In support of the Texas Seagrass Monitoring Program, remote sensing research is underway to evaluate automated methods for monitoring landscape changes in seagrass beds related to human and/or natural disturbances. This paper discusses the integration of high resolution aerial color film photography, color space transformation, pixel threshold models, and geographic information system technology to detect, assess, and monitor 1-m ground feature changes and disturbance areas within a Texas, United States, shallow seagrass bed over 3 site years. The procedure entails transforming digitized, aerial color film transparencies from red, green, and blue color space to intensity, hue, and saturation color space; analyzing the saturation and/or intensity imagery and their histograms to identify bare areas; and developing threshold models to separate bare areas from vegetated areas employing the results obtained in the previous step. Maps created with this semiautomated approach had classification accuracies ranging from 75% to 100%. We used geographic information system tools to quantify landscape feature changes occurring at the shallow test site for 3 consecutive years. The overall findings indicate that the semiautomated approach described in this study can be used as an efficient protocol to accurately map changes in bare and vegetated areas within this Texas seagrass bed, and suggest that the techniques would have high potential for other similar seagrass areas.