Retrieval of urban land surface component temperature using multi-source remote-sensing data

The components of urban surface cover are diversified, and component temperature has greater physical significance and application values in the studies on urban thermal environment. Although the multi-angle retrieval algorithm of component temperature has been matured gradually, its application in the studies on urban thermal environment is restricted due to the difficulty in acquiring urban-scale multi-angle thermal infrared data. Therefore, based on the existing multi-source multi-band remote sensing data, access to appropriate urban-scale component temperature is an urgent issue to be solved in current studies on urban thermal infrared remote sensing. Then, a retrieval algorithm of urban component temperature by multi-source multi-band remote sensing data on the basis of MODIS and Landsat TM images was proposed with expectations achieved in this work, which was finally validated by the experiment on urban images of Changsha, China. The results show that: 1) Mean temperatures of impervious surface components and vegetation components are the maximum and minimum, respectively, which are in accordance with the distribution laws of actual surface temperature; 2) High-accuracy retrieval results are obtained in vegetation component temperature. Moreover, through a contrast between retrieval results and measured data, it is found that the retrieval temperature of impervious surface component has the maximum deviation from measured temperature and its deviation is greater than 1 °C, while the deviation in vegetation component temperature is relatively low at 0.5 °C.