Estimating forest height and biomass of tropical forests with P-band TomoSAR and GEDI observations

Understanding the vertical structure of forests, including metrics like forest height and above-ground biomass (AGB), is crucial for assessing carbon dynamics, ecosystem diversity, and forest dynamics. While lidar technology is widely used for this purpose, the potential of P-band synthetic aperture radar tomography (TomoSAR) in capturing biomass and vertical forest structure remains underexplored. In this study, we used lidar data from NASA's Global Ecosystem Dynamics Investigation (GEDI) to investigate the sensitivity of airborne P-band SAR tomography backscatter to forest height and AGB in two tropical forests in Gabon, Africa (Lopé and Mondah). We applied machine learning models to estimate forest height and AGB, respectively, from TomoSAR profiles, and validated our results against data from the Land, Vegetation, and Ice Sensor (LVIS) airborne lidar. Our findings demonstrate moderate performance in estimating forest height and moderate to good performance in estimating total AGB. Additionally, we examined the vertical distribution of AGB using corrected TomoSAR backscatter and compared it with AGB profiles derived from field observations in Mondah. Our results suggest the potential of TomoSAR observations for mapping the vertical AGB distribution in tropical forests, although further field observations are necessary to refine these techniques.

This publication is part of Xiao Liu's doctoral thesis on methods for estimating the vertical distribution of forest biomass at the Junior Professorship for Environmental Remote Sensing.

Liu, X., Neigh, C. S. R., Pardini, M., and Forkel, M. (2024).
Estimating forest height and above-ground biomass in tropical forests using P-band TomoSAR and GEDI observations
International Journal of Remote Sensing, 9, 45, 3129-3148, https://doi.org/10.1080/01431161.2024.2343134