Forest Biomass Retrieval from L-Band SAR Using Tomographic Ground Backscatter Removal
Journal article, 2018

A tomographic synthetic aperture radar (TomoSAR) represents a possible route to improved retrievals of forest parameters. Simulated orbital L-band TomoSAR data corresponding to the proposed Satellites for Observation and Communications-Companion Satellite (SAOCOM-CS) mission (1.275 GHz) are evaluated for retrieval of above-ground biomass in boreal forest. L-band data and biomass measurements, collected at the Krycklan test site in northern Sweden as part of the BioSAR 2008 campaign, are used to compare biomass retrievals from SAOCOM-CS to those based on SAOCOM SAR data. Both data sets are in turn compared with the corresponding airborne case, as represented by experimental airborne SAR through processing of the original SAR data. TomoSAR retrievals use a model involving a logarithmic transform of the volumetric backscatter intensity, Ivol, defined as the total backscatter originating between 10 and 30 m above ground. SAR retrievals are obtained with slope-compensated intensity γ0using the same model. It is concluded that tomography using SAOCOM-CS represents an improvement over an airborne SAR imagery, resulting in biomass retrievals from a single polarization (HH) having a 26%-30% root-mean-square error with a little to no impact from the look direction or the local topography.

tomography

L-band

Satellites for Observation and Communications-Companion Satellite (SAOCOM-CS)

Biomass

boreal forest

Author

Erik Blomberg

Chalmers, Space, Earth and Environment, Microwave and Optical Remote Sensing

L. Ferro-Famil

University of Rennes 1

Maciej Soja

Chalmers, Space, Earth and Environment, Microwave and Optical Remote Sensing

Lars Ulander

Chalmers, Space, Earth and Environment, Microwave and Optical Remote Sensing

S. Tebaldini

Polytechnic University of Milan

IEEE Geoscience and Remote Sensing Letters

1545-598X (ISSN) 15580571 (eISSN)

Vol. 15 7 1030-1034

Subject Categories

Remote Sensing

Geophysics

Physical Geography

DOI

10.1109/LGRS.2018.2819884

More information

Latest update

12/7/2018