Abstract

Historical map scans contain valuable information (e.g., historical locations of roads, buildings) enabling the analyses that require long-term historical data of the natural and built environment. Many online archives now provide public access to a large number of historical map scans, such as the historical USGS (United States Geological Survey) topographic archive and the historical Ordnance Survey maps in the United Kingdom. Efficiently extracting information from these map scans remains a challenging task, which is typically achieved by manually digitizing the map content. In computer vision, the process of detecting and extracting the precise locations of objects from images is called semantic segmentation. Semantic segmentation processes take an image as input and classify each pixel of the image to an object class of interest. Machine learning models for semantic segmentation have been progressing …

Date

September 22, 2025

Authors

Yao-Yi Chiang, Weiwei Duan, Stefan Leyk, Johannes H Uhl, Craig A Knoblock, Yao-Yi Chiang, Weiwei Duan, Stefan Leyk, Johannes H Uhl, Craig A Knoblock

Journal

Using historical maps in scientific studies: Applications, challenges, and best practices

Pages

65-98

Publisher

Springer International Publishing