Ground and Volume Scattering Separation in Compact Polarimentric Interferometric SAR Data
This work presents a methodology to separate the ground and volume contributions from compact polarimetric SAR interferometric (PolInSAR) data over forest areas. One can decompose the PolInSAR data into two covariance matrices from ground and volume in a particular resolution cell, relying on the as...
Published in: | 2022 URSI Regional Conference on Radio Science (USRI-RCRS) |
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Main Authors: | , , |
Format: | Conference Object |
Language: | English |
Published: |
2022
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Subjects: | |
Online Access: | https://elib.dlr.de/188444/ https://elib.dlr.de/188444/1/URSI_RCRS_2022_SD.pdf |
Summary: | This work presents a methodology to separate the ground and volume contributions from compact polarimetric SAR interferometric (PolInSAR) data over forest areas. One can decompose the PolInSAR data into two covariance matrices from ground and volume in a particular resolution cell, relying on the assumptions of the two-layer model. We demonstrate this approach using simulated single baseline compact polarimetric SAR data of the BioSAR-2008 mission over boreal forests in Northern Sweden. |
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