Mapping and modeling mangrove biophysical and biochemical parameters using Sentinel-2A satellite data in Bhitarkanika National Park, Odisha

Abstract

Mangroves are Earth's most active and diversified saline wetlands, which play an essential role in protecting coastal communities from storm surge, cyclonic winds, tsunami, and tidal waves. Space-borne satellite data provide vital information for monitoring mangrove and retrieving health-related parameters. The objective of this study is to map and model biophysical and biochemical parameters of mangrove forests over the Bhitarkanika reserve forest located on the eastern coast of Odisha. The present study has employed Sentinel–2A sensor's red-edge bands to derive both the aforementioned parameters. Furthermore, the near-proximal sensor (NPS) data were integrated with satellite data for mapping leaf chlorophyll and nitrogen contents with the help of an empirical model. The key findings indicate that EVI (Enhanced Vegetation Index) and measured leaf chlorophyll were significantly and positively correlated (R2 = 0.78). EVI showed a stronger relationship with foliage pigments, such as leaf chlorophyll and nitrogen. Leaf area index (LAI) of mangrove ranged between 1 and 4, with healthy dense mangrove depicted LAI more than 2.5. Leaf chlorophyll content for dense mangrove forests showed between 40 and 90 μg/cm2 as estimated from satellite-based (i.e. NAOC index) and empirical model. However, the NAOC (Normalized Area Over reflectance Curve) index has relatively overestimated the chlorophyll. A similar pattern was also obtained for leaf nitrogen. Nevertheless, integrating both satellite and handheld NPS instruments has provided a robust and dynamic way to monitor mangrove forests' health conditions. Satellite-derived biophysical and biochemical parameters offer vital information on mangrove, which could be crucial towards conservation, plantation, and mangrove management.