Lost cities refer to historical or ancient settlements that have been abandoned, obscured by natural processes, or forgotten over time, and subsequently rediscovered through archaeological and geospatial investigation. As a GIS use case, this domain involves integrating multidisciplinary geospatial data sources — including satellite imagery, LiDAR point clouds, aerial photography, and historical cartographic records — to detect, map, and analyze subsurface and surface archaeological features that indicate prior human occupation.

GIS technology enables analysts to perform advanced spatial analysis workflows such as terrain modeling, remote sensing classification, and predictive site modeling to identify anomalies consistent with buried structures, road networks, agricultural systems, and settlement patterns. Platforms like ArcGIS and QGIS support the overlay of multispectral datasets with elevation models, allowing practitioners to isolate anthropogenic signatures obscured by dense vegetation or sediment accumulation.

The practical benefits include accelerating archaeological discovery, reducing invasive excavation through non-destructive survey methodologies, and preserving cultural heritage through accurate digital documentation. This use case demonstrates GIS's critical role in synthesizing complex geospatial datasets to reconstruct historical landscapes and inform evidence-based heritage management decisions.