UNSUPERVISED WISHART CLASSFICATION OF WETLANDS IN NEWFOUNDLAND, CANADA USING POLSAR DATA BASED ON FISHER LINEAR DISCRIMINANT ANALYSIS
Polarimetric Synthetic Aperture Radar (PolSAR) imagery is a complex multi-dimensional dataset, which is an important source of information for various natural resources and environmental classification and monitoring applications. PolSAR imagery produces valuable information by observing scattering...
Published in: | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
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Language: | English |
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Copernicus Publications
2016
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Online Access: | https://doi.org/10.5194/isprs-archives-XLI-B7-305-2016 https://noa.gwlb.de/receive/cop_mods_00012164 https://noa.gwlb.de/servlets/MCRFileNodeServlet/cop_derivate_00012120/isprs-archives-XLI-B7-305-2016.pdf https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLI-B7/305/2016/isprs-archives-XLI-B7-305-2016.pdf |
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ftnonlinearchiv:oai:noa.gwlb.de:cop_mods_00012164 2023-05-15T17:21:54+02:00 UNSUPERVISED WISHART CLASSFICATION OF WETLANDS IN NEWFOUNDLAND, CANADA USING POLSAR DATA BASED ON FISHER LINEAR DISCRIMINANT ANALYSIS Mohammadimanesh, F. Salehi, B. Mahdianpari, M. Homayouni, S. 2016-06 electronic https://doi.org/10.5194/isprs-archives-XLI-B7-305-2016 https://noa.gwlb.de/receive/cop_mods_00012164 https://noa.gwlb.de/servlets/MCRFileNodeServlet/cop_derivate_00012120/isprs-archives-XLI-B7-305-2016.pdf https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLI-B7/305/2016/isprs-archives-XLI-B7-305-2016.pdf eng eng Copernicus Publications ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences -- http://www.isprs.org/publications/archives.aspx -- 2194-9034 https://doi.org/10.5194/isprs-archives-XLI-B7-305-2016 https://noa.gwlb.de/receive/cop_mods_00012164 https://noa.gwlb.de/servlets/MCRFileNodeServlet/cop_derivate_00012120/isprs-archives-XLI-B7-305-2016.pdf https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLI-B7/305/2016/isprs-archives-XLI-B7-305-2016.pdf uneingeschränkt info:eu-repo/semantics/openAccess article Verlagsveröffentlichung article Text doc-type:article 2016 ftnonlinearchiv https://doi.org/10.5194/isprs-archives-XLI-B7-305-2016 2022-02-08T22:56:13Z Polarimetric Synthetic Aperture Radar (PolSAR) imagery is a complex multi-dimensional dataset, which is an important source of information for various natural resources and environmental classification and monitoring applications. PolSAR imagery produces valuable information by observing scattering mechanisms from different natural and man-made objects. Land cover mapping using PolSAR data classification is one of the most important applications of SAR remote sensing earth observations, which have gained increasing attention in the recent years. However, one of the most challenging aspects of classification is selecting features with maximum discrimination capability. To address this challenge, a statistical approach based on the Fisher Linear Discriminant Analysis (FLDA) and the incorporation of physical interpretation of PolSAR data into classification is proposed in this paper. After pre-processing of PolSAR data, including the speckle reduction, the H/α classification is used in order to classify the basic scattering mechanisms. Then, a new method for feature weighting, based on the fusion of FLDA and physical interpretation, is implemented. This method proves to increase the classification accuracy as well as increasing between-class discrimination in the final Wishart classification. The proposed method was applied to a full polarimetric C-band RADARSAT-2 data set from Avalon area, Newfoundland and Labrador, Canada. This imagery has been acquired in June 2015, and covers various types of wetlands including bogs, fens, marshes and shallow water. The results were compared with the standard Wishart classification, and an improvement of about 20% was achieved in the overall accuracy. This method provides an opportunity for operational wetland classification in northern latitude with high accuracy using only SAR polarimetric data. Article in Journal/Newspaper Newfoundland Niedersächsisches Online-Archiv NOA Canada Newfoundland The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B7 305 310 |
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ftnonlinearchiv |
language |
English |
topic |
article Verlagsveröffentlichung |
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article Verlagsveröffentlichung Mohammadimanesh, F. Salehi, B. Mahdianpari, M. Homayouni, S. UNSUPERVISED WISHART CLASSFICATION OF WETLANDS IN NEWFOUNDLAND, CANADA USING POLSAR DATA BASED ON FISHER LINEAR DISCRIMINANT ANALYSIS |
topic_facet |
article Verlagsveröffentlichung |
description |
Polarimetric Synthetic Aperture Radar (PolSAR) imagery is a complex multi-dimensional dataset, which is an important source of information for various natural resources and environmental classification and monitoring applications. PolSAR imagery produces valuable information by observing scattering mechanisms from different natural and man-made objects. Land cover mapping using PolSAR data classification is one of the most important applications of SAR remote sensing earth observations, which have gained increasing attention in the recent years. However, one of the most challenging aspects of classification is selecting features with maximum discrimination capability. To address this challenge, a statistical approach based on the Fisher Linear Discriminant Analysis (FLDA) and the incorporation of physical interpretation of PolSAR data into classification is proposed in this paper. After pre-processing of PolSAR data, including the speckle reduction, the H/α classification is used in order to classify the basic scattering mechanisms. Then, a new method for feature weighting, based on the fusion of FLDA and physical interpretation, is implemented. This method proves to increase the classification accuracy as well as increasing between-class discrimination in the final Wishart classification. The proposed method was applied to a full polarimetric C-band RADARSAT-2 data set from Avalon area, Newfoundland and Labrador, Canada. This imagery has been acquired in June 2015, and covers various types of wetlands including bogs, fens, marshes and shallow water. The results were compared with the standard Wishart classification, and an improvement of about 20% was achieved in the overall accuracy. This method provides an opportunity for operational wetland classification in northern latitude with high accuracy using only SAR polarimetric data. |
format |
Article in Journal/Newspaper |
author |
Mohammadimanesh, F. Salehi, B. Mahdianpari, M. Homayouni, S. |
author_facet |
Mohammadimanesh, F. Salehi, B. Mahdianpari, M. Homayouni, S. |
author_sort |
Mohammadimanesh, F. |
title |
UNSUPERVISED WISHART CLASSFICATION OF WETLANDS IN NEWFOUNDLAND, CANADA USING POLSAR DATA BASED ON FISHER LINEAR DISCRIMINANT ANALYSIS |
title_short |
UNSUPERVISED WISHART CLASSFICATION OF WETLANDS IN NEWFOUNDLAND, CANADA USING POLSAR DATA BASED ON FISHER LINEAR DISCRIMINANT ANALYSIS |
title_full |
UNSUPERVISED WISHART CLASSFICATION OF WETLANDS IN NEWFOUNDLAND, CANADA USING POLSAR DATA BASED ON FISHER LINEAR DISCRIMINANT ANALYSIS |
title_fullStr |
UNSUPERVISED WISHART CLASSFICATION OF WETLANDS IN NEWFOUNDLAND, CANADA USING POLSAR DATA BASED ON FISHER LINEAR DISCRIMINANT ANALYSIS |
title_full_unstemmed |
UNSUPERVISED WISHART CLASSFICATION OF WETLANDS IN NEWFOUNDLAND, CANADA USING POLSAR DATA BASED ON FISHER LINEAR DISCRIMINANT ANALYSIS |
title_sort |
unsupervised wishart classfication of wetlands in newfoundland, canada using polsar data based on fisher linear discriminant analysis |
publisher |
Copernicus Publications |
publishDate |
2016 |
url |
https://doi.org/10.5194/isprs-archives-XLI-B7-305-2016 https://noa.gwlb.de/receive/cop_mods_00012164 https://noa.gwlb.de/servlets/MCRFileNodeServlet/cop_derivate_00012120/isprs-archives-XLI-B7-305-2016.pdf https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLI-B7/305/2016/isprs-archives-XLI-B7-305-2016.pdf |
geographic |
Canada Newfoundland |
geographic_facet |
Canada Newfoundland |
genre |
Newfoundland |
genre_facet |
Newfoundland |
op_relation |
ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences -- http://www.isprs.org/publications/archives.aspx -- 2194-9034 https://doi.org/10.5194/isprs-archives-XLI-B7-305-2016 https://noa.gwlb.de/receive/cop_mods_00012164 https://noa.gwlb.de/servlets/MCRFileNodeServlet/cop_derivate_00012120/isprs-archives-XLI-B7-305-2016.pdf https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLI-B7/305/2016/isprs-archives-XLI-B7-305-2016.pdf |
op_rights |
uneingeschränkt info:eu-repo/semantics/openAccess |
op_doi |
https://doi.org/10.5194/isprs-archives-XLI-B7-305-2016 |
container_title |
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
container_volume |
XLI-B7 |
container_start_page |
305 |
op_container_end_page |
310 |
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1766107899327676416 |