Abstract
A thorough understanding of the biophysical and biochemical parameters is essential for monitoring mangrove vegetation and identifying environmental and anthropogenic stress. Therefore, in this study, the Leaf Area Index (LAI), which is one of the most important biophysical parameters, were estimated in the Indian Sundarbans using remote sensing and field observations. This study primarily focuses on remote sensing-based LAI assessment using a high-resolution AVIRIS-NG dataset using indices such as the Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI). To minimize background influence, mangroves from non-mangroves vegetation were separated based on tree height estimation from Sentinel-1 Synthetic Aperture Radar (SAR) data. The tree height in the study area ranges from ~ 1–9 m while the range of LAI values was found to be 0.18 to 4.87. The AVIRIS-NG derived EVI showed maximum correlation (R2 = 0.88) with in-situ measured LAI. As there is no repetitive coverage of AVRIS-NG data, a new site-specific solution was also developed for future monitoring using freely available datasets like LANDSAT and Sentinel-2. The results generated in this study will be helpful for monitoring the health of the mangroves and adapting a robust approach for restoration efforts in the future.