Abstract

1 Historical maps capture past landscapes' natural and anthropogenic features, with geohistorical data from periods before the 1970s (before the Landsat program's launch) primarily found, barring a few exceptions, only on printed map sheets. In the past decade, numerous maps have been digitized and made publicly accessible. This chapter overviews cutting-edge AI methods and systems for processing historical maps to generate valuable data, insights, and knowledge. Individual sections highlight our recently published research findings across various domains, including the semantic web, big data, data mining, machine learning, document understanding, natural language processing, remote sensing, and geographic information systems. 1 Contact: Yao-Yi Chiang. Email: [email protected]. All other authors are listed in alphabetical order.

Date

January 1, 2023

Authors

Yao-Yi Chiang, Muhao Chen, Weiwei Duan, Jina Kim, Craig A Knoblock, Stefan Leyk, Zekun Li, Yijun Lin, Min Namgung, Basel Shbita, Johannes H Uhl

Book

Handbook of Geospatial Artificial Intelligence

Pages

217-247

Publisher

CRC Press