Retrieving vegetation biophysical parameters and GPP using satellite-driven LUE model in a National Park

The terrestrial biosphere plays an active role in governing the climate system by regulating carbon exchange between the land and the atmosphere. Analysis of vegetation biophysical parameters and gross primary production (GPP) makes it convenient to monitor vegetation's health. A light use efficiency (LUE) model was employed to estimate daily GPP from satellite-driven data and environmental factors. The LUE model is driven by four major variables, namely normalized difference vegetation index (NDVI), photosynthetically active radiation (PAR), air temperature, and moisture for which both satellite-based and ERA5-Land data were applied. In this study, the vegetation health of Dibru Saikhowa National Park (DSNP) in Assam has been analyzed through vegetation biophysical and biochemical parameters (i.e., NDVI, EVI, LAI, and chlorophyll content) using Sentinel-2 data. Leaf area index (LAI) varied between 1 and 5.2, with healthy forests depicted LAI more than 2.5. Daily GPP was estimated for January (winter) and August (monsoon) 2019 for tropical evergreen and deciduous forest types. A comparative analysis of GPP for two seasons has been performed. In January, GPP was found to be 3.6 gC m(-2) day(-1), while in August, GPP was 5 gC m(-2) day(-1). The outcome of this study may be constructive to forest planners to manage the National Park so that net carbon sink may be attained in DSNP.

Automated summary

The study analyzed the vegetation health of Dibru Saikhowa National Park by examining vegetation biophysical parameters and GPP. It was found that an LAI greater than 2.5 indicated healthy forests. Daily GPP was estimated for January and August 2019 for tropical forest types, with higher values in August.