Identifying the dynamics and extent of noxious weeds in a spatial and temporal context improves monitoring, planning, and management practices. Musk thistle (Carduus nutans L.), a noxious weed, is a good candidate for detection by remote sensing platforms because it may produce a unique spectral signature due to a large, purple-red flower head. Therefore, 3 remote sensing instruments—a ground hyperspectral spectrometer, a multispectral ground radiometer, and an airborne hyperspectral imaging spectrometer—were used to establish regression models between reflected data and the biophysical parameters (density, height, flower head density, and percent ground cover) of musk thistle. The coefficients of determination (R²) obtained from simple regression models for vegetation indices and musk thistle biophysical variables ranged from 0.46 to 0.77. Multiple regression models with up to 3 variables increased R² by an average of 0.07. This study indicated that normalized difference and simple ratio indices can be used for specific applications such as detection of musk thistle biophysical variables in rangelands. Once applied to the image, these results will produce a map of parameters that can be used to determine the size of infestation and the reduction in rangeland productivity.