Li Bin, Xing Hanfa, Cao Duanguang, Yang Guang, Zhang Huanxue
College of Geography and Environment, Shandong Normal University, Jinan 250300, China.
Beidou Research Institute, Faculty of Engineering, South China Normal University, Foshan 528000, China.
Int J Environ Res Public Health. 2022 Jan 24;19(3):1272. doi: 10.3390/ijerph19031272.
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.
路边是重要的城市公共空间，居民在其中直接接触热环境。了解不同植被类型对路边热环境的影响一直是近期城市研究的一个重要方面。尽管先前的研究表明热环境与植被的类型和配置有关，但基于遥感的技术不适用于在路边尺度上提取不同的植被类型。街景数据的快速发展和使用提供了解决这一问题的途径，因为街景数据具有独特的行人视角。在本研究中，我们使用街景图像探索了不同路边植被类型对地表温度（LST）的影响。首先，利用语义分割技术从19596张街景图像中提取草-灌-树（GST）比例，同时利用辐射传输方程算法从Landsat-8图像中提取LST和归一化植被指数（NDVI）值。其次，基于地理加权回归（GWR）探索不同植被类型对路边LST的影响，并讨论使用遥感图像和街景图像进行分析的不同表现。结果表明，GST植被在不同空间具有不同的降温效果，通过GWR确定的拟合值为0.835。在这些空间中，草地具有显著降温效果的区域主要位于福田区核心商业区，这里人车密集；灌木具有显著降温效果的区域主要位于南部的工业园区，这里工业热排放最高；树木具有显著降温效果的区域主要位于福田核心区，这里道路和建筑密集。这些也是福田区热岛效应最严重的区域。本研究拓展了我们对路边植被与城市热环境关系的理解，对城市热环境调控的规划和指导具有科学意义。
