Speaker
Description
Synthetic Aperture Radar (SAR) Tomography (TomoSAR) is an emerging technology to image the 3D structure of the illuminated media. TomoSAR exploits the key feature of microwaves to penetrate into vegetation, snow, and ice, hence providing the possibility to see features that are hidden to optical and hyper-spectral systems. The research on the use of P-Band waves, in particular, has been largely propelled since 2007 in experimental studies supporting the future spaceborne Mission BIOMASS, to be launched in 2022 with the aim of mapping forest Above Ground Biomass (AGB) accurately and globally. The results obtained in the frame of these studies demonstrated that TomoSAR can be used for accurate retrieval of geophysical variables such as forest height and terrain topography, and, especially in the case of dense tropical forests, to provide a more direct link to AGB. In this talk, we analyze the causes behind the link between tomographic intensities and forest AGB, trying to single out the roles of forest structure, rejection of ground contributions, and wave extinction. The analysis is carried out by studying the correlation with respect to forest AGB of several forest parameters, including forest height, extinction, and ground and volume backscattered intensities, as derived by using multi-pass tomographic data and single-baseline interferometric data. Results indicate that tomography brings information about AGB in tropical forests by virtue of its ability to single out the returns from different layers within the vegetation while rejecting ground scattering. Interestingly, this study indicates that that total volume backscatter is simply not the right parameter to consider for AGB retrieval, and points out the role of forest height and wave extinction. On the base of these findings, an interferometric approach is proposed to enhance the correlation between Radar intensity and AGB by or notching out ground scattering while preserving scattering from the main canopy layers.
