Develop and validate a modeling tool to detect and predict invasive plant infestations using GIS, GPS, and remote sensing data.
Identifying areas with existing weed infestations is important to land managers. These areas can be targeted for control in accordance with accepted best management practices. Predicting areas most at risk to future invasion is more precarious, but accurate prediction is an extremely powerful tool for land managers.

Adapt indicators of rangeland health to evaluation with geotechnologies.
Using guidelines established by USDI and USDA we evaluated the following indicators; 1) Bare ground, 2) presence and proportion of various plant functional/structural groups, 3) plant decadence, 4) litter, and 5) invasive plants. We used Landsat 7 ETM+ satellite imagery, high-spatial resolution multi-spectral imagery, SSURGO and STATSGO soils datasets, and field samples.

Remote Sensing of Aeolian Transport on the Snake River Plain, Idaho
Utilize and evaluate the ability of remote sensing systems to quantify and predict aeolian transport of soils after wildfires. The goals are to 1) quantify the amount of sediment flux, 2) compare rates and amounts of flux between vegetated and non-vegetated sites, 3) predict the amount of vegetation required to reduce sediment transport, and 4) assess the ability of LIDAR and high-resolution multispectral imagery to determine surficial changes from aeolian transport.

Use GIS to investigate the effects of land use/disturbance history on site invasibility.
Invasions of exotic plants into semiarid rangelands have resulted in substantial environmental and economic damage. This objective seeks to be able to identify proactive control methods by understanding the biological and ecological factors that lead to plant invasions.