The DOI matches its Crossref record; 51 of the 51 references it cites were found in a registry or an index.
GeoAI: spatially explicit artificial intelligence techniques for geographic knowledge discovery and beyond
Open accessAbstract
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, a...
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Cites
ImageNet: A large-scale hierarchical image database
Deng, J., Dong, W., Socher, R., Li, L.-J., Li, K., & Fei-Fei, L. (2009) · 2009 IEEE Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2009.5206848 · Cited by 65,333
GAN（Generative Adversarial Nets）
(2017) · Journal of Japan Society for Fuzzy Theory and Intelligent Informatics · doi:10.3156/jsoft.29.5_177_2 · Cited by 19,270
The Fourth Paradigm – Data-Intensive Scientific Discovery
Hey, T. (2012) · Communications in Computer and Information Science · doi:10.1007/978-3-642-33299-9_1 · Cited by 1,585
The Fourth Paradigm: Data-Intensive Scientific Discovery
Buchan, I. E., Winn, J. M., & Bishop, C. (2009) · Cited by 1,439
(2017) · International Conference on Learning Representations · Cited by 1,075
Deep learning for short-term traffic flow prediction
Polson, N. G., & Sokolov, V. O. (2017) · Transportation Research Part C: Emerging Technologies · doi:10.1016/j.trc.2017.02.024 · Cited by 1,015
Social Sensing: A New Approach to Understanding Our Socioeconomic Environments
Liu, Y., Liu, X., Gao, S., Gong, L., Kang, C., Zhi, Y., Chi, G., & Shi, L. (2015) · Annals of the Association of American Geographers · doi:10.1080/00045608.2015.1018773 · Cited by 804
Self-citationExploiting place features in link prediction on location-based social networks
Scellato, S., Noulas, A., & Mascolo, C. (2011) · Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining · doi:10.1145/2020408.2020575 · Cited by 522
Examining the Challenges of Scientific Workflows
Gil, Y., Deelman, E., Ellisman, M., Fahringer, T., Fox, G., Gannon, D., Goble, C., Livny, M., Moreau, L., & Myers, J. (2007) · Computer · doi:10.1109/mc.2007.421 · Cited by 518
Gebru, T., Krause, J., Wang, Y., Chen, D., Deng, J., Aiden, E. L., & Fei-Fei, L. (2017) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1700035114 · Cited by 518
Cited by
Southworth, J., Migliaccio, K., Glover, J., Glover, J., Reed, D., McCarty, C., Brendemuhl, J., & Thomas, A. (2023) · Computers and Education: Artificial Intelligence · doi:10.1016/j.caeai.2023.100127 · Cited by 647
“GeoAI training is critical given the projected growth of approximately 16% in this industry by 2050 (Janowicz et al., 2020), and so establishing these focused areas of expertise and training at UF is timely.”
BackgroundResnik, D. B., & Hosseini, M. (2025) · AI and Ethics · doi:10.1007/s43681-024-00493-8 · Cited by 228
“AI tools have been used to perform or augment a variety of scientific tasks, including 1 : • Analyzing data and images [34, 43, 65, 88, 106, 115, 122, 124, 149, 161].”
Replication across space and time must be weak in the social and environmental sciences
Goodchild, M. F., & Li, W. (2021) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2015759118 · Cited by 157
Li, W., & Hsu, C.-Y. (2022) · ISPRS International Journal of Geo-Information · doi:10.3390/ijgi11070385 · Cited by 147
GeoAI at ACM SIGSPATIAL: progress, challenges, and future directions
Hu, Y., Gao, S., Lunga, D., Li, W., Newsam, S., & Bhaduri, B. (2019) · SIGSPATIAL Special · doi:10.1145/3377000.3377002 · Cited by 58
Self-citation
Metadata
- Authors
- Janowicz, K., Gao, S., McKenzie, G., Hu, Y., & Bhaduri, B.
- Venue
- International Journal of Geographical Information Science
- Publisher
- Informa UK Limited
- Published
- 2019-10-30
- Volume
- 34
- Issue
- 4
- Pages
- 625-636
- ISSN
- 0269-3798 (ISSN-L)
- 1365-8816
- 1362-3087
- OpenAlex
- W2982441053
- Cited by
- 600
- References
- 51
- Type
- journal article
- Language
- en
- Open access
- green
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- Janowicz, K., Gao, S., McKenzie, G., Hu, Y., & Bhaduri, B. (2020). GeoAI: spatially explicit artificial intelligence techniques for geographic knowledge discovery and beyond. International Journal of Geographical Information Science. https://doi.org/10.1080/13658816.2019.1684500
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
