Journal
GEOCARTO INTERNATIONAL
Volume 37, Issue 6, Pages 1757-1781Publisher
TAYLOR & FRANCIS LTD
DOI: 10.1080/10106049.2020.1790675
Keywords
ASTER; land surface temperature; surface emissivity; NDVI; TES
Categories
Funding
- Deanship of Scientific Research at King Khalid University [R.G.P2/75/41]
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This research compares four different algorithms for retrieving land surface temperature (LST), and the results show that the emissivity derived NDVI TES method has the highest accuracy. This has important implications for predicting energy budget and climate information.
Land surface temperature is a significant source of energy budget and climate information, contributing to various environmental and biophysical processes. This research includes comparing the LSTs retrieved from the ASTER sensor using the Reference Channel method, the Emissivity Normalization method (NOR), TES method and Retrieving LSE by taking the proportion of vegetation cover coupled with NDVI and integrates it into the TES algorithm. The results of derived LST from the four algorithms compare with MODIS data of 7 control points having thermally homogenous sites. The analysis showed that the four algorithms are suitable for LST retrieval, whereby the proposed emissivity-derived NDVI algorithms exhibited the highest degree of accuracy (RMSE 0.145), and the NOR had the least accuracy (RMSE 0.403). The analysis shows that emissivity derived NDVI TES method more reliant on the upwelling, downwelling and transmittance and will achieve the best results compared to the other three algorithms.
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