The BIOMASS Level 2 Prototype Processor: Design and Experimental Results of Above-Ground Biomass Estimation

被引:21
作者
Banda, Francesco [1 ]
Giudici, Davide [1 ]
Le Toan, Thuy [2 ]
d'Alessandro, Mauro Mariotti [3 ]
Papathanassiou, Kostas [4 ]
Quegan, Shaun [5 ]
Riembauer, Guido [6 ]
Scipal, Klaus [6 ]
Soja, Maciej [7 ,8 ]
Tebaldini, Stefano [3 ]
Ulander, Lars [9 ]
Villard, Ludovic [2 ]
机构
[1] Aresys, I-20132 Milan, Italy
[2] Ctr Etud Spati Biosphere, F-31400 Toulouse, France
[3] Politecn Milan, Dipartimento Elettron Informaz & Bioingn, I-20133 Milan, Italy
[4] German Aerosp Ctr DLR, D-82234 Wessling, Germany
[5] Univ Sheffield, Sch Math & Stat, Sheffield S10 2TG, S Yorkshire, England
[6] European Space Agcy, NL-2201 AZ Noordwijk, Netherlands
[7] MJ Soja Consulting, Hobart, Tas 7000, Australia
[8] Univ Tasmania, Sch Technol, Environm & Design, Hobart, Tas, Australia
[9] Chalmers Univ Technol, Dept Space Earth & Environm, S-41296 Gothenburg, Sweden
基金
英国自然环境研究理事会;
关键词
BIOMASS; SAR; polarimetry; tomography; interferometry; forest height; forest disturbance; earth explorer; DTM; FOREST CARBON STOCKS; SAR TOMOGRAPHY; RETRIEVAL; CALIBRATION; INVERSION; BENCHMARK; MISSION; SINGLE; SERIES;
D O I
10.3390/rs12060985
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
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.
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页数:28
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