A method for unsupervised change detection and automatic radiometric normalization in multispectral data

Allan Aasbjerg Nielsen, Morton John Canty

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Abstract

Based on canonical correlation analysis the iteratively re-weighted multivariate alteration detection (MAD) method is used to successfully perform unsupervised change detection in bi-temporal Landsat ETM+ images covering an area with villages, woods, agricultural fields and open pit mines in North Rhine- Westphalia, Germany. A link to an example with ASTER data to detect change with the same method after the 2005 Kashmir earthquake is given. The method is also used to automatically normalize multitemporal, multispectral Landsat ETM+ data radiometrically. IDL/ENVI, Python and Matlab software to carry out the analyses is available from the authors' websites.
Original languageEnglish
Title of host publication34th International Symposium on Remote Sensing of Environment : The GEOSS Era: Towards Operational Environmental Monitoring
Number of pages4
PublisherInternational Society for Photogrammetry and Remote Sensing
Publication date2011
Publication statusPublished - 2011
Event34th International Symposium on Remote Sensing of Environment (ISRSE2011) - Sydney Convention & Exhibition Centre , Sydney, Australia
Duration: 10 Apr 201115 Apr 2011
Conference number: 34

Conference

Conference34th International Symposium on Remote Sensing of Environment (ISRSE2011)
Number34
LocationSydney Convention & Exhibition Centre
Country/TerritoryAustralia
CitySydney
Period10/04/201115/04/2011

Keywords

  • Computer software
  • Environmental engineering
  • MATLAB
  • Remote sensing
  • Signal detection
  • Iterative methods

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