Land Cover Characterization and Classification of Arctic Tundra Environments by Means of Polarized Synthetic Aperture X- and C-Band Radar (PolSAR) and Landsat 8 Multispectral Imagery — Richards Island, Canada

In this work the potential of polarimetric Synthetic Aperture Radar (PolSAR) data of dual-polarized TerraSAR-X (HH/VV) and quad-polarized Radarsat-2 was examined in combination with multispectral Landsat 8 data for unsupervised and supervised classification of tundra land cover types of Richards Isl...

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Main Authors: Tobias Ullmann, Andreas Schmitt, Achim Roth, Jason Duffe, Stefan Dech, Hans-Wolfgang Hubberten, Roland Baumhauer
Format: Article
Language:English
Published: MDPI AG 2014-09-01
Series:Remote Sensing
Subjects:
SAR
Online Access:http://www.mdpi.com/2072-4292/6/9/8565
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spelling doaj-732ea4fe7501452cb2c5a298299362782020-11-24T22:25:21ZengMDPI AGRemote Sensing2072-42922014-09-01698565859310.3390/rs6098565rs6098565Land Cover Characterization and Classification of Arctic Tundra Environments by Means of Polarized Synthetic Aperture X- and C-Band Radar (PolSAR) and Landsat 8 Multispectral Imagery — Richards Island, CanadaTobias Ullmann0Andreas Schmitt1Achim Roth2Jason Duffe3Stefan Dech4Hans-Wolfgang Hubberten5Roland Baumhauer6Institute for Geography and Geology, University of Wuerzburg, D-97074 Wuerzburg, GermanyGerman Aerospace Center (DLR), German Remote Sensing Data Center (DFD), D-82234 Wessling, GermanyGerman Aerospace Center (DLR), German Remote Sensing Data Center (DFD), D-82234 Wessling, GermanyNational Wildlife Research Center (NWRC), Ottawa, ON K1A 0H3, CanadaInstitute for Geography and Geology, University of Wuerzburg, D-97074 Wuerzburg, GermanyAlfred Wegener Institute for Polar and Marine Research (AWI), Research Section Potsdam, Telegrafenberg A43, D-14473 Potsdam, GermanyInstitute for Geography and Geology, University of Wuerzburg, D-97074 Wuerzburg, GermanyIn this work the potential of polarimetric Synthetic Aperture Radar (PolSAR) data of dual-polarized TerraSAR-X (HH/VV) and quad-polarized Radarsat-2 was examined in combination with multispectral Landsat 8 data for unsupervised and supervised classification of tundra land cover types of Richards Island, Canada. The classification accuracies as well as the backscatter and reflectance characteristics were analyzed using reference data collected during three field work campaigns and include in situ data and high resolution airborne photography. The optical data offered an acceptable initial accuracy for the land cover classification. The overall accuracy was increased by the combination of PolSAR and optical data and was up to 71% for unsupervised (Landsat 8 and TerraSAR-X) and up to 87% for supervised classification (Landsat 8 and Radarsat-2) for five tundra land cover types. The decomposition features of the dual and quad-polarized data showed a high sensitivity for the non-vegetated substrate (dominant surface scattering) and wetland vegetation (dominant double bounce and volume scattering). These classes had high potential to be automatically detected with unsupervised classification techniques.http://www.mdpi.com/2072-4292/6/9/8565arctictundraland coverclassificationpolarimetryradarPolSARSARTerraSAR-XRadarsat-2
collection DOAJ
language English
format Article
sources DOAJ
author Tobias Ullmann
Andreas Schmitt
Achim Roth
Jason Duffe
Stefan Dech
Hans-Wolfgang Hubberten
Roland Baumhauer
spellingShingle Tobias Ullmann
Andreas Schmitt
Achim Roth
Jason Duffe
Stefan Dech
Hans-Wolfgang Hubberten
Roland Baumhauer
Land Cover Characterization and Classification of Arctic Tundra Environments by Means of Polarized Synthetic Aperture X- and C-Band Radar (PolSAR) and Landsat 8 Multispectral Imagery — Richards Island, Canada
Remote Sensing
arctic
tundra
land cover
classification
polarimetry
radar
PolSAR
SAR
TerraSAR-X
Radarsat-2
author_facet Tobias Ullmann
Andreas Schmitt
Achim Roth
Jason Duffe
Stefan Dech
Hans-Wolfgang Hubberten
Roland Baumhauer
author_sort Tobias Ullmann
title Land Cover Characterization and Classification of Arctic Tundra Environments by Means of Polarized Synthetic Aperture X- and C-Band Radar (PolSAR) and Landsat 8 Multispectral Imagery — Richards Island, Canada
title_short Land Cover Characterization and Classification of Arctic Tundra Environments by Means of Polarized Synthetic Aperture X- and C-Band Radar (PolSAR) and Landsat 8 Multispectral Imagery — Richards Island, Canada
title_full Land Cover Characterization and Classification of Arctic Tundra Environments by Means of Polarized Synthetic Aperture X- and C-Band Radar (PolSAR) and Landsat 8 Multispectral Imagery — Richards Island, Canada
title_fullStr Land Cover Characterization and Classification of Arctic Tundra Environments by Means of Polarized Synthetic Aperture X- and C-Band Radar (PolSAR) and Landsat 8 Multispectral Imagery — Richards Island, Canada
title_full_unstemmed Land Cover Characterization and Classification of Arctic Tundra Environments by Means of Polarized Synthetic Aperture X- and C-Band Radar (PolSAR) and Landsat 8 Multispectral Imagery — Richards Island, Canada
title_sort land cover characterization and classification of arctic tundra environments by means of polarized synthetic aperture x- and c-band radar (polsar) and landsat 8 multispectral imagery — richards island, canada
publisher MDPI AG
series Remote Sensing
issn 2072-4292
publishDate 2014-09-01
description In this work the potential of polarimetric Synthetic Aperture Radar (PolSAR) data of dual-polarized TerraSAR-X (HH/VV) and quad-polarized Radarsat-2 was examined in combination with multispectral Landsat 8 data for unsupervised and supervised classification of tundra land cover types of Richards Island, Canada. The classification accuracies as well as the backscatter and reflectance characteristics were analyzed using reference data collected during three field work campaigns and include in situ data and high resolution airborne photography. The optical data offered an acceptable initial accuracy for the land cover classification. The overall accuracy was increased by the combination of PolSAR and optical data and was up to 71% for unsupervised (Landsat 8 and TerraSAR-X) and up to 87% for supervised classification (Landsat 8 and Radarsat-2) for five tundra land cover types. The decomposition features of the dual and quad-polarized data showed a high sensitivity for the non-vegetated substrate (dominant surface scattering) and wetland vegetation (dominant double bounce and volume scattering). These classes had high potential to be automatically detected with unsupervised classification techniques.
topic arctic
tundra
land cover
classification
polarimetry
radar
PolSAR
SAR
TerraSAR-X
Radarsat-2
url http://www.mdpi.com/2072-4292/6/9/8565
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