PolSAR-Decomposition-Based Extended Water Cloud Modeling for Forest Aboveground Biomass Estimation
Polarimetric synthetic aperture radar (PolSAR) remote sensing has been widely used for forest mapping and monitoring. PolSAR data has the capability to provide scattering information that is contributed by different scatterers within a single SAR resolution cell. A methodology for a PolSAR-based ext...
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doaj-f90552460eb74557abf6b4dcfcc404fa2020-11-25T01:35:57ZengMDPI AGRemote Sensing2072-42922019-09-011119228710.3390/rs11192287rs11192287PolSAR-Decomposition-Based Extended Water Cloud Modeling for Forest Aboveground Biomass EstimationShashi Kumar0Rahul D. Garg1Himanshu Govil2Satya P. S. Kushwaha3Indian Institute of Remote Sensing, Dehradun-248001, IndiaIndian Institute of Technology, Roorkee-247667, IndiaNational Institute of Technology, Raipur-492013, IndiaIndian Institute of Remote Sensing, Dehradun-248001, IndiaPolarimetric synthetic aperture radar (PolSAR) remote sensing has been widely used for forest mapping and monitoring. PolSAR data has the capability to provide scattering information that is contributed by different scatterers within a single SAR resolution cell. A methodology for a PolSAR-based extended water cloud model (EWCM) has been proposed and evaluated in this study. Fully polarimetric phased array type L-band synthetic aperture radar (PALSAR) data of advanced land observing satellite (ALOS) was used in this study for forest aboveground biomass (AGB) retrieval of Dudhwa National Park, India. The shift in the polarization orientation angle (POA) is a major problem that affects the PolSAR-based scattering information. The two sources of POA shift are Faraday rotation angle (FRA) and structural properties of the scatterer. Analysis was carried out to explore the effect of FRA in the SAR data. Deorientation of PolSAR data was implemented to minimize any ambiguity in the scattering retrieval of model-based decomposition. After POA compensation of the coherency matrix, a decrease in the power of volume scattering elements was observed for the forest patches. This study proposed a framework to extend the water cloud model for AGB retrieval. The proposed PolSAR-based EWCM showed less dependency on field data for model parameters retrieval. The PolSAR-based scattering was used as input model parameters to derive AGB for the forest area. Regression between PolSAR-decomposition-based volume scattering and AGB was performed. Without deorientation of the PolSAR coherency matrix, EWCM showed a modeled AGB of 92.90 t ha<sup>−1</sup>, and a 0.36 R<sup>2</sup> was recorded through linear regression between the field-measured AGB and the modeled output. After deorientation of the PolSAR data, an increased R<sup>2</sup> (0.78) with lower RMSE (59.77 t ha<sup>−1</sup>) was obtained from EWCM. The study proves the potential of a PolSAR-based semiempirical model for forest AGB retrieval. This study strongly recommends the POA compensation of the coherency matrix for PolSAR-scattering-based semiempirical modeling for forest AGB retrieval.https://www.mdpi.com/2072-4292/11/19/2287polsarscatteringpoafraewcmforest agb |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Shashi Kumar Rahul D. Garg Himanshu Govil Satya P. S. Kushwaha |
spellingShingle |
Shashi Kumar Rahul D. Garg Himanshu Govil Satya P. S. Kushwaha PolSAR-Decomposition-Based Extended Water Cloud Modeling for Forest Aboveground Biomass Estimation Remote Sensing polsar scattering poa fra ewcm forest agb |
author_facet |
Shashi Kumar Rahul D. Garg Himanshu Govil Satya P. S. Kushwaha |
author_sort |
Shashi Kumar |
title |
PolSAR-Decomposition-Based Extended Water Cloud Modeling for Forest Aboveground Biomass Estimation |
title_short |
PolSAR-Decomposition-Based Extended Water Cloud Modeling for Forest Aboveground Biomass Estimation |
title_full |
PolSAR-Decomposition-Based Extended Water Cloud Modeling for Forest Aboveground Biomass Estimation |
title_fullStr |
PolSAR-Decomposition-Based Extended Water Cloud Modeling for Forest Aboveground Biomass Estimation |
title_full_unstemmed |
PolSAR-Decomposition-Based Extended Water Cloud Modeling for Forest Aboveground Biomass Estimation |
title_sort |
polsar-decomposition-based extended water cloud modeling for forest aboveground biomass estimation |
publisher |
MDPI AG |
series |
Remote Sensing |
issn |
2072-4292 |
publishDate |
2019-09-01 |
description |
Polarimetric synthetic aperture radar (PolSAR) remote sensing has been widely used for forest mapping and monitoring. PolSAR data has the capability to provide scattering information that is contributed by different scatterers within a single SAR resolution cell. A methodology for a PolSAR-based extended water cloud model (EWCM) has been proposed and evaluated in this study. Fully polarimetric phased array type L-band synthetic aperture radar (PALSAR) data of advanced land observing satellite (ALOS) was used in this study for forest aboveground biomass (AGB) retrieval of Dudhwa National Park, India. The shift in the polarization orientation angle (POA) is a major problem that affects the PolSAR-based scattering information. The two sources of POA shift are Faraday rotation angle (FRA) and structural properties of the scatterer. Analysis was carried out to explore the effect of FRA in the SAR data. Deorientation of PolSAR data was implemented to minimize any ambiguity in the scattering retrieval of model-based decomposition. After POA compensation of the coherency matrix, a decrease in the power of volume scattering elements was observed for the forest patches. This study proposed a framework to extend the water cloud model for AGB retrieval. The proposed PolSAR-based EWCM showed less dependency on field data for model parameters retrieval. The PolSAR-based scattering was used as input model parameters to derive AGB for the forest area. Regression between PolSAR-decomposition-based volume scattering and AGB was performed. Without deorientation of the PolSAR coherency matrix, EWCM showed a modeled AGB of 92.90 t ha<sup>−1</sup>, and a 0.36 R<sup>2</sup> was recorded through linear regression between the field-measured AGB and the modeled output. After deorientation of the PolSAR data, an increased R<sup>2</sup> (0.78) with lower RMSE (59.77 t ha<sup>−1</sup>) was obtained from EWCM. The study proves the potential of a PolSAR-based semiempirical model for forest AGB retrieval. This study strongly recommends the POA compensation of the coherency matrix for PolSAR-scattering-based semiempirical modeling for forest AGB retrieval. |
topic |
polsar scattering poa fra ewcm forest agb |
url |
https://www.mdpi.com/2072-4292/11/19/2287 |
work_keys_str_mv |
AT shashikumar polsardecompositionbasedextendedwatercloudmodelingforforestabovegroundbiomassestimation AT rahuldgarg polsardecompositionbasedextendedwatercloudmodelingforforestabovegroundbiomassestimation AT himanshugovil polsardecompositionbasedextendedwatercloudmodelingforforestabovegroundbiomassestimation AT satyapskushwaha polsardecompositionbasedextendedwatercloudmodelingforforestabovegroundbiomassestimation |
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