document: Land cover change detection : a case study The study of land cover change is an important problem in the Earth Science domain because of its impacts on local climate , radiation balance , biogeochemistry , hydrology , and the diversity and abundance of terrestrial species . Most well-known change detection techniques from statistics , signal processing and control theory are not well-suited for the massive high-dimensional spatio-temporal data sets from Earth Science due to limitations such as high computational complexity and the inability to take advantage of seasonality and spatio-temporal autocorrelation inherent in Earth Science data . In our work , we seek to address these challenges with new change detection techniques that are based on data mining approaches . Specifically , in this paper we have performed a case study for a new change detection technique for the land cover change detection problem . We study land cover change in the state of California , focusing on the San Francisco Bay Area and perform an extended study on the entire state . We also perform a comparative evaluation on forests in the entire state . These results demonstrate the utility of data mining techniques for the land cover change detection problem .
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