Forest Stand Height Estimation using Inversion of RVoG Model over Forest of North-Eastern India
Presented at the 3rd Conference of the Arabian Journal of Geosciences, Sousse, Tunisia, 2020.
In recent years, numerous studies have focused on estimating forest height using advanced remote sensing techniques, recognizing its critical role in biomass estimation and carbon sequestration research. Among these, Polarimetric Interferometric Synthetic Aperture Radar (PolInSAR) has emerged as a powerful method due to its sensitivity to the vertical structure of forest canopies. This paper explores the use of the Random Volume over Ground (RVoG) model for forward scattering modelling and employs a Three-Stage Inversion (TSI) technique to retrieve forest stand height. Utilizing single-baseline L-band ALOS-2 PALSAR data acquired over the Saipung Reserve Forest in Meghalaya, North-Eastern India, the study achieves a strong correlation (R = 0.81) between field-measured and estimated forest heights, with an RMSE of 5.05 meters. The results underscore the effectiveness of PolInSAR for accurate forest stand height retrieval and highlight its potential in forest biophysical parameter estimation.
Citation:
Mungalpara, Ankita, Sanid Chirakkal, Deepak Putrevu, and Suman Mitra. "Forest stand height estimation using inversion of RVoG model over forest of north-eastern India." In Conference of the Arabian Journal of Geosciences, pp. 19-22. Cham: Springer Nature Switzerland, 2020. https://doi.org/10.1007/978-3-031-43759-5_5