Land Surface Temperature Estimation from Satellite Imagery in Imphal-Iril River Catchment, Manipur, India

One of the most essential parameters for any climate model is land surface temperature, which is also regarded as an important indicator for the assessment of global energy balance and hydrologic modeling. The Imphal-Iril River catchment is the present study area where agricultural land (16.5%) and forest (73%) are the most prevalent Land Use Land Cover (LULC) classifications. The main objective of this research is to assess the spatial variation of land surface temperature (LST) across various land use types within the catchment by using satellite-based normalized difference vegetation index (NDVI) and land surface emissivity (LSE). LST was derived using ArcGIS 10.3 from the thermal infrared sensor (TIRS) Band 10 of Landsat 8 imagery for three different periods, namely 22 November 2018, 8 December 2018, and 9 January 2019. The present study used 45 in situ observations for various land uses and the MODIS LST product to validate the computed LST. The results reveal that LST estimated from Landsat 8 has an excellent correlation with in situ LST observation data. The study also observed that a negative relationship exists between NDVI and LST for all periods. The spatial patterns of LST were assessed across three time periods to gain insight into surface temperature fluctuations in the area.