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Multitemporal RADARSAT-2 Polarimetric SAR Data for Urban Land-Cover Mapping
KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geodesy and Geoinformatics. (Geoinformatics)
KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geodesy and Geoinformatics. (Geoinformatics)
2010 (English)In: Proceedings of SPIE - The International Society for Optical Engineering, Bellingham: SPIE-INT SOC OPTICAL ENGINEERING , 2010, Vol. 7841Conference paper, Published paper (Refereed)
Abstract [en]

The objective of this research is to evaluate the performance of multitemporal RADARSAT-2 polarimetric SAR data for urban land use/land-cover classification. Three dates of RADARSAT-2 polarimetric SAR data were acquired during the summer of 2008 over the rural-urban fringe of the Greater Toronto Area. The major land-cover types are residential areas, industry areas, bare land, golf courses, forest, and agricultural crops. The methodology used in this study follow the manner that first extracting the features and then carrying out the supervised classification taking the different feature combinations as an input. Support vectors machine is selected to be the classifier. SAR features including amplitude, intensity, long-term coherence, Freeman-Durden decomposition are extracted and compared by evaluating the classification abilities. Long-term coherence plays an important role in building discrimination in this study. The best classification results achieved by using the three dates HH, VH, HV amplitude layers and the coherence map. The overall accuracy is 82.3%. The results indicate that RADARSAT-2 polarimetric data has a potential to urban land-cover classification with the proper feature combinations.

Place, publisher, year, edition, pages
Bellingham: SPIE-INT SOC OPTICAL ENGINEERING , 2010. Vol. 7841
Series
Proceedings of SPIE-The International Society for Optical Engineering, ISSN 0277-786X
Keyword [en]
RADARSAT-2, polarimetric, classification, urban, coherence
National Category
Remote Sensing
Identifiers
URN: urn:nbn:se:kth:diva-32129DOI: 10.1117/12.873218ISI: 000287764600022Scopus ID: 2-s2.0-78650352225ISBN: 978-0-8194-8364-5 (print)OAI: oai:DiVA.org:kth-32129DiVA: diva2:409319
Conference
6th International Symposium on Digital Earth: Data Processing and Applications; Beijing; China 9 September 2009 through 12 September 2009
Note

QC 20150713

Available from: 2011-04-07 Created: 2011-04-07 Last updated: 2015-07-13Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
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Output format
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