A comparative study of algorithms for land cover change

Shyam Boriah, Varun Mithal, Ashish Garg, Vipin Kumar, Michael Steinbach, Chris Potter, Steve Klooster

Research output: Chapter in Book/Report/Conference proceedingConference contribution

10 Scopus citations

Abstract

Ecosystem-related observations from remote sensors on satellites offer huge potential for understanding the location and extent of global land cover change. This paper presents a comparative study of three time series based algorithms for detecting changes in land cover. The techniques are evaluated quantitatively using forest fire ground truth from the state of California for 2000-2009. On relatively high quality data sets, all three schemes perform reasonably well, but their ability to handle noise and natural variability in the vegetation data differs dramatically. In particular, one of the algorithms significantly outperforms the other two since it accounts for variability in the time series.

Original languageEnglish (US)
Title of host publicationProceedings of the 2010 Conference on Intelligent Data Understanding, CIDU 2010
Pages175-188
Number of pages14
StatePublished - Dec 1 2010
EventNASA Conference on Intelligent Data Understanding, CIDU 2010 - Mountain View, CA, United States
Duration: Oct 5 2010Oct 6 2010

Other

OtherNASA Conference on Intelligent Data Understanding, CIDU 2010
CountryUnited States
CityMountain View, CA
Period10/5/1010/6/10

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