The distribution and abundance of flowering leafy spurge (Euphorbia esula L.) can be determined with hyperspectral remote sensing, but the availability of hyperspectral sensors is limited. Hence, the Landsat 7 Enhanced Thematic Mapper Plus (ETM ) and System Pour d'Observation de la Terre (SPOT) 4 imagery were acquired to test the ability of these sensors to detect leafy spurge. The green:red band ratio was the vegetation index with the highest correlations to flowering leafy spurge cover, but the correlations were weak and not useful for predictions. With Airborne Visible Infrared Imaging Spectrometer (AVIRIS) data, the green:red band ratio was also weakly correlated to flowering leafy spurge cover, although the output from a hyperspectral unmixing algorithm was highly correlated with cover using the same data, indicating simple indices have limited power for detecting leafy spurge. Canopy reflectance modeling using the Scattering by Arbitrarily Inclined Leaves (SAIL) model suggests the weak correlations were caused by variations in leaf area index. It is important to develop spectral libraries in order to use canopy reflectance simulation models that can reduce the time and effort of remote sensing analysis for detecting leafy spurge and other invasive weeds.