Huuva, Ivan and Persson, Henrik and Soja, Maciej J. and Wallerman, Jörgen and Ulander, Lars M. H. and Fransson, Johan
(2020).
Predictions of Biomass Change in a Hemi-Boreal Forest Based on Multi-Polarization L- and P-Band SAR Backscatter.
Canadian Journal of Remote Sensing. 46
, 661-680
[Research article]
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Abstract
Above-ground biomass change accumulated during four growth seasons in a hemi-boreal forest was predicted using airborne L- and P-band synthetic aperture radar (SAR) backscatter. The radar data were collected in the BioSAR 2007 and BioSAR 2010 campaigns over the Remningstorp test site in southern Sweden. Regression models for biomass change were developed from biomass maps created using airborne LiDAR data and field measurements. To facilitate training and prediction on image pairs acquired at different dates, a backscatter offset correction method for L-band data was developed and evaluated. The correction, based on the HV/VV backscatter ratio, facilitated predictions across image pairs almost identical to those obtained using data from the same image pair for both training and prediction. For P-band, previous positive results using an offset correction based on the HH/VV ratio were validated. The best L-band model achieved a root mean square error (RMSE) of 21 t/ha, and the best P-band model achieved an RMSE of 19 t/ha. Those accuracies are similar to that of the LiDAR-based biomass change of 18 t/ha. The limitation of using LiDAR-based data for training was considered. The findings demonstrate potential for improved biomass change predictions from L-band backscatter despite varying environmental conditions and calibration uncertainties.
Authors/Creators: | Huuva, Ivan and Persson, Henrik and Soja, Maciej J. and Wallerman, Jörgen and Ulander, Lars M. H. and Fransson, Johan | ||||||
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Title: | Predictions of Biomass Change in a Hemi-Boreal Forest Based on Multi-Polarization L- and P-Band SAR Backscatter | ||||||
Series Name/Journal: | Canadian Journal of Remote Sensing | ||||||
Year of publishing : | 2020 | ||||||
Volume: | 46 | ||||||
Page range: | 661-680 | ||||||
Number of Pages: | 20 | ||||||
Publisher: | TAYLOR AND FRANCIS INC | ||||||
ISSN: | 0703-8992 | ||||||
Language: | English | ||||||
Publication Type: | Research article | ||||||
Article category: | Scientific peer reviewed | ||||||
Version: | Published version | ||||||
Copyright: | Creative Commons: Attribution 4.0 | ||||||
Full Text Status: | Public | ||||||
Subjects: | (A) Swedish standard research categories 2011 > 2 Engineering and Technology > 207 Environmental Engineering > Remote Sensing | ||||||
URN:NBN: | urn:nbn:se:slu:epsilon-p-109251 | ||||||
Permanent URL: | http://urn.kb.se/resolve?urn=urn:nbn:se:slu:epsilon-p-109251 | ||||||
Additional ID: |
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ID Code: | 23102 | ||||||
Faculty: | S - Faculty of Forest Sciences | ||||||
Department: | (S) > Dept. of Forest Resource Management (NL, NJ) > Dept. of Forest Resource Management | ||||||
Deposited By: | SLUpub Connector | ||||||
Deposited On: | 08 Apr 2021 07:14 | ||||||
Metadata Last Modified: | 08 Apr 2021 07:21 |
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