The BIOMASS level 2 prototype processor: Design and experimental results of above-ground biomass estimation
Journal article, 2020

BIOMASS is ESA's seventh Earth Explorer mission, scheduled for launch in 2022. The satellite will be the first P-band SAR sensor in space and will be operated in fully polarimetric interferometric and tomographic modes. The mission aim is to map forest above-ground biomass (AGB), forest height (FH) and severe forest disturbance (FD) globally with a particular focus on tropical forests. This paper presents the algorithms developed to estimate these biophysical parameters from the BIOMASS level 1 SAR measurements and their implementation in the BIOMASS level 2 prototype processor with a focus on the AGB product. The AGB product retrieval uses a physically-based inversion model, using ground-canceled level 1 data as input. The FH product retrieval applies a classical PolInSAR inversion, based on the Random Volume over Ground Model (RVOG). The FD product will provide an indication of where significant changes occurred within the forest, based on the statistical properties of SAR data. We test the AGB retrieval using modified airborne P-Band data from the AfriSAR and TropiSAR campaigns together with reference data from LiDAR-based AGB maps and plot-based ground measurements. For AGB estimation based on data from a single heading, comparison with reference data yields relative Root Mean Square Difference (RMSD) values mostly between 20% and 30%. Combining different headings in the estimation process significantly improves the AGB retrieval to slightly less than 20%. The experimental results indicate that the implemented retrieval scheme provides robust results that are within mission requirements.

Forest height

DTM

Earth explorer

Interferometry

SAR

Tomography

Forest disturbance

Polarimetry

BIOMASS

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Published in

Remote Sensing

20724292 (eISSN)

Vol. 12 Issue 6 art. no 985

Research Project(s)

BIOMASS level 2 implementation study

European Space Research and Technology Centre (ESA ESTEC) (4000119231/167/NL/CT), 2017-02-01 -- 2020-01-31.

Categorizing

Subject Categories (SSIF 2011)

Forest Science

Geophysics

Signal Processing

Identifiers

DOI

10.3390/rs12060985

More information

Latest update

11/13/2020