Determining the Points of Change in Time Series of Polarimetric SAR Data

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Abstract

We present the likelihood ratio test statistic for the homogeneity of several complex variance–covariance matrices that may be used in order to assess whether at least one change has taken place in a time series of SAR data. Furthermore, we give a factorization of this test statistic into a product of test statistics that each tests simpler hypotheses of homogeneity up to a certain point and that are independent if the hypothesis of total homogeneity is true. This factorization is used in determining the (pixelwise) time points of change in a series of six L-band EMISAR polarimetric SAR data. The pixelwise analyses are applied on homogeneous subareas covered with different vegetation types using the distribution of the observed p-values.
Original languageEnglish
JournalIEEE Transactions on Geoscience and Remote Sensing
Volume54
Issue number5
Pages (from-to)3007-3024
ISSN0196-2892
DOIs
Publication statusPublished - 2016

Keywords

  • Complex covariance matrix test statistic
  • Complex Wishart distribution
  • Dual polarization
  • EMISAR
  • Full polarization
  • Multitemporal synthetic aperture radar (SAR) data
  • Omnibus test statistic
  • Quad polarization
  • Remote sensing change detection

Cite this

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title = "Determining the Points of Change in Time Series of Polarimetric SAR Data",
abstract = "We present the likelihood ratio test statistic for the homogeneity of several complex variance–covariance matrices that may be used in order to assess whether at least one change has taken place in a time series of SAR data. Furthermore, we give a factorization of this test statistic into a product of test statistics that each tests simpler hypotheses of homogeneity up to a certain point and that are independent if the hypothesis of total homogeneity is true. This factorization is used in determining the (pixelwise) time points of change in a series of six L-band EMISAR polarimetric SAR data. The pixelwise analyses are applied on homogeneous subareas covered with different vegetation types using the distribution of the observed p-values.",
keywords = "Complex covariance matrix test statistic, Complex Wishart distribution, Dual polarization, EMISAR, Full polarization, Multitemporal synthetic aperture radar (SAR) data, Omnibus test statistic, Quad polarization, Remote sensing change detection",
author = "Knut Conradsen and Nielsen, {Allan Aasbjerg} and Henning Skriver",
year = "2016",
doi = "10.1109/TGRS.2015.2510160",
language = "English",
volume = "54",
pages = "3007--3024",
journal = "I E E E Transactions on Geoscience and Remote Sensing",
issn = "0196-2892",
publisher = "Institute of Electrical and Electronics Engineers",
number = "5",

}

Determining the Points of Change in Time Series of Polarimetric SAR Data. / Conradsen, Knut; Nielsen, Allan Aasbjerg; Skriver, Henning.

In: IEEE Transactions on Geoscience and Remote Sensing, Vol. 54, No. 5, 2016, p. 3007-3024.

Research output: Contribution to journalJournal articleResearchpeer-review

TY - JOUR

T1 - Determining the Points of Change in Time Series of Polarimetric SAR Data

AU - Conradsen, Knut

AU - Nielsen, Allan Aasbjerg

AU - Skriver, Henning

PY - 2016

Y1 - 2016

N2 - We present the likelihood ratio test statistic for the homogeneity of several complex variance–covariance matrices that may be used in order to assess whether at least one change has taken place in a time series of SAR data. Furthermore, we give a factorization of this test statistic into a product of test statistics that each tests simpler hypotheses of homogeneity up to a certain point and that are independent if the hypothesis of total homogeneity is true. This factorization is used in determining the (pixelwise) time points of change in a series of six L-band EMISAR polarimetric SAR data. The pixelwise analyses are applied on homogeneous subareas covered with different vegetation types using the distribution of the observed p-values.

AB - We present the likelihood ratio test statistic for the homogeneity of several complex variance–covariance matrices that may be used in order to assess whether at least one change has taken place in a time series of SAR data. Furthermore, we give a factorization of this test statistic into a product of test statistics that each tests simpler hypotheses of homogeneity up to a certain point and that are independent if the hypothesis of total homogeneity is true. This factorization is used in determining the (pixelwise) time points of change in a series of six L-band EMISAR polarimetric SAR data. The pixelwise analyses are applied on homogeneous subareas covered with different vegetation types using the distribution of the observed p-values.

KW - Complex covariance matrix test statistic

KW - Complex Wishart distribution

KW - Dual polarization

KW - EMISAR

KW - Full polarization

KW - Multitemporal synthetic aperture radar (SAR) data

KW - Omnibus test statistic

KW - Quad polarization

KW - Remote sensing change detection

U2 - 10.1109/TGRS.2015.2510160

DO - 10.1109/TGRS.2015.2510160

M3 - Journal article

VL - 54

SP - 3007

EP - 3024

JO - I E E E Transactions on Geoscience and Remote Sensing

JF - I E E E Transactions on Geoscience and Remote Sensing

SN - 0196-2892

IS - 5

ER -