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GIS
2008
ACM

Data mining for visual exploration and detection of ecosystem disturbances

14 years 10 months ago
Data mining for visual exploration and detection of ecosystem disturbances
This paper presents a case study on the application of data mining to the problem of detecting ecosystem disturbances from vegetation cover data obtained from satellite observations. We describe two anomaly detection approaches--moving average and random walk--for detecting such events. We also illustrate how clustering can be used to locate similar incidents of disturbance events. Finally, we present a clustering-based framework to aid the visual exploration of ecosystem disturbances from high resolution data.
Haibin Cheng, Pang-Ning Tan, Christopher Potter, S
Added 09 Nov 2009
Updated 09 Nov 2009
Type Conference
Year 2008
Where GIS
Authors Haibin Cheng, Pang-Ning Tan, Christopher Potter, Steven A. Klooster
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