城市热岛斑块遥感识别及空间扩张路径研究——以北京市为例

研究利用MODIS地表温度数据产品，引入概率阈值算法提升城市热岛斑块空间识别精度。在此基础上，构建城市热岛扩张指数将城市热岛斑块时空变化过程分解为飞地型、边缘型、填充型扩张模式和缩减型模式。基于土地利用变化过程，开展城市热岛斑块空间扩张模式的路径分析，准确识别城市热岛斑块空间扩张路径的来源和归趋。研究表明：2020年北京市夏季昼夜城市热岛斑块总面积分别为3932 km²和2 266 km²，占北京市总面积比例23.96%和13.81%。2005―2020年夏季昼夜城市热岛斑块面积比例分别增加43.40%和24.44%。增长型城市热岛斑块面积大于缩减型城市热岛斑块面积。边缘型扩张模式是增长型城市热岛斑块最主要的模式。耕地、城市建设用地、农村居民点是增长型城市热岛斑块主要的空间扩张路径。研究结果为揭示城市热环境形成过程和精细化管理提供理论依据和数据支撑。

Identifying Urban Heat Island Patches and Spatial Expansion Path Based on Remote Sensing Technology: A Case of Beijing City

With the MODIS surface temperature data products, the probabilistic threshold algorithm is introduced to improve the spatial recognition accuracy of urban heat island patches. On this basis, the urban heat island expansion index is constructed to decompose the spatio-temporal change process of urban heat island patches into leapfrogging, edge-expanding, infilling expansion model and reduced model. Based on the land use change process, the path analysis of the spatial expansion pattern of urban heat island plaque is carried out, and the source and trend of the spatial expansion path of urban heat island plaque are accurately identified. The results show that the total area of urban heat island patches in Beijing in summer day and night in 2020 was 3932 km² and 2266 km², accounting for 23.96% and 13.81% of the total area of Beijing. From the summer of 2005 to 2020, the proportion of urban heat island patches area had a 43.40% and 24.44% growth in the daytime and nighttime, respectively. The area of new heat urban island patches is larger than that of reduced patches. The edge-expanding model is the most important model for the new urban heat island patches. Cropland, urban land, and rural settlement area are the main spatial expansion paths of new urban heat island patches. The research results provide theoretical basis and data support for revealing the formation process and refined management of urban thermal environment.