Developing a Decision Support System for Quality of Landscape and Quality of Life in the Sustainable Adriatic City

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

1 Developing a Decision Support System for Quality of Landscape and in the Sustainable Adriatic City Luca Cetara**, Rosalba D Onofrio*, Roberta Cocci Grifoni*, Mariano Pierantozzi, Massimo Sargolini* ** University of Camerino - School of Environmental Sciences; EURAC * University of Camerino - School of Architecture and Design International Conference on Smart and Sustainable Planning for Cities and Regions 2015 EURAC, Bolzano Italy

2 Structure of the presentation 1.Aims of the 2.Re-defining the urban 3.The as 4.Metrics, Policies 5.Survey of QOL urban 6.Methodologies for assessing multi-dimensional QoL in the 7.The QLAND-QLIFE : steps and methods 8.Partial results 9.Summary and

3 urban 3. The as urban the Achieving a high level QoL in the urban Developing novel metrics for measuring policy actions in a urban Identification and selection of a set of QoL indicators under macro-domains Crossing QoL indicators with strategic priorities for the 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

4 urban urban 3. The as urban the Figure 1: Map of the Italian urban areas according to the OECD-EC methodology. Accessed at:

5 urban urban Code City Total population Category (2008) IT011 Venezia 505,626 Metropolitan area IT015 Trieste 242,235 IT506 Ravenna 145,134 Medium-sized urban area Small urban area IT508 Rimini 185,243 Small urban area IT039 Pesaro 111,092 Small urban area the IT017 Ancona 181,298 Small urban area IT019 Pescara 212,211 IT038 Barletta 92, 094 Medium-sized urban area Small urban area IT008 Bari 590,529 Metropolitan area IT037 Lecce 208,811 Medium-sized urban area 3. The as urban

6 urban 3. The as 3. The as 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. urban Ancona qualifies as a OECD-EC small urban area close to the lower threshold for the superior category. the Structural urban characteristics of Ancona have been considered to determine broad dimensions and specific indicators for urban QOL and partitions of the urban transect

7 Quality of Life Re-defining the 2. urban 3. The as urban the 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 (QOL)/Well-Being (WB) Composite dashboards vs. integrated indices for QoL Classical three pillars of sustainability (economic, al, 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)

8 urban indicators for the urban 3. The as urban the Priority Goals for Urban Centre (): a) improving al 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? 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. Categories of urban policies: a) risk reduction and energy-efficiency; b) improving al quality; c) urban regeneration.

9 urban indicators for the urban Main studies surveyed 3. The as urban the 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)

10 urban indicators for the urban 3. The as Domain urban the Subdomains Identity and pleasant Efficient and nice Clean and healthy Landscape Ecology, Uses and form of the green spaces, physical city (N.8) morphology (N. 15) Protected areas (N.3) Landscape perception (N. 6) Biodiversity and natural resources management (N.7) Metabolism and urban comfort (N.15) Form and urban identity Soil degradation and (N. 16) 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, Waste management public transport (N.26): and collection (N.4) Quality of public spaces Safety: (N.3) and services (N.8) # Indicators (175)

11 assessing multi-dimensional QOL in the urban 3. The as urban the 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

12 assessing multi-dimensional QOL in the urban Organisation of planning documents for Ancona 3. The as urban the 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 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.

13 assessing multi-dimensional QOL in the urban 3. The as urban assessing multidimensional QoL in the Urban partitions identify settlement patterns classified on the basis of: a) urban morphology and built / open spaces / street network ratio b) density (built /open 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)

14 assessing multi-dimensional QOL in the urban 3. The as urban assessing multidimensional QoL in the Partitions of the.

15 assessing multi-dimensional QOL in the urban 3. The as urban assessing multidimensional QoL in the Partition of the (1).

16 assessing multi-dimensional QOL in the urban 3. The as urban assessing multidimensional QoL in the Partition of the (2).

Progetto Cometa Verde da Documento Programmatico COMUNE DI ANCONA 1 Riqualificazione Corso Mazzini 2 Verifica di vulnerabilità

17 assessing multi-dimensional QOL in the urban Partition of the and planned projects Progetto "Passeggiata da Mare a Mare" 3. The as urban assessing multidimensional QoL in the. 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

18 assessing multi-dimensional QOL in the urban 3. The as urban assessing multidimensional QoL in the Partition of the (Urban Atlas)

19 assessing multi-dimensional QOL in the urban 3. The as urban the Partition of the (Urban Atlas).

20 assessing multi-dimensional QOL in the Strategic Dimensions and urban QOL targets in the Adriatic City 3. The as Risk reduction and management Soil safety (indicators categories) Policy Domains Safety Environmental quality and landscape improvement Urban Comfort and physical and psychical Environment and health health Strenghtening of urban ecosystem services Urban form and identity assessing multi- Reorganization and redimensional QoL functionalisation of the city Quality of public spaces in the Perception and culture and services Fight to waste Degradation and re-use Energy and network efficiency Urban Metabolism Fruition - accessibility Cross-cutting domains Efficiency Identity and Pleasant Efficient and Nice Clean and Healthy

21 QLAND QLIFE model a) Neural approach and machine learning techniques applied to territorial and urban urban analyses (Virgilio 2012) b) Multi-objective parametric optimization analysis (Pareto) 3. The as 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 s (based on Cocci Grifoni et al. 2013): 1) gathers structural connections in a territorial system 2) autonomously identifies and ranks connections and dynamic relationships urban 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/relationships assessing multi4) allows for the identification of a best connection matrix (BCM) reproducing dimensional QoL in the territorial dynamics observed in a urban and building scenarios the 5) uses Exponential Random Graph Models (ERGM) for validating hypotheses on the specific structure of the network Thus, applied to each partition of the : 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)

22 1. Single-objective optimisation: applying algorithms looking for the min or max of a function, according to the set objective. Some multi-objective optimisations urban can be reduced to single-objective functions by using a priori weights, if objectives are homogenous enough. 3. The as 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.. urban the 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

23 urban 3. The as urban the 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 density 2. building heights 3. buiding compactness 4. road width. Similar outcomes would result also out of simulations run for urban soil safety indicators

24 open issues urban 3. The as urban the Short list of indicators to address policy challenges using QOL targets (safety, & 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 '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).

25 Thank you for your attention

Economic valuation of green urban spaces: a meta-analysis

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