Urban morphology and land surface temperature dataset

This project is linked to a manuscript submited to <b>GIScience &amp; Remote Sensing</b>: Quantifying spatially heterogeneous impacts of urban morphology on urban thermal environment using an interpretable geographically weighted XGBoost model. Landsat 8/9 OLI/TRIS images was used to retrieve Land Surface Temperature and to extract various surface biophysical parameters, including the Normalized Difference Vegetation Index and the Modified Normalized Difference Water Index. Land cover data were applied to calculate a series of landscape pattern indices, quantifying spatial structure and composition features. Building data were utilized to quantify multiple morphological indicators, such as building density, height, and volume, thereby providing a comprehensive characterization of the three-dimensional urban spatial form.

本项目关联一篇投稿至《GIScience & Remote Sensing》（地理信息科学与遥感）期刊的学术论文，题为《基于可解释地理加权XGBoost模型量化城市形态对城市热环境的空间异质性影响》。研究采用陆地卫星（Landsat）8/9号OLI/TRIS影像反演地表温度（Land Surface Temperature, LST），并提取各类地表生物物理参数，包括归一化植被指数（Normalized Difference Vegetation Index, NDVI）与改进归一化水体指数（Modified Normalized Difference Water Index, MNDWI）。通过土地覆被数据计算一系列景观格局指数，以此量化城市空间结构与组成特征。利用建筑数据量化多维度城市形态指标，涵盖建筑密度、建筑高度与建筑体量，从而全面刻画三维城市空间形态。