New methods of image acquisition and analysis are advancing rangeland assessment techniques. Most image-analysis programs require users to adjust detection thresholds for color or object classification, a subjective process we postulated would be influenced by human error and variation. We developed a ground-cover–measurement calibration procedure, the digital grid overlay (DGO), which is similar to image point sampling (dot grid) advanced by earlier researchers. We asked 21 rangeland professionals to measure ground cover using 2 subjective visual-estimate methods (threshold adjustment process, or TAP, and external [to the software] visual estimate, or EVE) and the DGO on 5 different nadir-view images of rangeland. We also compared cover measurements made by DGO-calibrated software in automated batch processing against DGO manual-only measurements. We found an unacceptable range of variation among rangeland professionals using TAP. The DGO and EVE values were more closely aligned. We discovered an age-related bias in bare-ground measurements: all users over 50 years of age classified more bare ground than did all users under 50 years of age when using TAP. One explanation for this bias is age-related yellowing of the eye lens. Manual DGO measurements required up to 15 minutes per image compared to about 1 second per image for automated computer analysis after software calibration. The greatest bare-ground difference between the DGO-calibrated software and manual DGO measurements for the data sets analyzed was 5.6% and the correlations imply that reasonably accurate automated measurements can be used for bare-ground measurements from digital-image data sets. The exception is where the software cannot adequately separate litter and bare ground. The digital methods we tested need improvement. However, external calibration (DGO or EVE) of current-generation image-analysis algorithms bring economical, statistically adequate monitoring of extensive land areas within the realm of practical application.