ASSESSMENT OF LAND SURFACE TEMPERATURE FROM SATELLITE DATA FOR DIFFERENT LAND USE AND LAND COVER

Assessing of land surface temperature (LST) helps to study the interactions and connections that are established within ecosystems. Retrieved of LST can be made based on terrestrial measurements or using satellite images. In this paper was evaluated LST for different land use and land cover (LULC) using a Landsat 5 Thematic Mapper (TM) satellite image in the thermal infrared band. The study area was classified in seven classes LULC using supervised classification method. The algorithms used were maximum likelihood, Mahalanobis distance and minimum distance. Overall accuracies were 92.38% for maximum likelihood, 85.23% for Mahalanobis distance and 69.33% for the minimum distance. Based on the classified surfaces of LULC by algorithms used, were achieved binary image which served as masks in LST retrieved. The results show that forest has the lowest temperature due to evapotranspiration and transpiration processes and the barren land has the highest temperature due to lack of vegetation and direct exposure to the sun. The temperatures determined for each category LULC and each algorithm are slightly different (1-3 degrees C).