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Land surface temperature (LST) from satellite data is a challenging task due to the atmospheric absorption and diversification
of earth surface emissivity. The analysis show that land surface temperature influenced by water content or vegetation
condition. The combination of HDF Explorer and ArcGIS software was useful for automatically processing the pixel latitude,
longitude and BT information from the ASTER HDF and Landsat imagery files. Forest areas with more moisture and water
body have shown smaller temperature than settlements. The urban area refers to the phenomenon of higher atmospheric and
surface temperatures occurring in urban areas than in the surrounding vegetation areas. A lookup table of effective temperature
anomalies is constructed based on the brightness temperature (BT) to resolve the inconsistencies between infrared and BT
variation. Here ASTER and Landsat data show similar behaviour for all land cover classes temperature. The results can be
referred to similar areas of the world for LST retrieval or land surface process research, in particular under extreme bad
weather conditions. So mitigation of the high temperature effects via the configuration of green spaces and sustainable designs
of urban environments have become an issue of increasing concern under changing climate.
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