Performance evaluation of supervised change detection tool on DubaiSat-2 multispectral and pansharp images

Hessa R. Almatroushi

doi:10.1117/12.2067008

23 October 2014 Performance evaluation of supervised change detection tool on DubaiSat-2 multispectral and pansharp images

Hessa R. Almatroushi

Author Affiliations +

Proceedings Volume 9244, Image and Signal Processing for Remote Sensing XX; 92441Y (2014) https://doi.org/10.1117/12.2067008
Event: SPIE Remote Sensing, 2014, Amsterdam, Netherlands

Abstract

Supervised Change Detection Tool (SCDT) is an in-house developed tool in Emirates Institution for Advanced Science and Technology (EIAST). The developed tool is based on Algebra Change Detection algorithm and multi-class Support Vector Machine classifier and is capable of highlighting the areas of change, describing them, and discarding any falsedetections that result from shadow. Further, it can collect the analysis results, which include the change of class an area went through and the overall change percentage of each class defined, in a Microsoft Word document automatically. This paper evaluates the performance of the SCDT, which was initially developed for DubaiSat-1 multispectral images, on DubaiSat-2 multispectral and pansharp images. Moreover, it compares its performance opposed to Change Detection Analysis (i.e. Post-Classification) in ENVI.

Citation Download Citation

Hessa R. Almatroushi, Hessa R. Almatroushi, "Performance evaluation of supervised change detection tool on DubaiSat-2 multispectral and pansharp images", Proc. SPIE 9244, Image and Signal Processing for Remote Sensing XX, 92441Y (23 October 2014); doi: 10.1117/12.2067008; https://doi.org/10.1117/12.2067008

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