Consistency is an essential aspect of the quality of metadata. Inconsistent metadata records are harmful: given a themed query, the set of retrieved metadata records would contain descriptions of unrelated or irrelevant resources, and may even not contain some resources considered obvious. This is even worse when the description of the location is inconsistent. Inconsistent spatial descriptions may yield invisible or hidden geographical resources that cannot be retrieved by means of spatially themed queries. Therefore, ensuring spatial consistency should be a primary goal when reusing, sharing and developing georeferenced digital collections. We present a methodology able to detect geospatial inconsistencies in metadata collections based on the combination of spatial ranking, reverse geocoding, geographic knowledge organization systems and information-retrieval techniques. This methodology has been applied to a collection of metadata records describing maps and atlases belonging to the Library of Congress. The proposed approach was able to automatically identify inconsistent metadata records (870 out of 10,575) and propose fixes to most of them (91.5%) These results support the ability of the proposed methodology to assess the impact of spatial inconsistency in the retrievability and visibility of metadata records and improve their spatial consistency.