北京市地表温度的季节变化及其驱动因素空间异质性分析

Seasonal variation of land surface temperature and thespatial heterogeneity of its driving factors in Beijing

探究城市地表温度(LST)的驱动机制,对于缓解城市热岛效应、构建健康舒适的城市人居环境具有重要意义。本研究利用2020—2021年4期的Landsat遥感影像反演北京市LST,探讨了城市热岛效应的季节变化,并采用地理探测器分析地表覆盖、地形、社会经济和气象4种驱动因素对LST的解释程度。进一步采用地理加权回归(GWR)模型分析LST驱动因素的空间分异性,结果表明:(1)北京市的城市热岛效应随季节变化明显,夏、秋2个季节热岛区集中分布于城区,春、冬2个季节热岛区分布较为分散;(2)LST的驱动因素存在季节变化,春季LST的主要驱动因素由高到低排序为归一化植被指数(NDVI)、改进的归一化差异水体指数(MNDWI)、数字高程模型(DEM),夏季LST的主要驱动因素由高到低排序为NDVI、DEM、MNDWI,秋季LST的主要驱动因素由高到低排序为DEM、夜间灯光、气温,冬季LST的主要驱动因素由高到低排序为气温、夜间灯光、MNDWI;(3)夏季LST驱动因素的空间异质性显示,NDVI、MNDWI和不透水面比例与LST之间的关系空间变异较小,道路密度、夜间灯光、DEM、风速、湿度和气温与LST之间的关系空间变异较大。

Exploring the driving mechanism of urban Land Surface Temperature(LST)is of great significance to alleviating the Urban Heat Island(UHI)effect and building a healthy and comfortable urban living environment.Four Landsat remote sensing images representing the four seasons in 2020 and 2021 were used in the paper to invert the LST of Beijing,then the seasonal changes of the UHI effect were discussed.Then geographical detector model was used to analyze the interpretation degree of LST by four types of driving factors including land cover,topography,social economy,and meteorology.Furthermore,the Geographically Weighted Regression(GWR)model was used to analyze the spatial heterogeneity of LST’s driving factors.The results showed that:(1)the UHI effect in Beijing varied obviously with seasons.The heat island areas were concentrated in urban areas in summer and autumn,and most of the heat island areas were scattered in the whole study area in spring and winter.(2)The driving factors for LST varied with seasons.The main driving factors of LST in spring were ranked from high to low as normalized difference vegetation index(NDVI),modified normalized difference water index(MNDWI),digital elevation model(DEM);the main driving factors of LST in summer were ranked from high to low as NDVI,DEM,MNDWI;the main driving factors of LST in autumn were ranked from high to low as DEM,nighttime light,air temperature;the main driving factors of LST in winter were ranked from high to low as air temperature,nighttime light,MNDWI.(3)Took exploring the spatial heterogeneity of the driving factors for LST in summer as an example,the results showed that the relationships between NDVI,MNDWI,the proportion of impervious surface and LST had little spatial variation,the relationships between road density,nighttime light intensity,DEM,wind speed,humidity,air temperature and LST had great spatial variation.