The 2008 Joint Meeting of the Society for Range Management and the America Forage and Grassland Council. |
Wednesday, January 30, 2008
26
Testing the Weed Invasion Susceptibility Prediction (WISP) Model for Leafy Spurge using Hyperspectral Remote Sensing
E. Raymond Hunt Jr.1, John Gillham2, and Randy Hamilton2. (1) Hydrology and Remote Sensing Laboratory, USDA-ARS, Bldg 007, Room 104, BARC-West, 10300 Baltimore Ave, Beltsville, MD 20705, (2) Remote Sensing Applications Center, USDA Forest Service, 2222 W. 2300 South, Salt Lake City, UT 84119
Leafy spurge (Euphorbia esula L.) is a noxious invasive weed that infests over 1.2 million hectares of land in North America. One of the fundamental needs in leafy spurge management is cost-effective, large-scale, and long-term documentation and monitoring of plant populations. Leafy spurge is a good candidate for detection via remote sensing because the distinctive yellow-green color of its bracts is spectrally unique when compared to co-occurring green vegetation. During 1999, Airborne Visible-Infrared Imaging Spectrometer (AVIRIS) imagery were acquired in northeastern Wyoming and ground vegetation data were collected nearby Devils Tower National Monument in Crook County , Wyoming . Hyperspectral analyses were used to classify leafy spurge presence/absence; overall accuracy using the spectral angle mapper was 76%. The classification data were used to test the Weed Invasion Susceptibility Prediction (WISP) model, which uses available geospatial data layers to predict the potential distribution of various invasive weeds. We tested the WISP model at two new locations, Fishlake National Forest in Utah and the South Unit of Theodore Roosevelt National Park in North Dakota. Both sites had model predictions significantly better than chance using kappa analyses. Future applications of the WISP model may be incorporation into decision support systems.