Tracking green space along streets of world cities
Street green space (SGS) - the presence of vegetation along streets of cities—is a key piece of urban infrastructure. SGS provides a broad range of functions, such as mitigating the urban heat island effect, reducing the impact of extreme precipitation events, and supporting human and animal well-be...
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| Format: | Article |
| Language: | English |
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IOP Publishing
2025-01-01
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| Series: | Environmental Research: Infrastructure and Sustainability |
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| Online Access: | https://doi.org/10.1088/2634-4505/add9c4 |
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| author | Giacomo Falchetta Ahmed T Hammad |
| author_facet | Giacomo Falchetta Ahmed T Hammad |
| author_sort | Giacomo Falchetta |
| collection | DOAJ |
| description | Street green space (SGS) - the presence of vegetation along streets of cities—is a key piece of urban infrastructure. SGS provides a broad range of functions, such as mitigating the urban heat island effect, reducing the impact of extreme precipitation events, and supporting human and animal well-being. Here we introduce an approach to estimate SGS based on the statistical modeling of a street-based indicator of canopy coverage (the green view index, GVI) with multispectral satellite observations and ancillary spatially granular data. Based on our trained and cross-validated non-parametric model, we conduct spatial sampling and prediction in 190 large cities distributed across twenty regions and estimate local to continental GVI trends between 2016–2023. Jointly considering such global pool of cities, we find evidence of a trend of GVI decrease of 0.3%–0.5% per year ( $p \lt 0.01)$ . Yet, both the direction and magnitude of trends show high heterogeneity across and within regions and cities, which we explore, along with stark inequalities in SGS availability within each city. Our analysis provides an updated estimate of the GVI as a measure of SGS across a global pool of cities and an open-source, validated approach to assess its future changes and support the design of policies for sustainable cities. |
| format | Article |
| id | doaj-art-6f8975711cff47d5a77ec1b5624db301 |
| institution | OA Journals |
| issn | 2634-4505 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IOP Publishing |
| record_format | Article |
| series | Environmental Research: Infrastructure and Sustainability |
| spelling | doaj-art-6f8975711cff47d5a77ec1b5624db3012025-08-20T02:29:07ZengIOP PublishingEnvironmental Research: Infrastructure and Sustainability2634-45052025-01-015202501110.1088/2634-4505/add9c4Tracking green space along streets of world citiesGiacomo Falchetta0https://orcid.org/0000-0003-2607-2195Ahmed T Hammad1https://orcid.org/0000-0003-3327-2435International Institute for Applied Systems Analysis , Laxenburg, Austria; Centro Euro-Mediterraneo sui Cambiamenti Climatici—RFF-CMCC European Institute for Economics and the Environment , Venice, ItalyDecatab PTE LTD , Singapore, SingaporeStreet green space (SGS) - the presence of vegetation along streets of cities—is a key piece of urban infrastructure. SGS provides a broad range of functions, such as mitigating the urban heat island effect, reducing the impact of extreme precipitation events, and supporting human and animal well-being. Here we introduce an approach to estimate SGS based on the statistical modeling of a street-based indicator of canopy coverage (the green view index, GVI) with multispectral satellite observations and ancillary spatially granular data. Based on our trained and cross-validated non-parametric model, we conduct spatial sampling and prediction in 190 large cities distributed across twenty regions and estimate local to continental GVI trends between 2016–2023. Jointly considering such global pool of cities, we find evidence of a trend of GVI decrease of 0.3%–0.5% per year ( $p \lt 0.01)$ . Yet, both the direction and magnitude of trends show high heterogeneity across and within regions and cities, which we explore, along with stark inequalities in SGS availability within each city. Our analysis provides an updated estimate of the GVI as a measure of SGS across a global pool of cities and an open-source, validated approach to assess its future changes and support the design of policies for sustainable cities.https://doi.org/10.1088/2634-4505/add9c4street green spacegreen view indexsustainable citiesenvironmental justiceremote sensingmachine learning |
| spellingShingle | Giacomo Falchetta Ahmed T Hammad Tracking green space along streets of world cities Environmental Research: Infrastructure and Sustainability street green space green view index sustainable cities environmental justice remote sensing machine learning |
| title | Tracking green space along streets of world cities |
| title_full | Tracking green space along streets of world cities |
| title_fullStr | Tracking green space along streets of world cities |
| title_full_unstemmed | Tracking green space along streets of world cities |
| title_short | Tracking green space along streets of world cities |
| title_sort | tracking green space along streets of world cities |
| topic | street green space green view index sustainable cities environmental justice remote sensing machine learning |
| url | https://doi.org/10.1088/2634-4505/add9c4 |
| work_keys_str_mv | AT giacomofalchetta trackinggreenspacealongstreetsofworldcities AT ahmedthammad trackinggreenspacealongstreetsofworldcities |