InSAR-based estimation of forest above-ground biomass using phase histogram technique

Abstract

This paper introduces a method for estimating forest above-ground biomass (AGB) using the Interferometric SAR (InSAR)-based Phase Histogram (PH) technique. This novel technique allows for the extraction of 3D vertical forest structure using only a single interferometric pair to acquire a coarse-resolution backscatter intensity distribution in the height direction. Through 3D backscatter distribution, we can extract forest height, the intensity at predefined height bins and introduce the volume-to-ground intensity ratio (VGR) factor to investigate their sensitivities to forest AGB. To validate the method, we use the airborne fully polarized TomoSense dataset, flight-tested by European Space Agency (ESA) in Kermeter area at Eifel National Park, Germany, in 2020. We adopt both multivariate linear stepwise regression (MLSR) and random forest (RF) models to verify the feasibility of the PH technique in forest AGB estimation. Experimental results show that the PH technique effectively captures the vertical structure of the forest at a certain resolution. The forest height, the PH-derived backscatter intensity at a fixed height and VGR have good positive correlation with AGB. Notably, combining forest height, the intensity at fixed height layers and VGR significantly improves the inversion precision of forest AGB. Specifically, compared with LiDAR-derived AGB, the average root-mean-square error (RMSE) of MLSR and RF models estimates combining P- and L-band 2D + 3D observables are 57.92 ton/ha and 55.11 ton/ha, with Pearson correlation coefficient (PCC) of 0.75 and 0.77, respectively. This study presents a promising alternative approach for current and future SAR Earth observation missions aimed at forest vertical structure construction and AGB estimation when only a few of single-polarization SAR images are available.