Evaluating P-Band TomoSAR for Biomass Retrieval in Boreal Forest

P-band synthetic aperture radar (SAR) is sensitive to above-ground biomass (AGB) but retrieval accuracy has been shown to deteriorate in topographic areas. In boreal forest, the signal penetrates through the canopy to interact with the ground producing variations in backscatter depending on ground t...

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Published in:IEEE Transactions on Geoscience and Remote Sensing
Main Authors: Blomberg, Erik, Ulander, Lars, Tebaldini, S., Ferro-Famil, L.
Language:unknown
Published: 2021
Subjects:
Online Access:https://doi.org/10.1109/TGRS.2020.3020775
https://research.chalmers.se/en/publication/523741
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spelling ftchalmersuniv:oai:research.chalmers.se:523741 2023-05-15T17:44:59+02:00 Evaluating P-Band TomoSAR for Biomass Retrieval in Boreal Forest Blomberg, Erik Ulander, Lars Tebaldini, S. Ferro-Famil, L. 2021 text https://doi.org/10.1109/TGRS.2020.3020775 https://research.chalmers.se/en/publication/523741 unknown http://dx.doi.org/10.1109/TGRS.2020.3020775 https://research.chalmers.se/en/publication/523741 Remote Sensing Geophysics Signal Processing Biomass P-band tomography boreal forest 2021 ftchalmersuniv https://doi.org/10.1109/TGRS.2020.3020775 2022-12-11T07:18:37Z P-band synthetic aperture radar (SAR) is sensitive to above-ground biomass (AGB) but retrieval accuracy has been shown to deteriorate in topographic areas. In boreal forest, the signal penetrates through the canopy to interact with the ground producing variations in backscatter depending on ground topography, forest structure, and soil moisture. Tomographic processing of multiple SAR images Tomographic SAR (TomoSAR) provides information about the vertical backscatter distribution. This article evaluates the use of P-band TomoSAR data to improve AGB retrievals from backscattered intensity by suppressing the backscattered signal from the ground. This approach can be used even when the tomographic resolution is insufficient to resolve the vertical backscatter profile. The analysis is based on P-band data from two campaigns: BioSAR-1 (2007) in Remingstorp, southern Sweden, and BioSAR-2 (2008) in Krycklan (KR), northern Sweden. BioSAR airborne data were also processed to correspond as closely as possible to future BIOMASS TomoSAR acquisitions, with BioSAR-2-based results shown. A power law AGB model using volumetric HV polarized backscatter performs best in KR, with training residual root mean-squared error (RMSE) of 30%-36% (27-33 t/ha) for airborne data and 38%-39% for simulated BIOMASS data. Airborne TomoSAR data suggest that both vertical and horizontal tomographic resolution are of importance and that it is possible to greatly reduce AGB retrieval bias when compared with airborne P-band SAR backscatter intensity-based retrievals. A lack of significant ground slopes in Remningstorp reduces the benefit of using TomoSAR data which performs similar to retrievals based solely on P-band SAR backscatter intensity. Other/Unknown Material Northern Sweden Chalmers University of Technology: Chalmers research IEEE Transactions on Geoscience and Remote Sensing 59 5 3793 3804
institution Open Polar
collection Chalmers University of Technology: Chalmers research
op_collection_id ftchalmersuniv
language unknown
topic Remote Sensing
Geophysics
Signal Processing
Biomass
P-band
tomography
boreal forest
spellingShingle Remote Sensing
Geophysics
Signal Processing
Biomass
P-band
tomography
boreal forest
Blomberg, Erik
Ulander, Lars
Tebaldini, S.
Ferro-Famil, L.
Evaluating P-Band TomoSAR for Biomass Retrieval in Boreal Forest
topic_facet Remote Sensing
Geophysics
Signal Processing
Biomass
P-band
tomography
boreal forest
description P-band synthetic aperture radar (SAR) is sensitive to above-ground biomass (AGB) but retrieval accuracy has been shown to deteriorate in topographic areas. In boreal forest, the signal penetrates through the canopy to interact with the ground producing variations in backscatter depending on ground topography, forest structure, and soil moisture. Tomographic processing of multiple SAR images Tomographic SAR (TomoSAR) provides information about the vertical backscatter distribution. This article evaluates the use of P-band TomoSAR data to improve AGB retrievals from backscattered intensity by suppressing the backscattered signal from the ground. This approach can be used even when the tomographic resolution is insufficient to resolve the vertical backscatter profile. The analysis is based on P-band data from two campaigns: BioSAR-1 (2007) in Remingstorp, southern Sweden, and BioSAR-2 (2008) in Krycklan (KR), northern Sweden. BioSAR airborne data were also processed to correspond as closely as possible to future BIOMASS TomoSAR acquisitions, with BioSAR-2-based results shown. A power law AGB model using volumetric HV polarized backscatter performs best in KR, with training residual root mean-squared error (RMSE) of 30%-36% (27-33 t/ha) for airborne data and 38%-39% for simulated BIOMASS data. Airborne TomoSAR data suggest that both vertical and horizontal tomographic resolution are of importance and that it is possible to greatly reduce AGB retrieval bias when compared with airborne P-band SAR backscatter intensity-based retrievals. A lack of significant ground slopes in Remningstorp reduces the benefit of using TomoSAR data which performs similar to retrievals based solely on P-band SAR backscatter intensity.
author Blomberg, Erik
Ulander, Lars
Tebaldini, S.
Ferro-Famil, L.
author_facet Blomberg, Erik
Ulander, Lars
Tebaldini, S.
Ferro-Famil, L.
author_sort Blomberg, Erik
title Evaluating P-Band TomoSAR for Biomass Retrieval in Boreal Forest
title_short Evaluating P-Band TomoSAR for Biomass Retrieval in Boreal Forest
title_full Evaluating P-Band TomoSAR for Biomass Retrieval in Boreal Forest
title_fullStr Evaluating P-Band TomoSAR for Biomass Retrieval in Boreal Forest
title_full_unstemmed Evaluating P-Band TomoSAR for Biomass Retrieval in Boreal Forest
title_sort evaluating p-band tomosar for biomass retrieval in boreal forest
publishDate 2021
url https://doi.org/10.1109/TGRS.2020.3020775
https://research.chalmers.se/en/publication/523741
genre Northern Sweden
genre_facet Northern Sweden
op_relation http://dx.doi.org/10.1109/TGRS.2020.3020775
https://research.chalmers.se/en/publication/523741
op_doi https://doi.org/10.1109/TGRS.2020.3020775
container_title IEEE Transactions on Geoscience and Remote Sensing
container_volume 59
container_issue 5
container_start_page 3793
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