Developing a Decision Support System for Quality of Landscape … › en › research › technologies › renewableenergy... · 2016-02-08 · Structure of the presentation 1.Aims

Developing a Decision Support System for Quality of Landscape and Quality of Life in the Sustainable Adriatic CityLuca Cetara**, Rosalba D’Onofrio*, Roberta Cocci Grifoni*, Mariano Pierantozzi, Massimo Sargolini*

** University of Camerino - School of Environmental Sciences; EURAC research* University of Camerino - School of Architecture and Design

International Conference on Smart and Sustainable Planning for Cities and Regions 2015

EURAC research, Bolzano – Italy

Structure of the presentation 1.Aims of the research

2.Re-defining the urban environment

3.The Adriatic city as an ideal-type

4.Metrics, Policies and Indicators for Quality of Life (QOL) in the urban environment

5.Survey of QOL indicators for a urban environment

6.Methodologies for assessing multi-dimensional QoL in the Adriatic city

7.The QLAND-QLIFE model in the Adriatic city: steps and methods

8.Partial results

9.Summary and Open issues

1. Aims of the research ● Achieving a high level QoL in the urban

environment

● Developing novel metrics for measuring policy actions in a urban environment

● Identification and selection of a set of QoL indicators under macro-domains

● Crossing QoL indicators with strategic priorities for the Adriatic city

● “Urban partition” analysis based on standard “settlement patterns”

● Dynamic parametric optimisation approach based on scenario planning

● Potential cost-effectiveness / BCA approach for selecting policy actions

1. Aims of the research

2. Re-defining the urban environment

3. The Adriatic city as an ideal-type

4. Metrics, Policies and Indicators for Quality of Life (QOL) in the urban environment

5. Survey of QOL indicators for a urban environment

6. Methodologies for assessing multi-dimensional QoL in the Adriatic city

7. The QLAND-QLIFE model in the Adriatic city

8. Partial results

9. Summary and Open issues

2. Re-defining the urban environment 1. Aims of the

research







8. Partial results


Figure 1: Map of the Italian urban areas according to the OECD-EC methodology. Accessed at:

http://www.oecd.org/gov/regional-policy/Italy.pdf

http://www.oecd.org/gov/regional-policy/Italy.pdf

2. Re-defining the urban environment 1. Aims of the

research







8. Partial results


Code City Total population (2008)

Category

IT011 Venezia 505 ,626 Metropolitan area

IT015 Trieste 242 ,235 Medium-sized urban area

IT506 Ravenna 145 ,134 Small urban area

IT508 Rimini 185 ,243 Small urban area

IT039 Pesaro 111 ,092 Small urban area

IT017 Ancona 181 ,298 Small urban area

IT019 Pescara 212 ,211 Medium-sized urban area

IT038 Barletta 92, 094 Small urban area

IT008 Bari 590 ,529 Metropolitan area

IT037 Lecce 208 ,811 Medium-sized urban area

3. The Adriatic city as an ideal-type 1. Aims of the

research







8. Partial results


Ancona (IT)

101,417 inhabitants in 2015 (Comune di Ancona 2015), 181,298 inhabitants in 2008 (OECD-EC)

City (urban core) is shorter than the scope of the the formal administrative boundaries of the Province of Ancona, according to the law.

Ancona qualifies as a OECD-EC “small urban area” close to the lower threshold for the superior category.

Structural urban characteristics of Ancona have been considered to determine broad dimensions and specific indicators for urban QOL and “partitions of the urban transect”









8. Partial results


● Urban studies often follow a vertical approach (by field): ecology, energy, energy-efficiency, transportation, technology, economics, urban planning

● Literature focused on definition, interpretation and possible metrics for Quality of Life (QOL)/Well-Being (WB)

● Composite dashboards vs. integrated indices for QoL ● “Classical” three pillars of sustainability (economic,

environmental, social) vs. adding other dimensions (e.g. resource efficiency, cost-effectiveness, cultural aspects and landscape)

● Recent appraisals of experimental metrics for QOL (incl. subjective WB) by primary national statistical institutes and governments (UK ONS-Measuring National Well-Being Programme and Italy-Istat-BES)

● Step-by-step Institutionalization of theoretical frameworks (Bruni et al. 2008, Bruni 2015)

5. Survey of QOL indicators for the urban environment








8. Partial results


● Categories of urban policies: a) risk reduction and energy-efficiency; b) improving environmental quality; c) urban regeneration.

● Priority Goals for Urban Centre (Adriatic city): a) improving environmental quality and the landscape; b) re-organising and redefining of urban functions; c) achieving or increasing energy and network efficiency.

● Which indicators already exist, for the mentioned urban policies, that have addressed the priority goals identified for the Adriatic city?

● Survey on existing sets of indicators for urban QoL: 1) role in the achievement of the final target, 2) own specific targets, 3) own unit of measurement, 4) possible numerical expression, 5) presence and use in literature.









8. Partial results


Main studies surveyed

● “Plan Especial de Indicadores de Sostenibilidad Ambiental de la Actividad Urbanística de Sevilla” (2008)

● “Indicatori di Vivibilità urbana, Qualità urbana e Percezione della Salute”. Ricerca PRIN (2004)

● “CAT MED-Change Mediterranean Metropolis Around Time” (2012)

● Progetto Lagrange - Fondazione ISI-CRT e CSI-Piemonte: “Sistema di monitoraggio web delle trasformazioni urbane complesse attraverso indicatori” and “Indice sintetico della qualità urbana e territoriale (IQUT)” (2014)

● SUSTAIN-Interreg 4C “Misurare la Sostenibilità costiera” (2012)

● “ECI - European Common Indicators (Indicatori Comuni Europei)” - ARPA Emilia Romagna (2003)

● “EfficienCities” - Siemens- Cittaitalia (2012) ● “URGE - Sviluppo degli Spazi Verdi urbani per migliorare la

qualità della vita nelle città e nelle regioni urbane” (2004)

DomainIdentity and

pleasantEfficient and

niceClean and

healthy

Sub-domains

Landscape Ecology, green spaces, physical morphology (N. 15)

Uses and form of the city (N.8)

Protected areas (N.3)

Landscape perception (N. 6)

Metabolism and urban comfort (N.15)

Biodiversity and natural resources management (N.7)

Form and urban identity (N. 16)

Soil degradation and consumption (N.4)

Air quality, water quality and management, energy consumption (N.10) :

Meeting spaces (N.4) Social and economic aspects (N. 33)

Natural and Human hazards (N.7)

Socio-cultural aspects (N.6)

Fruition, accessibility, public transport (N.26):

Waste management and collection (N.4)

Quality of public spaces and services (N.8)

Safety: (N.3)

# Indicators (175) 47 94 34








8. Partial results










8. Partial results


Ancona Metropolitan area’s Strategic Action Plan (AMMA 2014): 39 municipalities in the Ancona-Jesi area● Analysis of formal AMMA 2014 statements ● Identification of four strategic dimensions (SD) ● Definition of SD sub-categories (“policy domains”) ● Link to pertinent targets of urban QOL in the Adriatic city

6. Methodologies for assessing multi-dimensional QOL in the Adriatic city








8. Partial results


Organisation of planning documents for Ancona● Strategic directions and actions to be implemented by means

of “metropolitan projects” [Strategic Metropolitan Plan (SMP) and Urban Agenda (UA) of Ancona].

● Metropolitan projects gather projects aligned with the Strategic Directions and Actions (SMP).

● SMP listed projects based on the strategic guidelines and scenarios for urban development (Comune di Ancona 2014).

Urban planning research methodology 1.Locations for SMP-UA projects' implementation across the city

classified in “urban partitions of the transect of the city” (UPTC) 2.Integration of planned SMP-UA projects and interventions

within UPTC 3.Definition and development of “ideal urban development

scenarios” (IUDS)4.Application of and test against sustainability indicators (SI)

(organised within the categories: “Identity and pleasant”,”Efficient and nice”, “Clean and healthy”) on IUDS for each UPTC .









8. Partial results



Urban partitions identify “settlement patterns”classified on the basis of: a) urban morphology and built environment / open spaces / street network ratio b) density (built environment/open environment ratio, according to EC-GMES Urban Atlas)c) building height (according to the regional technical database, Regione Marche)

Identification and geo-localisation of 6 partitions (UPTCs) in the urban metropolitan area of Ancona-Jesi (on a 500 x 500 m network) on the basis of recurring morphological features suitable to be exported and applied to other sites and cities on the Adriatic coast and outside, with adjustments (e.g. ongoing experiment in France)








8. Partial results


Partitions of the Adriatic city .









8. Partial results


Partition of the Adriatic city (1) .









8. Partial results


Partition of the Adriatic city (2) .









8. Partial results


Partition of the Adriatic city and planned projects .


Progetto "Passeggiata da Mare a Mare"

Progetto Cometa Verde da Documento

Programmatico COMUNE DI ANCONA

1 Riqualificazione Corso Mazzini

2 Verifica di vulnerabilità sismica della scuola materna

Garibaldi in via Torrioni

3 Valorizzazione del Mercaro delle Erbe

4 Sostituzione corpi illuminanti nelle

scuole

5 Interventi di efficientamento energetico degli

impianti di pubblica illuminazione








8. Partial results


Partition of the Adriatic city (Urban Atlas)









8. Partial results


Partition of the Adriatic city (Urban Atlas) .









8. Partial results


Strategic Dimensions and Policy Domains

QOL targets in the Adriatic City

(indicators categories)

Cross-cutting research domains

Risk reduction and management

● Soil safety Safety

● Identity and Pleasant

● Efficient and Nice

● Clean and Healthy

Environmental quality and landscape improvement

● Urban Comfort and physical and psychical health

● Strenghtening of ecosystem services

● Urban form and identity

Environment and health

Reorganization and re-functionalisation of the city

● Quality of public spaces and services

● Fight to waste● Degradation and re-use

Perception and culture

Energy and network efficiency ● Urban Metabolism ● Fruition - accessibility

Efficiency









8. Partial results


7. The QLAND-QLIFE model in the Adriatic city QLAND – QLIFE model a) Neural approach and machine learning techniques applied to territorial and urban analyses (Virgilio 2012) b) Multi-objective parametric optimization analysis (Pareto)

QLAND-QLIFE based on Auto-Associative Neural Networks (AANN) / Kohonen maps (Kohonen 1982, 2001):1) learning phase 2) recall phase (use of self-responding algorythms, network training, modeling network adjustments, dynamic resetting of targets in the response phase)

QLAND-QLIFE in urban environments (based on Cocci Grifoni et al. 2013): 1) gathers structural connections in a territorial system 2) autonomously identifies and ranks connections and dynamic relationships within a collection of data corresponding to “urban requirements” 3) trains the network allowing for a comparative evaluation of different results obtained on the basis of alternative solutions impacting connections/relationships4) allows for the identification of a “best connection matrix” (BCM) reproducing the territorial dynamics observed in a urban environment and building scenarios5) uses Exponential Random Graph Models (ERGM) for validating hypotheses on the specific structure of the network

Thus, applied to each partition of the Adriatic city:● a scenario is developed independently by QLAND-QLIFE ● based on prevailing territorial trends and transformations (indicators, expert

opinion) ● taking as a reference the envisaged territorial projects and interventions

(AMMA 2014 and UA Ancona 2015)








8. Partial results


7. The QLAND-QLIFE model in the Adriatic city 1. Single-objective optimisation: applying algorithms looking for the min or max of a function, according to the set objective. Some multi-objective optimisations can be reduced to single-objective functions by using “a priori” weights, if objectives are homogenous enough.

2. Multi-objective optimisation can keep the objectives separate within the optimisation process. The algorithm applied identifies solutions on the trade-off curve/Pareto frontier, where improving one objective means worsening at least one of the other objectives.

.

Figure: scatter plots related to PMV and PPD for thermal comfort generated in the optimization process (modeFRONTIER). Such graphs associate pairs of objectives that the optimization process aims to minimize. Each point on the graph represents a solution analysed








8. Partial results


8. Partial results “Status quo” and ongoing application

● QLAND-QLIFE Parametric Optimization for a sample city partition

● Indicators within “urban comfort” sub-category (A1.2 Endowment of green public space per capita; B2.2 Vertical surfaces with South orientation; B2.6 Green areas to the ground)

● Sensitivity analysis performed

Preliminary Results ● “Pareto-preferred” combinations of energy consumption and

thermal comfort indices● Threshold of external temperature higher than 29°C● Insensitiveness of the combinations to changes in:

1. urban texture density2. building heights3. buiding compactness 4. road width.

● Similar outcomes would result also out of simulations run for “urban soil safety” indicators








8. Partial results


9. Summary and open issues ● Short list of indicators to address policy challenges using

QOL targets (safety, environment & health, perception & culture, efficiency)

● Test of parametric optimization method for multiple targets (out of indicators on energy consumption and thermal comfort) for sample PUTC

● Planning strategy intensifying institutional and community commitment to keep external temperature within the threshold (29°C) to ensure use of urban planning measures as a leverage for QOL vs. infrastructural actions

● Assessment of efficacy and efficiency of projects (AMMA 2014) for Ancona and 39 municipalities, within partitions, against the Pareto-optimization of QOL targets

● Standardised Adriatic city's partitions suitable for transfer from test-site to other urban settlements (Adriatic coast and beyond) also in line with OECD-EC method

● Room for a cost-benefit analysis (CBA) method aimed at financial comparison of alternative interventions impacting the constitutive variables of urban partitions, with similar efficiency or desirability in terms of QOL variation, and ranking the preferred options (add: economic viability).

Thank you for your attention

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Developing a Decision Support System for Quality of Landscape … › en › research › technologies › renewableenergy... · 2016-02-08 · Structure of the presentation 1.Aims