Geospatial Data Mining

  • X. Zhou, W. Li, S. Wu, and S. Wang (2017). An ontology-driven, SVM approach for hyperspectral image classification. International Journal of Image and Data Fusion .(in press)
  • W. Li, S. Wang, and V. Bhatia (2016). PolarHub: A large-scale web crawling engine for OGC service discovery in cyberinfrastructure. Computers, Environment and Urban Systems , DOI: 10.1016/j.compenvurbsys.2016.07.004.
  • W. Li and C.Y. Hsu, 2018. Automated terrain feature identification from remote sensing imagery: a deep learning approach. International Journal of Geographical Information Science. https://doi.org/10.1080/13658816.2018.1542697.
  • N. N. Haghighi, X. C. Liu, R. Wei, W. Li, and H. Shao (2018). Using Twitter data for transit performance assessment: a framework for evaluating transit riders’ opinions about quality of service.  Public Transport, 1-15.
  • F. Wang, W. Li, S. Wang, and C.R. Johnson (2018). Association rule–based multivariate analysis and exploration of spatiotemporal climate data. ISPRS International Journal of Geo-information, 7(7), 266; doi: 10.3390/ijgi7070266.
  • W. Li (2018). Lowering the barriers for accessing distributed geospatial big data through large-scale web crawling to advance spatial data science: The PolarHub solution. Annals of the Association of American Geographers, doi: 10.1080/24694452.2017.1373625.
  • X. Zhang, W. Li, F. Zhang, R. Liu, and Z. Du (2018). Identifying urban functional zones using public bicycle rental records and Point-of-Interest data. International Journal of Geo-Information. 2018, 7(12), 459.
  • W. Li, B. Zhou, C.Y. Hsu, Y. Li, and F. Ren. 2017. Recognizing terrain features on terrestrial surface using a deep learning model: an example with crater detection. In: Proceedings of the 1st Workshop on Artificial Intelligence and Deep Learning for Geographic Knowledge Discovery (GeoAI '17) , ACM, New York, NY, USA, 33-36. DOI: https://doi.org/10.1145/3149808.3149814.
  • H. Shao, Y. Zhang, and W. Li (2017). Extraction and analysis of tourists’ spatiotemporal behavior based on social media data. Computers, Environment and Urban Systems, 65, 66-78
  • W. Li, M.F. Goodchild, R.L. Church and B. Zhou, 2012. Geospatial Data Mining on the Web: Discovering Locations of Emergency Service Facilities. In: S. Zhou, S. Zhang and G. Karypis (Eds.) ADMA2012, Lecture Notes in Artificial Intelligence,7713,pp 552-563.
  • W. Li, C. Yang, D. Nebert, R. Raskin and H. Wu, 2011. Semantic-based service chaining for building a virtual Arctic spatial data infrastructure. Computers & Geosciences. 37(11), 1752-1762.
  • W. Li, C. Yang and C. Yang, 2010. An active crawler for discovering geospatial web services and their distribution pattern. International Journal of Geographic Information Science, 24(8), 1127-1147.
  • W. Li, C. Yang and D. Sun, 2009. Mining the correlation of geophysical parameters’ contribution to tropical storms through decision-Tree analysis. Computer and Geosciences, 35(2), 309-316.