Volume scattering modelling in PolSAR decompositions

Study of ALOS PALSAR data over boreal forest

Oleg Antropov, Yrjö Rauste, Tuomas Häme

Research output: Contribution to journalArticleScientificpeer-review

70 Citations (Scopus)

Abstract

Model-based approaches for decomposing polarimetric backscatter data from boreal forest are discussed in this paper. Several model-based decompositions are analyzed with respect for the most accurate estimation of the volume scattering component. A novel generalized model for description of the volume contribution is proposed when observed backscatter from forest indicates that media does not follow azimuthal symmetry case. The model can be adjusted to the polarimetric synthetic aperture radar (PolSAR) data itself, taking into consideration higher sensitivity of HH against VV backscattering term to the presence of canopy at L-band. The model is general enough to allow a broad range of canopies to be modeled and is shown to comply with several earlier proposed volume scattering mechanism models. It is afterward incorporated in the Freeman-Durden three-component decomposition, yielding an improved modification. The performance of the proposed modification is evaluated using multitemporal ALOS PALSAR data acquired over Kuortane area in central Finland, representing typical mixed boreal forestland. Several decompositions are also benchmarked in order to see how they satisfy physical requirements when decomposing covariance matrix into a weighted sum of individual scattering mechanism contributions. When using experimental data, the proposed decomposition is shown to better satisfy non-negativity constraints for the covariance matrix eigenvalues at each decomposition step with less additional PolSAR data averaging needed. Discussed decompositions are also evaluated for the accuracy of initial stratification based on dominating scattering mechanism using ground reference data.
Original languageEnglish
Pages (from-to)3838-3848
Number of pages11
JournalIEEE Transactions on Geoscience and Remote Sensing
Volume49
Issue number10
DOIs
Publication statusPublished - 2011
MoE publication typeA1 Journal article-refereed

Fingerprint

PALSAR
ALOS
Synthetic aperture radar
boreal forest
synthetic aperture radar
scattering
Scattering
decomposition
Decomposition
modeling
Covariance matrix
backscatter
canopy
matrix
eigenvalue
Backscattering
symmetry
stratification

Keywords

  • Boreal forest
  • model-based decomposition
  • polarimetry
  • scattering mechanisms
  • synthetic aperture radar (SAR)

Cite this

@article{d477ae277a5a481983ebf77081637097,
title = "Volume scattering modelling in PolSAR decompositions: Study of ALOS PALSAR data over boreal forest",
abstract = "Model-based approaches for decomposing polarimetric backscatter data from boreal forest are discussed in this paper. Several model-based decompositions are analyzed with respect for the most accurate estimation of the volume scattering component. A novel generalized model for description of the volume contribution is proposed when observed backscatter from forest indicates that media does not follow azimuthal symmetry case. The model can be adjusted to the polarimetric synthetic aperture radar (PolSAR) data itself, taking into consideration higher sensitivity of HH against VV backscattering term to the presence of canopy at L-band. The model is general enough to allow a broad range of canopies to be modeled and is shown to comply with several earlier proposed volume scattering mechanism models. It is afterward incorporated in the Freeman-Durden three-component decomposition, yielding an improved modification. The performance of the proposed modification is evaluated using multitemporal ALOS PALSAR data acquired over Kuortane area in central Finland, representing typical mixed boreal forestland. Several decompositions are also benchmarked in order to see how they satisfy physical requirements when decomposing covariance matrix into a weighted sum of individual scattering mechanism contributions. When using experimental data, the proposed decomposition is shown to better satisfy non-negativity constraints for the covariance matrix eigenvalues at each decomposition step with less additional PolSAR data averaging needed. Discussed decompositions are also evaluated for the accuracy of initial stratification based on dominating scattering mechanism using ground reference data.",
keywords = "Boreal forest, model-based decomposition, polarimetry, scattering mechanisms, synthetic aperture radar (SAR)",
author = "Oleg Antropov and Yrj{\"o} Rauste and Tuomas H{\"a}me",
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year = "2011",
doi = "10.1109/TGRS.2011.2138146",
language = "English",
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journal = "IEEE Transactions on Geoscience and Remote Sensing",
issn = "0196-2892",
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}

Volume scattering modelling in PolSAR decompositions : Study of ALOS PALSAR data over boreal forest. / Antropov, Oleg; Rauste, Yrjö; Häme, Tuomas.

In: IEEE Transactions on Geoscience and Remote Sensing, Vol. 49, No. 10, 2011, p. 3838-3848.

Research output: Contribution to journalArticleScientificpeer-review

TY - JOUR

T1 - Volume scattering modelling in PolSAR decompositions

T2 - Study of ALOS PALSAR data over boreal forest

AU - Antropov, Oleg

AU - Rauste, Yrjö

AU - Häme, Tuomas

N1 - Project code: 26202

PY - 2011

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N2 - Model-based approaches for decomposing polarimetric backscatter data from boreal forest are discussed in this paper. Several model-based decompositions are analyzed with respect for the most accurate estimation of the volume scattering component. A novel generalized model for description of the volume contribution is proposed when observed backscatter from forest indicates that media does not follow azimuthal symmetry case. The model can be adjusted to the polarimetric synthetic aperture radar (PolSAR) data itself, taking into consideration higher sensitivity of HH against VV backscattering term to the presence of canopy at L-band. The model is general enough to allow a broad range of canopies to be modeled and is shown to comply with several earlier proposed volume scattering mechanism models. It is afterward incorporated in the Freeman-Durden three-component decomposition, yielding an improved modification. The performance of the proposed modification is evaluated using multitemporal ALOS PALSAR data acquired over Kuortane area in central Finland, representing typical mixed boreal forestland. Several decompositions are also benchmarked in order to see how they satisfy physical requirements when decomposing covariance matrix into a weighted sum of individual scattering mechanism contributions. When using experimental data, the proposed decomposition is shown to better satisfy non-negativity constraints for the covariance matrix eigenvalues at each decomposition step with less additional PolSAR data averaging needed. Discussed decompositions are also evaluated for the accuracy of initial stratification based on dominating scattering mechanism using ground reference data.

AB - Model-based approaches for decomposing polarimetric backscatter data from boreal forest are discussed in this paper. Several model-based decompositions are analyzed with respect for the most accurate estimation of the volume scattering component. A novel generalized model for description of the volume contribution is proposed when observed backscatter from forest indicates that media does not follow azimuthal symmetry case. The model can be adjusted to the polarimetric synthetic aperture radar (PolSAR) data itself, taking into consideration higher sensitivity of HH against VV backscattering term to the presence of canopy at L-band. The model is general enough to allow a broad range of canopies to be modeled and is shown to comply with several earlier proposed volume scattering mechanism models. It is afterward incorporated in the Freeman-Durden three-component decomposition, yielding an improved modification. The performance of the proposed modification is evaluated using multitemporal ALOS PALSAR data acquired over Kuortane area in central Finland, representing typical mixed boreal forestland. Several decompositions are also benchmarked in order to see how they satisfy physical requirements when decomposing covariance matrix into a weighted sum of individual scattering mechanism contributions. When using experimental data, the proposed decomposition is shown to better satisfy non-negativity constraints for the covariance matrix eigenvalues at each decomposition step with less additional PolSAR data averaging needed. Discussed decompositions are also evaluated for the accuracy of initial stratification based on dominating scattering mechanism using ground reference data.

KW - Boreal forest

KW - model-based decomposition

KW - polarimetry

KW - scattering mechanisms

KW - synthetic aperture radar (SAR)

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JO - IEEE Transactions on Geoscience and Remote Sensing

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