Urban green infrastructure (UGI) has a key role in improving human and environmental health in cities and contributes to several services related to climate adaptation. Accurate localization and quantification of pervious surfaces and canopy cover are envisaged to implement UGI, address sustainable spatial planning, and include adaptation and mitigation strategies in urban planning practices. This study aims to propose a simple and replicable process to map pervious surfaces and canopy cover and to investigate the reliability and the potential planning uses of UGI maps. The proposed method combines the normalized difference vegetation index (NDVI), extracted from high-resolution airborne imagery (0.20 m), with digital elevation models to map pervious surfaces and canopy cover. The approach is tested in the Municipality of Trento, Italy, and, according to a random sampling validation, has an accuracy exceeding 80%. The paper provides a detailed map of green spaces in the urban areas, describing quantity and distribution, and proposes a synthesis map expressed as a block-level degree of pervious surfaces and canopy cover to drive urban transformations. The proposed approach constitutes a useful tool to geovisualize critical areas and to compare levels of pervious surfaces and canopy cover in the municipal area. Acknowledging the role of green areas in the urban environment, the paper examines the potential applications of the maps in the policy cycle, such as land use management and monitoring, and in climate-related practices, and discusses their integration into the current planning tools to shift towards performative rather than prescriptive planning.

Mapping Pervious Surfaces and Canopy Cover Using High-Resolution Airborne Imagery and Digital Elevation Models to Support Urban Planning / Codemo, Anna; Pianegonda, Angelica; Ciolli, Marco; Favargiotti, Sara; Albatici, Rossano. - In: SUSTAINABILITY. - ISSN 2071-1050. - ELETTRONICO. - 14:10(2022), pp. 614901-614921. [10.3390/su14106149]

Mapping Pervious Surfaces and Canopy Cover Using High-Resolution Airborne Imagery and Digital Elevation Models to Support Urban Planning

Codemo, Anna;Pianegonda, Angelica;Ciolli, Marco;Favargiotti, Sara;Albatici, Rossano
2022

Abstract

Urban green infrastructure (UGI) has a key role in improving human and environmental health in cities and contributes to several services related to climate adaptation. Accurate localization and quantification of pervious surfaces and canopy cover are envisaged to implement UGI, address sustainable spatial planning, and include adaptation and mitigation strategies in urban planning practices. This study aims to propose a simple and replicable process to map pervious surfaces and canopy cover and to investigate the reliability and the potential planning uses of UGI maps. The proposed method combines the normalized difference vegetation index (NDVI), extracted from high-resolution airborne imagery (0.20 m), with digital elevation models to map pervious surfaces and canopy cover. The approach is tested in the Municipality of Trento, Italy, and, according to a random sampling validation, has an accuracy exceeding 80%. The paper provides a detailed map of green spaces in the urban areas, describing quantity and distribution, and proposes a synthesis map expressed as a block-level degree of pervious surfaces and canopy cover to drive urban transformations. The proposed approach constitutes a useful tool to geovisualize critical areas and to compare levels of pervious surfaces and canopy cover in the municipal area. Acknowledging the role of green areas in the urban environment, the paper examines the potential applications of the maps in the policy cycle, such as land use management and monitoring, and in climate-related practices, and discusses their integration into the current planning tools to shift towards performative rather than prescriptive planning.
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Codemo, Anna; Pianegonda, Angelica; Ciolli, Marco; Favargiotti, Sara; Albatici, Rossano
Mapping Pervious Surfaces and Canopy Cover Using High-Resolution Airborne Imagery and Digital Elevation Models to Support Urban Planning / Codemo, Anna; Pianegonda, Angelica; Ciolli, Marco; Favargiotti, Sara; Albatici, Rossano. - In: SUSTAINABILITY. - ISSN 2071-1050. - ELETTRONICO. - 14:10(2022), pp. 614901-614921. [10.3390/su14106149]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11572/344908
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