Retrieving and assessing land surface temperature from ASTER data

Land surface temperature (LST) is a key parameter in ecological and farm environment studies. The study area is located in Zhangye of Gansu province, mainly was covered by crops and desert. To retrieve LST from ASTER thermal infrared (TIR), split window algorithm was used. Surface emissivity and atmospheric transmittance was estimated previously. To evaluate the estimated result, the ASTER and MODIS LST production was collected and compared in both visual method and spatial distributions of LST profiles derived from typical transects. The maps showed that the general distribution tendency of ASTER LST was consistent with MODIS LST data and corresponded to the NDVI image in an inverse fashion. To gain an insight into the negative relationship between LST and NDVI, empirical statistics was conducted and the results showed that there was a strong negative relationship between LST and NDVI (R²=0.508). Further, the mean temperature and standard deviation of each land cover types for two standard LST productions and LST estimated in our method were collected to make a comparison. For the three LST data, the sequence of temperature values for land use/land cover (LULC) from high to low was same: sand, desert, impervious, vegetation and water. However, ASTER LST retrieval in our method was lower than the other two LST data. It may be caused by the estimated parameters or the coarse resolution of MODIS. In our study, a relative comparison approach was adopted to verify the result, which proved LST images retrieved from only two ASTER thermal channels using our developed algorithms were reliable and easily realized.