Abstract With the progressive developments in digital humanities and smart city initiatives, there is a surging demand for the digitization of historical city maps, necessitating efficient and cost-effective georeferencing technologies. Existing methods often fall short in user-friendliness for non-technical personnel, highlighting the urgent need for low-barrier, batch processing solutions. This study proposes a framework for grouping modern urban maps based on cartographical characteristics, utilizing a manually constructed external reference grid system to generate conjugate Ground Control Points (GCPs) for batch georeferencing within these groups. Experimental results indicate that for urban maps at scales between 1:5,000 and 1:20,000, this method can maintain the root mean square error (RMSE) between 25.96 m and 66.25 m, significantly lower than errors associated with existing methods based on internal feature matching. By standardizing the construction of an external reference system, this approach effectively addresses the technical challenges associated with the lack of corresponding control points in unbuilt areas of historical urban planning maps. It provides a replicable batch georeferencing approach for non-technical users, significantly enhancing the efficiency of digitizing paper map archives and their precise temporal and spatial alignment with modern Geographic Information Systems (GIS).
Xu et al. (Sun,) studied this question.