Ecosystem Services Based Approach for Participatory Spatial Planning and Risk Management in a Multi-Level Governance System

Giaimo, Carolina; Barbieri, C.; Salata, Stefano

doi:10.1007/978-3-319-76944-8_5

Cited by 4 publications

(3 citation statements)

References 8 publications

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“…It is well-known that sat-images are sensitive to seasonal changes in the land uses, but this kind of problem also affects the digitalization process employed for a LULC dataset, which is the crucial input variable of habitat quality. Therefore, the research conducted here took the available information (input data) of HQ modeled during the Life SAM4CP research and compared the standard values with a new modeling output that is based on the utilization of the NDVI as a new proxy of sensitivity [42][43][44]. Both HQ models were produced using the latest version of InVEST (suite of models produced by the Natural Capital Project, Stanford University, Stanford, California v. 3.7.0) sharing the same catchment area of Turin to see how the two outputs differ in each zone of the city.…”

Section: Introductionmentioning

confidence: 99%

The Utilization of Normalized Difference Vegetation Index to Map Habitat Quality in Turin (Italy)

et al. 2020

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The integration of ecosystem service mapping in decision-making is crucial to place effective urban design and sustainable planning solutions. Nonetheless, often ecosystem service maps are the product of different data inputs that influences the final modeling output thus affecting final decisions, especially when a finer and site-specific assessment is required to design practical and effective solutions. In this work, the city of Turin (Northwest Italy) was selected as a test site for an empirical experiment of ecosystem service mapping using the software Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST): two habitat quality models of the city were compared in a Geographic Information System environment, the first using the “traditional” sensitivity employed during the LIFE SAM4CP European research while the second using the natural difference vegetation index to re-assign the sensitivity scores. Results demonstrate that the integration of site-specific information in the habitat quality input model generates a different result, which is capable of differentiating all those dense built-up areas of the dense settlement system that provide ecosystem supporting functions at the city-level. These differences were analyzed to define new green hotspots in the compact city while furnishing a new perspective for sustainable city planning.

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Section: Introductionmentioning

confidence: 99%

The Utilization of Normalized Difference Vegetation Index to Map Habitat Quality in Turin (Italy)

et al. 2020

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“…Interestingly, despite Turin is being characterized by a dense urban fabric with elevated imperviousness values, not all the urban areas have high pluvial flooding vulnerability. Excluding the hilly area and the northern ridge where the Po River meets the Stura River, characterized by high habitat quality due to their zoning (Giaimo et al, 2018), it was surprising that some of the central areas have low vulnerability. It appears that the zones of "Vanchiglia," "Vanchiglietta," "Crocetta," and "Borgo San Secondo" are characterized by a more significant "porosity" and consistency of urban greenery confirmed through the Normalized Difference Vegetation Index.…”

Section: Discussionmentioning

confidence: 99%

Mainstreaming climate resilience: A GIS-based methodology to cope with cloudbursts in Turin, Italy

Brunetta

Caldarice

Faravelli

2022

Environment and Planning B: Urban Analytics and City Science

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Cities play an increasingly significant role in the challenges posed by climate change, mainly due to their role in economic and demographic drivers. It is generally agreed that the intensification of climate change effects, such as extreme weather events, requires strengthening in the mechanisms of adaptation and the endogenous self-organization of urban systems. An operative way to adapt is by mainstreaming climate resilience, i.e., the iterative process of integrating climate change considerations into policymaking, budgeting, implementation, and monitoring processes at national and subnational levels. This paper falls under this heading, and it aims at building an innovative methodology to experiment with data-driven approaches to support the resilient transition of the city of Turin in Italy. The process aims to create territorial knowledge of specific weather phenomenon, that cloudburst events are, by filling the gap of existing hazard information with original vulnerability datasets. The proposed approach will create a hydraulic vulnerability map by identifying cloudburst vulnerable areas with a GIS-based spatial overlay. The paper will employ an array of datasets combined with original modelling techniques elaborated with the help of the open-source InVEST (Integrated Valuation of Ecosystem Services and Trade-offs) software program. The results allow us to understand what would happen if the urban water network failed to discharge during a phenomenon of intense rain and, consequently, which city areas should undergo adaptation and transformation to reduce their flooding vulnerability.

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“…The catchment area includes 21 municipalities that border the city of Turin (Figure 1), defined as the "first ring" due to their strong interaction with the main city, namely, Baldissero Torinese, Beinasco, Borgaro Torinese, Caselle Torinese, Castiglione Torinese, Collegno, Druento, Gassino Torinese, Grugliasco, Leinì, Mappano, Moncalieri, Nichelino, Orbassano, Pecetto Torinese, Pianezza, Pino Torinese, San Mauro Torinese, San Raffaele Cimena, Settimo Torinese, Torino, Venaria Reale, and Volpiano. Despite the high administrative fragmentation, the city of Turin consists physically of a unique semi-dense continuous built-up system that from the core area shapes the surrounding zones while comprising a heterogeneous land use [37]. The average daily temperature varies from below 1.4 • C in January to 23.6 • C recorded in July, the climate is warm and temperate with significant rainfall throughout the year (about 864 mm of annual precipitation), and the driest month is January, with 38 mm, while May is the wettest month, with an average of 108 mm (https://en.climate-data.org/ accessed on 16 September 2020).…”

Section: The Turin Metropolitan Areamentioning

confidence: 99%

Performance-Based Planning to Reduce Flooding Vulnerability Insights from the Case of Turin (North-West Italy)

et al. 2021

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Climate change impacts urban areas with greater frequency and exposes continental cities located on floodplains to extreme cloudbursts events. This scenario requires developing specific flooding vulnerability mitigation strategies that improve local knowledge of flood-prone areas at the urban scale and supersede the traditional hazard approach based on the classification of riverine buffers. Moreover, decision-makers need to adopt performance-based strategies for contrasting climate changes and increasing the resilience of the system. This research develops the recent Flooding Risk Mitigation model of InVEST (Integrated Evaluation of Ecosystem Services and Trade-off), where cloudburst vulnerability results from the soil’s hydrological conductivity. It is based on the assumption that during cloudburst events, all saturated soils have the potential for flooding, regardless of the distance to rivers or channels, causing damage and, in the worst cases, victims. The model’s output gives the run-off retention index evaluated in the catchment area of Turin (Italy) and its neighborhoods. We evaluated the outcome to gain specific insight into potential land use adaptation strategies. The index is the first experimental biophysical assessment developed in this area, and it could prove useful in the revision process of the general town plan underway.

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Ecosystem Services Based Approach for Participatory Spatial Planning and Risk Management in a Multi-Level Governance System

Cited by 4 publications

References 8 publications

The Utilization of Normalized Difference Vegetation Index to Map Habitat Quality in Turin (Italy)

The Utilization of Normalized Difference Vegetation Index to Map Habitat Quality in Turin (Italy)

Mainstreaming climate resilience: A GIS-based methodology to cope with cloudbursts in Turin, Italy

Performance-Based Planning to Reduce Flooding Vulnerability Insights from the Case of Turin (North-West Italy)

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