AbstractThere is growing consensus that land degradation assessments should occur at local to regional scales, as global assessments fail to capture the complexity of land degradation processes, and how they manifest in different social‐ecological contexts. We have tested a statistically rigorous method for regional land degradation assessment in drylands, using fuzzy classification theory and techniques, that results in the creation of a habitat condition archetype for the Namaqualand Hardeveld bioregion of the Succulent Karoo biome in South Africa. The methodology initially groups field data into classes based on known indicators of land degradation, before predicting observed field cover with 16 remote sensing variables, derived from both LANDSAT 8 and SENTINEL‐2A satellite data. Using fuzzy classification techniques, projections of field cover from the resulting model are combined with variables representing a potential change in cover to produce a map of the habitat condition of the bioregion. Approximately 17% of the bioregion had habitat condition values less than one standard deviation smaller than the mean and could therefore be considered degraded. To provide context, this map is presented with potential drivers of change for the bioregion. The map, and accompanying drivers of change, is ultimately presented in a Google Earth Engine app for easy interpretation and use.