AbstractThe economic development activities of an increasing world population threaten the assimilative capacity of our environment and have stimulated interest in the concept of environmental carrying capacity. While the pace of land transformations has encouraged the refinement of information technologies such as satellite remote sensing to provide a synoptic view of earth‐system processes, the volume of information these systems generate and the high level of expertise required to translate these data retard effective and timely land‐management decision making. This paper introduces a methodology that employs an artificial neural network trained to recognize categories of population support capacity from satellite data acquired from the NOAA‐AVHRR. The network, functioning as an ‘intelligent’ mapping tool, achieved a classification accuracy of 77.5 per cent for the study site and points to the potential role a model of this type may play in land degradation m