By using TM imagery as the raw data in this paper, the authors first classified the objects of the study area into three classes, i.e., impervious surface (IS), vegetation, and water based on the algorithm of OTSU, and retrieved land surface temperature (LST) of the study area by using the mono-window algorithm. Then, the study area was separated into 45 pieces by setting a multi-level buffer in a discriminating scheme, which was based on the distance between each pixel and the center of Nanjing, and the work of statistics and analysis was carried out for the mean temperature of all pixels, the mean temperature of IS, the mean temperature of vegetation, and the mean temperature of water in each buffer. Finally, the authors set up the relational models between LST and the area ratio of IS, LST and the area ratio of vegetation, LST and the area ratio of water. The results showed that the land surface temperature decreased obviously with the increasing distance from the city's center. Vegetation and water could reduce the temperature in central city proper, and the cooling effect of water is 2.43 times that of vegetation. The integrated relational model between LST and the area ratio of IS, the area ratio of vegetation and the area ratio of water was performed well.
刘东, 李艳, 孔繁花. 中心城区地表温度空间分布及地物降温效应——以南京市为例[J]. 国土资源遥感, 2013, 25(1): 117-122.
LIU Dong, LI Yan, KONG Fanhua. Spatial distribution of land surface temperature in central city proper and the cooling of objects effect: A case study of Nanjing. REMOTE SENSING FOR LAND & RESOURCES, 2013, 25(1): 117-122.
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