Litcius/Paper detail

Interferometric Ground Cancellation for Above Ground Biomass Estimation

Mauro Mariotti d’Alessandro, Stefano Tebaldini, S. Quegan, Maciej J. Soja, Lars M. H. Ulander, Klaus Scipal

2020IEEE Transactions on Geoscience and Remote Sensing26 citationsDOI

Abstract

A new processing technique, i.e., ground cancellation, which removes the ground signal from a pair of interferometric synthetic aperture radar (SAR) images, is used to emphasize the response from above-ground targets. This technique is of particular interest when studying forest canopies using low-frequency signals able to reach the underlying ground, in which case the portion of the signal coming from the ground interferes with the recovery of information about the vegetation. We demonstrate that the power in ground-canceled P-band HV SAR data gives significantly higher correlations with above-ground biomass (AGB) than the interferometric images considered separately. In addition, a significant increase in the sensitivity of backscatter to AGB is observed. Ground-canceled power may then be modeled or regressed to estimate AGB; these possibilities are not discussed here as they will be the topic of forthcoming publications. The effectiveness of this technique is proven through simulations and analysis of real data gathered on tropical forests. The stability of the technique is analyzed under the digital terrain model and baseline control errors, and compensation strategies for these errors are presented.

Topics & Concepts

Remote sensingSynthetic aperture radarInterferometryInterferometric synthetic aperture radarTerrainBackscatter (email)Environmental scienceGround truthVegetation (pathology)ClutterRadar imagingSensitivity (control systems)RadarDigital elevation modelGeologyComputer scienceGeographyPhysicsOpticsTelecommunicationsArtificial intelligenceEngineeringElectronic engineeringMedicineCartographyWirelessPathologySynthetic Aperture Radar (SAR) Applications and TechniquesRemote Sensing and LiDAR ApplicationsSoil Moisture and Remote Sensing