Changing urban landscape with multistoried high rises, roads and pavements is continuously reducing urban green space. These structures result in high surface temperature variation within cities. To explore the relationship between surface temperature and normalized difference vegetation index (NDVI), this study estimates two models—geographically weighted regression (GWR) and a fixed effect panel data model in relation to the Guwahati Metropolitan Area (GMA), a secondary city in north east India. The results indicate the superiority of GWR regression in presence of spatial dependence. Panel data analysis shows that the densely populated urban areas in the GMA with less than 10 per cent greenery are 1°C warmer than the sub‐urban areas with 50 per cent greenery.

中文翻译：

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城市中的闷热者：印度古瓦哈蒂的城市绿化及其对温度的影响

多层高层建筑，道路和人行道改变着城市景观，不断减少着城市的绿地。这些结构导致城市内部较高的地表温度变化。为了探索地表温度与归一化植被指数（NDVI）之间的关系，本研究估算了两个模型-地理加权回归（GWR）和与古瓦哈提都会区（GMA）有关的固定效应面板数据模型，该市是印度的二级城市印度东北部。结果表明存在空间依赖性时，GWR回归的优越性。面板数据分析显示，GMA中人口稠密，绿化率低于10％的城市地区比郊区绿化率达50％的郊区高1°C。