Biomass estimation of mumbai mangroves using optical and microwave satellite remote sensing

Abstract

In a changing climate condition, the ability to effectively quantify biomass becomes increasingly important in the context of climate change mitigation and adaptation strategies. This study is an attempt to estimate biomass of Mumbai mangroves and Bhitarkanika mangroves using Optical remote sensing and microwave remote sensing. For this study the ground data along with ORNL DAAC biomass data is used to form a model to compare the performance of both remote sensing platforms in estimating the biomass. In order to find these selected parameters were derived for Sentinel-1 and Sentinel-2 data. A total of 14 parameters were derived from them. For these parameters the relation with biomass was analyzed using linear regression, multiple linear regression, and stepwise regression. The analysis was done separately for the Sentinel-1 and Sentinel-2 parameters to compare their performance. From the linear regression, Normalised Difference Vegetation Index (NDVI) parameter derived from Sentinel-2 and Polarimetric Radar Vegetation Index (PRVI) parameter from Sentinel-1 showed relatively better relationship with biomass when compared to other parameters chosen. The Multiple linear regression indicates that the Sentinel-2 parameters are explaining the biomass variance better than the Sentinel-1 parameters. And the result implies that the Sentinel-1 parameters show poor relationship to explain variance in biomass of mangroves. The biomass map for both regions was generated based on the R2 value of stepwise regression. A comparative analysis was conducted for the Sentinel-1 and Sentinel-2 dataset by creating scatterplot between the parameters derived from them. Also analyzed the difference in them for both mangroves and other vegetation. For mangroves, EVI (Enhanced Vegetation Index) and PRVI (Polarimetric Radar Vegetation Index) have relatively strong relationships with biomass. Whereas for other vegetation, CMVI (Combined Mangrove vegetation Index) and DOP (Degree of Polarization) show similarly strong associations with biomass. Keywords: Mangroves, NDVI, PRVI, EVI, CMVI, ORNL DAAC