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Remote sensing techniques have been used effectively for measuring theoverall loss of terrestrial ecosystem production and biodiversity due to theforest fire. The current research focuses on assessing the impact of forestfire severity on terrestrial ecosystem productivity using different burnindices in Uttarakhand, India. Satellite-based land surface temperature (LST)was calculated for pre-fire (2014) and fire (2016) year using MODerateResolution Imaging Spectroradiometer (MODIS) to identify the burn area hotspotsacross all eco-regions in Uttarakhand. In this study, spatial and temporalchanges of different vegetation and burn area indices i.e Normalized Burn Ratio(NBR), Burnt Area Index (BAI), Normalized Multiband Drought Index (NMDI), SoilAdjusted Vegetation Index (SAVI), Global Environmental Monitoring Index (GEMI),Enhanced Vegetation Index (EVI), Normalized Difference Vegetation Index(NDVI)were estimated for both pre-fire and fire years. Additionally, two LightUse Efficiency (LUE) models i.e Carnegie- Ames-Stanford-Approach (CASA) andVegetation Photosynthesis Model (VPM) were selected to quantify the terrestrialNet Primary Productivity (NPP) in pre-fire and fire years across all biomes ofthe study area.The present approach appears to be promising and has a potentialin quantifying the loss of ecosystem productivity due to forest fires. Adetailed field observation data is required for further training, and testingof remotely sensed fire maps for future research.

Effects of forest fire severity on terrestrial carbon emission and ecosystem production in the Himalayan region, India