Ecological data obtained from field-based plots can provide researchers with detailed information about ecosystem structure and function.  However, these data typically represent processes that occur over small spatial areas and short time scales.  Accordingly, it is difficult to extrapolate these data to patterns and processes that take place at regional scales or over several years.  Satellite-derived imagery can provide a means to explore environmental variables at broad scales.  The main objective of this study was to conduct a landscape-scale ecological assessment of a rapidly-developing area of West Georgia, in order to assess indicators of ecosystem health and detect multi-temporal changes in the area.  Indicator variables included in the assessment were: population density and change, road density, proportion of stream that has roads within 30 meters, proportion of area that has agriculture on slopes >3%, proportion of stream with adjacent agriculture, proportion of stream with adjacent forest cover, percent forest land cover, forest patch density, and Shannon's Diversity Index.  Cluster analysis was used to combine these indicator variables into different groups.  Cluster means were then used to rank different areas of the four-county region according to relative cumulative ecological impact.  Our results indicate that landscape variables are highly correlated to field measurements, and areas observed to have greater adverse impact scores corroborate the findings from our plot-level forest condition assessments.  These findings suggest that satellite imagery can be used to accurately predict areas of adverse ecological impact and could be used to monitor forest health in a time- and cost-efficient manner.