基于POI数据的武汉市夏季热场主导因素多尺度分析

分析不同尺度下土地覆被、人类活动等因素对地表温度影响作用大小,可为城市生态空间布局调整优化提供参考。以兴趣点(Point of Interest, POI)数据表征人类活动强度,利用大气校正法反演2016年夏季武汉市外环线区域地表温度,借助最小二乘法在500、1 000和2 000 m 3个尺度下定量研究地表温度与POI密度、归一化植被指数和归一化水体指数的相关性及作用大小,并分析各变量对地表温度的相对重要性。研究表明:(1)3种尺度下,POI密度均与地表温度呈显著正相关关系且相关系数随尺度增大而增大;归一化植被指数和水体指数与地表温度呈显著负相关关系,归一化植被指数与地表温度相关系数随尺度增大而减小,归一化水体指数与地表温度相关系数随尺度增大而增大;(2)武汉市热场空间是自然生态环境和人类活动共同作用的结果;(3)POI对地表温度的解释作用占较大权重,是热场空间形成的重要因素。POI对于地表温度解释的相对贡献度最大,在研究城市热场影响因素中,POI可用来反映人类活动强度,对遥感信息有较好的补充作用。

Multi-scale Analysis of Main Factors of Summer Thermal Field in Wuhan Based on POI Data

Clarifying the effects and relative importance of surface parameters on Land Surface Temperature (LST) at different scales can provide a reference for the adjustment and optimization of urban ecological space layout. We used Point of Interest (POI) data to characterize the micro-scale human activity intensity and use the atmospheric correction method to invert the LST of the outer ring region of Wuhan in the summer of 2016. Using Method of Ordinary Least Squares, we quantitatively analyzed the relationships between LST to POI, Normalized Difference Vegetation Index (NDVI) and Modified Normalized Difference Water Index (MNDWI) at 500 m, 1 000 m and 2 000 m scales, then further distinguished the relative importance of variables to LST. The results show that: (1) POI is significantly positively correlated with LST and the correlation coefficient increases with the increase of scale at three scales. NDVI and MNDWI are significantly negatively correlated with LST. The correlation coefficient between NDVI and LST decreases with the increase of scale. The correlation coefficient between MNDWI and LST increases with the increase of scale. (2)The thermal field in Wuhan is the result of the joint action of natural ecological environment and human activities; (3) The interpretation of LST by POI occupies a large relative weight and is the most important factor in the formation of thermal field. The results show that POI has the greatest relative contribution to the interpretation of LST, in the study of urban thermal field influencing factors, POI can be used to reflect the intensity of human activity and has a good complement to remote sensing information.