ArticleInternational journal of environmental research and public health2022
Exploring the Effects of Roadside Vegetation on the Urban Thermal Environment Using Street View Images.
Article in International journal of environmental research and public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed, 20 citations in OpenAlex.
- The First Seasonal Green View Index Mapping Dataset across Chinese cities powered by deep learning.Scientific data · 2025Article
- Exploring the influence of urban green space and urban morphology on urban heat Islands using street view and satellite imagery.Scientific reports · 2025Article
- Mapping facade materials utilizing zero-shot segmentation for applications in urban microclimate research.Scientific reports · 2025Article
- Urban Heat Island Mitigation: GIS-Based Analysis for a Tropical City Singapore.International journal of environmental research and public health · 2022Article
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Authors and funding
5 authors at 2 institutions in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
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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