GeoAI in Social Science
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Abstract (arXiv)
GeoAI, or geospatial artificial intelligence, is an exciting new area that leverages artificial intelligence (AI), geospatial big data, and massive computing power to solve problems with high automation and intelligence. This paper reviews the progress of AI in social science research, highlighting important advancements in using GeoAI to fill critical data and knowledge gaps. It also discusses the importance of breaking down data silos, accelerating convergence among GeoAI research methods, as well as moving GeoAI beyond geospatial benefits.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 7 of its 54 references that are in the map. First posted on arXiv 19 Dec 2023.
Builds on
7 of 54 references.
References · 7
- 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,713
- 2015Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networkscited by 9,639
- 2017Graph Embedding Techniques, Applications, and Performance: A Surveycited by 188
- 2017Using Deep Learning and Google Street View to Estimate the Demographic Makeup of the UScited by 66
- 2017Aerial Vehicle Tracking by Adaptive Fusion of Hyperspectral Likelihood Mapscited by 13
- 2018Where to Go Next: A Spatio-temporal LSTM model for Next POI Recommendationcited by 6
- 2021Learning from Counting: Leveraging Temporal Classification for Weakly Supervised Object Localization and Detectioncited by 5
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