GeoAI: spatially explicit artificial intelligence techniques for geographic knowledge discovery and beyond

Janowicz, Krzysztof; Gao, Song; McKenzie, Grant; Hu, Yingjie; Bhaduri, Budhendra

doi:10.1080/13658816.2019.1684500

Title: GeoAI: spatially explicit artificial intelligence techniques for geographic knowledge discovery and beyond

Journal Article · Wed Oct 30 00:00:00 EDT 2019 · International Journal of Geographical Information Science

DOI:https://doi.org/10.1080/13658816.2019.1684500· OSTI ID:1619012

Janowicz, Krzysztof ^[1];

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Univ. of California, Santa Barbara, CA (United States)
Univ. of Wisconsin, Madison, WI (United States)
McGill Univ., Montreal, QC (Canada)
Univ. at Buffalo, NY (United States)
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

Recent progress in Artificial Intelligence (AI) techniques, the large-scale availability of high-quality data, as well as advances in both hardware and software to efficiently process these data, are transforming a range of fields from computer vision and natural language processing to autonomous driving and healthcare. For example, the availability of high-resolution geographic data and high-performance computing techniques together with deep learning fuel progress in fast and accurate object detection. Recent examples of GeoAI work include the detections of terrain features and densely-distributed building footprints, information extraction from scanned historical maps, semantic classification (e.g. LiDAR point clouds), novel methods for spatial interpolation, and advances in traffic forecasting. Similarly, machine learning and natural language processing are facilitating the extraction of geographic information from unstructured (textual) data, such as news articles and Wikipedia as well as the matching of natural features in multiple gazetteers.

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Research Organization:: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)

Sponsoring Organization:: USDOE; National Science Foundation (NSF); Natural Sciences and Engineering Research Council of Canada (NSERC); Wisconsin Alumni Research Foundation

Grant/Contract Number:: AC05-00OR22725; 1936677; 1940091

OSTI ID:: 1619012

Journal Information:: International Journal of Geographical Information Science, Vol. 34, Issue 4; ISSN 1365-8816

Publisher:: Informa UK LimitedCopyright Statement

Country of Publication:: United States

Language:: English

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Cited by: 72 works

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