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The BIOMASS level 2 prototype processor: design and experimental results of above-ground biomass estimation

Citation

Banda, F and Giudici, D and Toan, TL and Mariotti, M and Papathanassiou, K and Quegan, S and Riembauer, G and Scipal, K and Soja, MJ and Tebaldini, S and Ulander, LHM and Villard, L, The BIOMASS level 2 prototype processor: design and experimental results of above-ground biomass estimation, Remote Sensing, 12, (6) pp. 1-28. ISSN 2072-4292 (2020) [Refereed Article]


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Copyright 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

DOI: doi:10.3390/rs12060985

Abstract

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.

Item Details

Item Type:Refereed Article
Keywords:BIOMASS, SAR, polarimetry, tomography, interferometry, forest height, forest disturbance, earth explorer, DTM
Research Division:Earth Sciences
Research Group:Atmospheric sciences
Research Field:Meteorology
Objective Division:Energy
Objective Group:Processing of energy sources
Objective Field:Biomass processing
UTAS Author:Soja, MJ (Dr Maciej Soja)
ID Code:152115
Year Published:2020
Web of Science® Times Cited:4
Deposited By:Geography and Spatial Science
Deposited On:2022-08-11
Last Modified:2022-09-05
Downloads:3 View Download Statistics

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