-Economic Environmental Social Urban Environment/ Infrastructure
North 24
Parganas
1991 ++ +++ ++ +++
2001 ++ +++ ++ ++
2011 ++ ++ + +++
South 24
Parganas
1991 ++ +++ ++ +
2001 + +++ ++ ++
2011 ++ +++ + ++
Kolkata 1991 +++ +++ +++ +++
2001 +++ +++ +++ ++
2011 + +++ +++ +++
Howrah 1991 ++ +++ ++ ++
2001 +++ +++ ++ ++
2011 + +++ ++ ++
Hugli
1991 ++
+++ ++ ++
2001 ++ +++ ++ ++
2011 ++ +++ ++ +++
Nadia 1991 ++
+++ ++ +++
2001 +++ +++ ++ ++
2011 + +++ ++ +++
Table 4 : Summary of the scores from overlay function
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Figure 3: The Urban environment/ infrastructure score (for the 1991. 2001 and 2911) If we focus on the urban environment and infrastructure category we observe that South 24 Parganas have
improved and North 24 Parganas have declined slightly for the year 2001 but improved later . Kolkata and Nadia
have more or less has been well serviced with some basic level of infrastructure. Howrah has a stagnant medium
level of infrastructure and has not been able to improve much. Hugli has improved its infrastructure over the
decade of 2001 to 2011. We observe that the Kolkata municipal corporation and its adjoin areas dominates the
region in terms of infrastructure sector showing a primacy behaviour. So scope of Brownfield development
would be more if only infrastructure sector was considered but a combined effect of all the factors show
different results.
Figure 4 : The final Brownfield Redevelopment score (for the 1991. 2001 and 2911)
After overlaying all the four categories we observe that for the year 1991 Howrah and Kolkata had maximum
conditions fulfilled for a Brownfield Redevelopment. In the year 2001,
Kolkata definitely dominated the region with its high levels of infrastructure, population density and social
factors. It also had the highest number of contaminated sites hence it has maximum scope for a Brownfield
Redevelopment. By the 2011 the whole region presented more or less equal scope for the Brownfield
redevelopment.
scale 1:400000
1991 2001 2011
scale 1:400000
1991 2001 2011
www.theinternationaljournal.org> RJSSM : Volume: 09, Number: 10, February 2020 Page 34
References [1] Adams, D., De Sousa, C., & Tiesdell, S. (2009). Brownfield Development: A Comparison of North American and British Approaches.
Urban Studies, 47(1), 75–104. https://doi.org/10.1177/0042098009346868
[2] Alker, S., Joy, V., Roberts, P., & Smith, N. (2000). The Definition of Brownfield. Journal of Environmental Planning and
Management, 43(1), 49–69. https://doi.org/10.1080/09640560010766
[3] Boin, A. (2009). The new world of crises and crisis management: Implications for policymaking and research. Review of Policy
Research, 26(4), 367–377. https://doi.org/10.1111/j.1541-1338.2009.00389.x
[4] Carter, J. G., Cavan, G., Connelly, A., Guy, S., Handley, J., & Kazmierczak, A. (2015). Climate change and the city: Building
capacity for urban adaptation. Progress in Planning, 95(July), 1–66. https://doi.org/10.1016/j.progress.2013.08.001
[5] Chicago Metropolitan Agency, & May, P. (2009). Brownfields Redevelopment Strategy, (May 2008).
[6] Chrysochoou, M., Brown, K., Dahal, G., Granda-Carvajal, C., Segerson, K., Garrick, N., & Bagtzoglou, A. (2012). A GIS and
indexing scheme to screen brownfields for area-wide redevelopment planning. Landscape and Urban Planning, 105(3), 187–198.
https://doi.org/10.1016/j.landurbplan.2011.12.010
[7] Cizler, J. (2014). Brownfield redevelopment as a measure for climate changes mitigation. Journal of the Geographical Institute Jovan
Cvijic, SASAZbornik Radova Geografskog Instituta Jovan Cvijic, SANU, 63(4), 57–73. https://doi.org/10.2298/ijgi1304057c
[8] Fernandes, A., de Sousa, J. F., Brito, S. S., Neves, B., & Vicente, T. (2018). Preparing Waterfront Brownfields Redevelopment for
Climate Change: the Water City Project, Almada (Portugal). Journal of Coastal Research, 85, 1531–1535.
https://doi.org/10.2112/si85-307.1
[9] Guerrero, I. M., & Stein, N. Roberto Zagha John Henry, S. M. (2011). India - Vulnerability of Kolkata metropolitan area to increased
precipitation in a changing climate. https://doi.org/Report No. 53282-IN
[10] Hamin, E. M., & Gurran, N. (2009). Urban form and climate change: Balancing adaptation and mitigation in the U.S. and Australia.
Habitat International, 33(3), 238–245. https://doi.org/10.1016/j.habitatint.2008.10.005
[11] Heid, J. (2004). Greenfield Development Without Sprawl�: The Role of Planned Communities.
[12] Idfc Foundation. (2016). India Infrastructure Report 2012. India Infrastructure Report 2012. https://doi.org/10.4324/9781315538914
[13] IPCC. (2014). Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Retrieved from
http://www.tandfonline.com/doi/abs/10.4155/cmt.13.80.
[14] Kolkata Metropolitan Development Authority. (2011). Introducing KMA. Retrieved from http://kmdaonline.org/home/download
[15] Marcotullio, P., Albrecht, J., & Sarzynski, A. (2011). The geography of greenhouse gas emissions from within urban areas of India: a
preliminary assessment. Journal of Resources, Energy and Development, 8(1), 11–35. https://doi.org/10.3233/RED-120079
[16] MesgariI, M. S., Pirmoradi, A., & Fallahi, G. R. (2008). Implementation of Overlay Function Based on Fuzzy Logic in Spatial
Decision Support System. World Applied Sciences, 3(1), 60–65.
[17] Pouliotte, J., Smit, B., & Westerhoff, L. (2009). Adaptation and development: Livelihoods and climate change in Subarnabad,
Bangladesh. Climate and Development, 1(1), 31–46. https://doi.org/10.3763/cdev.2009.0001
[18] Raines, G. L., Sawatzky, D. L., & Bonham-Carter, G. F. (2010). New fuzzy logic tools in ArcGIS 10. ArcUser, Spring, 8–13.
Retrieved from www.esri.com
[19] Rinaldi, S. M., Peerenboom, J. P., & Kelly, T. K. (2001). Identifying, understanding, and analyzing critical infrastructure
interdependencies. IEEE Control Systems Magazine, 21(6), 11–25. https://doi.org/10.1109/37.969131
[20] Rogers Richard, & Power Anne. (2000). The compact sustainable city - Designing Buildings Wiki. Retrieved July 12, 2017, from
https://www.designingbuildings.co.uk/wiki/The_compact_sustainable_city#Brownfield_vs_greenfield
[21] Rogers Richard, & Power Anne. (2017). The compact sustainable city - Designing Buildings Wiki. Retrieved July 12, 2017, from
https://www.designingbuildings.co.uk/wiki/The_compact_sustainable_city#Brownfield_vs_greenfield
[22] Satterthwaite, D., Huq, S., Pelling, M., Reid, H., & Lankao, P. R. (2007). Human Settlements Discussion Paper Series Adapting to
Climate Change in Urban Areas The possibilities and constraints in low-and middle-income nations. Retrieved from
http://www.rockfound.org/initiatives/climate/climate_change.shtml
[23] Tang, Y. T., & Paul Nathanail, C. (2012). Sticks and Stones: The impact of the definitions of brownfield in policies on socio-
economic sustainability. Sustainability, 4(5), 840–862. https://doi.org/10.3390/su4050840
[24] The Global Commission on the Economy and Climate. (2014). Cities. Better Growth, Better Climate: The New Climate Economy
Report, 2–33.
[25] Walsh, C. L., Dawson, R. J., Hall, J. W., Barr, S. L., Batty, M., Bristow, A. L., … Zanni, A. M. (2011). Assessment of climate change
mitigation and adaptation in cities. Proceedings of the Institution of Civil Engineers - Urban Design and Planning, 164(2), 75–84.
https://doi.org/10.1680/udap.2011.164.2.75
[26] Wilbanks, T., & Fernandez, S. (2013). Climate Change and Infrastructure, Urban Systems, and Vulnerabilities: Technical Report for
the U.S. Department of Energy in Support of the National Climate Assessment.