Kalkhan, M.A., T.J. Stohlgren, G.W. Chong, L.D. Schell, and R.M. Reich. 2001. A predictive spatial model of plant diversity: integration of remotely sensed data, GIS, and spatial statistics. Remote Sensing and Geospatial Technologies for the New Millennium, Proccedings of the 8th Forest Service Remote Sensing Applications Conference, (available on CD-Rom). The paper details a new, powerful predictive model for invasive plant species or hot spots of biodiversity, based on field data, remotely sensed data, and spatial statistics. Biological and environmental data are merged with trend surface analysis, kriging, and co-kriging spatial models to provide land managers with maps of invasive species. This will greatly facilitate control and restoration activities. The study site was Rocky Mountain National Park, Colorado, but the same models would work for most invasive species.
For more information contact: Tom Stohlgren
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