Integrated application of multi-source remote sensing image is one of the best ways to improve the accuracy of land surface temperature (LST) retrieval. The difference between satellite overpass time of MODIS Terra and Landsat is small, so it is easy to get synchronized MODIS and Landsat TM images. The most challenging work of LST retrieval from Landsat TM images is acquisition of atmospheric profile parameters, and MODIS image has several near infrared bands that can be used to estimate atmospheric profile. In order to evaluate the effectiveness of atmospheric parameters estimated from MODIS image being used to LST retrieval algorithm of Landsat TM images, some experimental studies about Qins mono-window algorithm and Jimenez-Munozs generalized single-channel algorithm have been conducted in this paper, and the retrieval LST results of the two algorithm were validated using the observed data from weather stations. Finally, the differences in accuracy of the two algorithms from different land cover types were analyzed. The results show that (1)two LST retrieval algorithms can get high-precision result in support of atmospheric parameters from MODIS images, the average deviation of mono-window algorithm is 0.76K, and the deviation of generalized single-channel algorithm is 1.23k; (2) the differences in accuracy of the two algorithms from different land cover types are obvious, the difference of water area is smallest, the difference of mean is 0.02K, and the difference of vegetation area is largest, the difference of mean is 0.62K, and the LST results of mono-window algorithm are smaller than the LST results of generalized single-channel algorithm.
ZHENG Wenwu, ZENG Yongnian
. Comparative Analysis of Two Land Surface Temperature Retrieval Algorithms Based on Multi-source Remote Sensing Data[J]. Journal of Geo-information Science, 2011
, 13(6)
: 840
-847
.
DOI: 10.3724/SP.J.1047.2011.00840
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