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IGARSS
2010

Geospatiotemporal data mining in an early warning system for forest threats in the United States

10 years 9 months ago
Geospatiotemporal data mining in an early warning system for forest threats in the United States
We investigate the potential of geospatiotemporal data mining of multi-year land surface phenology data (250 m Normalized Difference Vegetation Index (NDVI) values derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) in this study) for the conterminous United States as part of an early warning system to identify threats to forest ecosystems. Cluster analysis of this massive data set, using high-performance computing, provides a basis for several possible approaches to defining the bounds of "normal" phenological patterns, indicating healthy vegetation in a given geographic location. We demonstrate the applicability of such an approach, using it to identify areas in Colorado, USA, where an ongoing mountain pine beetle outbreak has caused significant tree mortality.
Forrest M. Hoffman, Richard Tran Mills, Jitendra K
Added 13 Feb 2011
Updated 13 Feb 2011
Type Journal
Year 2010
Where IGARSS
Authors Forrest M. Hoffman, Richard Tran Mills, Jitendra Kumar, Srinivasa S. Vulli, William W. Hargrove
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