Remote sensing has long been recognized as a rapid, inexpensive, nondestructive, and synoptic technique to study rangeland vegetation and soils. With respect to the worldwide phenomenon of woody plant invasion on many grasslands and rangelands, there is increasing interest in accurate and cost-effective quantification of woody plant cover and distribution over large land areas. Our objectives were to 1) investigate the relationship between ground-measured and image-classified honey mesquite (Prosopis glandulosa Torr.) canopy cover at three sites in north Texas using high spatial resolution (0.67-m) aerial images, and 2) examine the suitability of aerial images with different spatial resolutions (0.67-m, 1-m, and 2-m) for accurate estimation of mesquite canopy cover. The line intercept method and supervised maximum likelihood classifier were used to measure mesquite cover on the ground and on images, respectively. Images all were taken in September when mesquite foliage was photosynthetically active and most herbaceous vegetation was dormant. The results indicated that there were robust agreements between classified and ground-measured mesquite cover at all three sites with the coefficients of determination (r²) ≥ 0.95. Accuracy of lower spatial resolution images ranged from r²  =  0.89–0.93, with the 2-m spatial resolution image on one of the sites at r²  =  0.89. For all sites, the overall, producer's, and user's accuracies, and kappa statistics were 92% and 97%, 91% and 99%, 85% and 96%, and 0.82 and 0.95 for 2-m and 0.67-m spatial resolution images, respectively. Results showed that images at all three spatial resolution levels were effective for estimating mesquite cover over large and remote or inaccessible areas.