Resource managers realize the potential of remote sensing and geographic information system (GIS) operations for detecting, monitoring, mapping, and modeling distributions of invasive plants. However, to make wise decisions, imagery must be evaluated in terms of geometric fidelity, spatial resolution, spectral resolution, area coverage, and cost. These data characteristics are discussed relative to mapping vegetation distributions and detecting exotic plants. Examples are drawn from projects conducted during the past 20 yr by the Department of Geography's Center for Remote Sensing and Mapping Science at the University of Georgia using remotely sensed data, GIS, and Global Positioning System techniques to produce detailed vegetation maps and databases for study areas in the southeastern United States. Many of these projects include a component of invasive plant detection and distribution mapping for monitoring spread and effectiveness of control.

Additional index words: Hyperspectral image data, national parks, natural resource management, photo interpretation, satellite imagery.

Abbreviations: ASTER, Advanced Spaceborne Thermal Emission and Relection Radiometer; AVHRR, Advanced Very High Resolution Radiometer; AVIRIS, Airborne Visible/Infrared Imaging Spectrometer; CIR, color infrared; DMC, Digital Modular Camera; GIS, geographic information system; GPS, Global Positioning System; GR, ground resolution; LIDAR, light detection and ranging; lprs/mm, line pairs per millimeter; MODIS, Moderate Resolution Imaging Spectroradiometer; PAN, panchromatic; SPOT, System Probatoire d'Observation de la Terre; USGS, United States Geological Survey; XS, multispectral.