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Change detection thresholds for remotely sensed images

Author

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  • Peter A. Rogerson

    (Department of Geography, University at Buffalo, Wilkeson Hall, Buffalo, NY 14261, USA)

Abstract

. The detection of change in remotely sensed images is often carried out by designating a threshold to distinguish between areas of change and areas of no change. The choice of threshold is often arbitrary however. The purpose of this paper is to offer a statistical framework for the selection of thresholds. The framework accounts for the facts that one carries out multiple tests of the null hypothesis of no change, when searching for regions of change over an image with a large number of pixels. Special attention is given to global spatial autocorrelation, which can affect the selection of appropriate threshold values.

Suggested Citation

  • Peter A. Rogerson, 2002. "Change detection thresholds for remotely sensed images," Journal of Geographical Systems, Springer, vol. 4(1), pages 85-97, March.
    • Handle: RePEc:kap:jgeosy:v:4:y:2002:i:1:d:10.1007_s101090100076
    DOI: 10.1007/s101090100076
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    Cited by:

    1. Barry Boots & Ferko Csillag, 2006. "Categorical maps, comparisons, and confidence," Journal of Geographical Systems, Springer, vol. 8(2), pages 109-118, July.
    2. Wulder, Michael A. & White, Joanne C. & Coops, Nicholas C. & Nelson, Trisalyn & Boots, Barry, 2007. "Using local spatial autocorrelation to compare outputs from a forest growth model," Ecological Modelling, Elsevier, vol. 209(2), pages 264-276.

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