GeoAI for the Digitization of Historical Maps

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

Research output: Chapter in Book/Report/Conference proceedingChapter

1 Scopus citations

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.

Original languageEnglish (US)
Title of host publicationHandbook of Geospatial Artificial Intelligence
PublisherCRC Press
Pages217-247
Number of pages31
ISBN (Electronic)9781003814924
ISBN (Print)9781032311661
DOIs
StatePublished - Jan 1 2023

Bibliographical note

Publisher Copyright:
© 2024 selection and editorial matter, Song Gao, Yingjie Hu, and Wenwen Li; individual chapters, the contributors.

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