Estimating Air Temperature using Land Surface Temperature products of INSAT-3D satellite

Abstract

Air Surface Temperature (Tair) available from meteorological stations, provides only limited information about spatial patterns over wide areas. The use of remote sensing data can help overcome this problem, particularly in areas with low station density, having the potential to improve the estimation of Tair at both regional and global scales. A study has been carried out to understand the relationship between Land Surface Temperature (LST), available from INSAT 3D, and Tair, available from ground meteorological station. The result shows good correlation for winter season but it keeps reducing as we move towards monsoon probably due to increase in the extreme temperature and data unavailability. We also observed low root mean square error (RMSE) of ~1.5 °C for months of winter season while it increases to ~4.5 °C in June. We conclude that there is a good agreement between LST and air temperature, although the two temperatures have different physical meaning and responses to atmospheric conditions.