Maciej J. Soia,Mauro Mariotti d'Alessandro,Shaun Quegan,Stefano Tebaldini,Lars M. H. Ulander
出处
期刊:International Geoscience and Remote Sensing Symposium日期:2018-07-22被引量:6
标识
DOI:10.1109/igarss.2018.8517614
摘要
This paper presents a new algorithm for forest biomass estimation from P-band synthetic-aperture radar (SAR) backscatter data, notch-filtered at ground-level. A semi-empirical model is fitted to spatial and polarization trends in the backscatter data and no reference biomass data are needed for training. An evaluation on airborne P-band SAR data from a tropical test site in Gabon results in a root-mean-square error lower than 20% and a correlation better than 90%.