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Exploring the Effects of Roadside Vegetation on the Urban Thermal Environment Using Street View Images

Roadsides are important urban public spaces where residents are in direct contact with the thermal environment. Understanding the effects of different vegetation types on the roadside thermal environment has been an important aspect of recent urban research. Although previous studies have shown that...

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Autores principales: Li, Bin, Xing, Hanfa, Cao, Duanguang, Yang, Guang, Zhang, Huanxue
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8834765/
https://www.ncbi.nlm.nih.gov/pubmed/35162302
http://dx.doi.org/10.3390/ijerph19031272
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author Li, Bin
Xing, Hanfa
Cao, Duanguang
Yang, Guang
Zhang, Huanxue
author_facet Li, Bin
Xing, Hanfa
Cao, Duanguang
Yang, Guang
Zhang, Huanxue
author_sort Li, Bin
collection PubMed
description Roadsides are important urban public spaces where residents are in direct contact with the thermal environment. Understanding the effects of different vegetation types on the roadside thermal environment has been an important aspect of recent urban research. Although previous studies have shown that the thermal environment is related to the type and configuration of vegetation, remote sensing-based technology is not applicable for extracting different vegetation types at the roadside scale. The rapid development and usage of street view data provide a way to solve this problem, as street view data have a unique pedestrian perspective. In this study, we explored the effects of different roadside vegetation types on land surface temperatures (LSTs) using street view images. First, the grasses–shrubs–trees (GST) ratios were extracted from 19,596 street view images using semantic segmentation technology, while LST and normalized difference vegetation index (NDVI) values were extracted from Landsat-8 images using the radiation transfer equation algorithm. Second, the effects of different vegetation types on roadside LSTs were explored based on geographically weighted regression (GWR), and the different performances of the analyses using remotely sensed images and street view images were discussed. The results indicate that GST vegetation has different cooling effects in different spaces, with a fitting value of 0.835 determined using GWR. Among these spaces, the areas with a significant cooling effect provided by grass are mainly located in the core commercial area of Futian District, which is densely populated by people and vehicles; the areas with a significant cooling effect provided by shrubs are mainly located in the industrial park in the south, which has the highest industrial heat emissions; the areas with a significant cooling effect provided by trees are mainly located in the core area of Futian, which is densely populated by roads and buildings. These are also the areas with the most severe heat island effect in Futian. This study expands our understanding of the relationship between roadside vegetation and the urban thermal environment, and has scientific significance for the planning and guiding of urban thermal environment regulation.
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spelling pubmed-88347652022-02-12 Exploring the Effects of Roadside Vegetation on the Urban Thermal Environment Using Street View Images Li, Bin Xing, Hanfa Cao, Duanguang Yang, Guang Zhang, Huanxue Int J Environ Res Public Health Article Roadsides are important urban public spaces where residents are in direct contact with the thermal environment. Understanding the effects of different vegetation types on the roadside thermal environment has been an important aspect of recent urban research. Although previous studies have shown that the thermal environment is related to the type and configuration of vegetation, remote sensing-based technology is not applicable for extracting different vegetation types at the roadside scale. The rapid development and usage of street view data provide a way to solve this problem, as street view data have a unique pedestrian perspective. In this study, we explored the effects of different roadside vegetation types on land surface temperatures (LSTs) using street view images. First, the grasses–shrubs–trees (GST) ratios were extracted from 19,596 street view images using semantic segmentation technology, while LST and normalized difference vegetation index (NDVI) values were extracted from Landsat-8 images using the radiation transfer equation algorithm. Second, the effects of different vegetation types on roadside LSTs were explored based on geographically weighted regression (GWR), and the different performances of the analyses using remotely sensed images and street view images were discussed. The results indicate that GST vegetation has different cooling effects in different spaces, with a fitting value of 0.835 determined using GWR. Among these spaces, the areas with a significant cooling effect provided by grass are mainly located in the core commercial area of Futian District, which is densely populated by people and vehicles; the areas with a significant cooling effect provided by shrubs are mainly located in the industrial park in the south, which has the highest industrial heat emissions; the areas with a significant cooling effect provided by trees are mainly located in the core area of Futian, which is densely populated by roads and buildings. These are also the areas with the most severe heat island effect in Futian. This study expands our understanding of the relationship between roadside vegetation and the urban thermal environment, and has scientific significance for the planning and guiding of urban thermal environment regulation. MDPI 2022-01-24 /pmc/articles/PMC8834765/ /pubmed/35162302 http://dx.doi.org/10.3390/ijerph19031272 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Li, Bin
Xing, Hanfa
Cao, Duanguang
Yang, Guang
Zhang, Huanxue
Exploring the Effects of Roadside Vegetation on the Urban Thermal Environment Using Street View Images
title Exploring the Effects of Roadside Vegetation on the Urban Thermal Environment Using Street View Images
title_full Exploring the Effects of Roadside Vegetation on the Urban Thermal Environment Using Street View Images
title_fullStr Exploring the Effects of Roadside Vegetation on the Urban Thermal Environment Using Street View Images
title_full_unstemmed Exploring the Effects of Roadside Vegetation on the Urban Thermal Environment Using Street View Images
title_short Exploring the Effects of Roadside Vegetation on the Urban Thermal Environment Using Street View Images
title_sort exploring the effects of roadside vegetation on the urban thermal environment using street view images
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8834765/
https://www.ncbi.nlm.nih.gov/pubmed/35162302
http://dx.doi.org/10.3390/ijerph19031272
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