AI-Supported Smart Search for Multi-Period Historical Maps Using the mapKurator Place Name Index
Year: 2025
Type: article
Abstract: Placenames, which link maps to historical records are vital for understanding spatiotemporal societal changes. Traditional workflows require scanned historical maps to be georeferenced before publishing in GIS-readable formats or web map services. Querying, however, typically remains limited to layer metadata, hindering historical placename identification across periods. This paper presents a complete pipeline that integrates batched placename extraction and large language models (LLMs) to enable smart spatial search. Using mapKurator, we batch-extracted text from 20th-century Web Map Tile Service format maps with simultaneous geolocation capture. Indexed placenames were stored in an Elasticsearch database integrated with OpenAI’s LLMs to extract spatiotemporal information from free-text user queries. An elastic, fuzzy-search engine retrieved relevant results exportable for GIS applications. By merging LLMs with mapKurator, a smart spatial search system was developed that efficiently compiles, visualizes, and overlays historical map layers on a Web GIS platform, significantly enhancing the searchability and analysis of historical maps.
Authors: Pi-Ling Pai, Hsiang-Hsi Lu, Wen-Rong Su, Hsiung-Ming Liao, Ta-Chien Chan, Yijun Lin, Yao-Yi Chiang
Language: English
Subfield: Geography, Planning and Development
Field: Social Sciences
Domain: Social Sciences
Open Access status: hybrid
Funder: Academia Sinica
OpenAlex ID: W4416415565