Dr. Yanan Wu
Assistant Professor
Burdick Hall, Room 138B
(501) 450-3434
Biography
Dr. Yanan Wu’s research explores the interaction between human activity and environment using novel data, machine learning and advanced analytical methods. Dr. Wu’s projects cover below research topics:
- Geoscience for Historical Map Intelligence
- Spatial-temporal modeling of Traffic and Urban Dynamics
- Lidar, Remote Sensing, and 3D Modeling
- Geospatial Data for Human-Environment Interaction
If you are interested in working with Dr. Wu on GIScience, historical map, human events, urban geography, please email at ywu@uca.edu with your cv. Every self-motivated student is highly welcome to join the research team!
Professional Links
CV | Google Scholar | Personal Website | GitHub | LinkedIn| Medium Blog
Projects
Courses
- GIS Fundamental
- Field Techniques
- Python in GIS
Education Background
- 2019–2024 Ph.D. in Geospatial Information Sciences. University of Texas at Dallas, Texas, USA
- 2017–2019 M.A. in Geography. Binghamton University (SUNY), New York, USA
- 2012–2016 B.S. in Resource Environment and Urban-Rural Planning Management. Xi’an University of Science and Technology, China
Awards & Honors
2023
- Second Place in Graduate Paper Competition, SWAAG conference
- International Cartographic Association Scholarship
- Travel award from USNC for ICA with NSF funding to attend the ICC2023
- Betty & Gifford Johnson Travel Award, UTD
Publications
- Yang, Y., Wu, Y., Yuan, M. (2025). Simulation‐Tested Spatial Association Mining of Co‐Location Patterns From Multiple Point‐Feature Classes. Transactions in GIS, 29(7), e70145.
- Yang, Y., Wu, Y., & Yuan, M. (2024). What Local Environments Drive Opportunities for Social Events? A New Approach Based on Bayesian Modeling in Dallas, Texas, USA. ISPRS International Journal of Geo-Information, 13(3), 81.
- Wu, Y., Yang, Y., & Yuan, M. (2024). Location Analytics of Routine Occurrences (LARO) to Identify Locations with Regularly Occurring Events with a Case Study on Traffic Accidents. Information, 15(2), 107.
- Wu, Y., Yang, Y., & Yuan, M. (2023). Understanding the role of geographical environments in emergency dispatches with GPS trajectories. Abstracts of the ICA, 6, 276.
- Wu, Y., Yang, Y., Yuan, M. (2022). Analyze emergency-vehicle dispatches in Dallas, Texas, USA. Unknown Journal.
- Wu, Y., & Yuan, M. (2021). Where and why there: location analytics of routine occurrences (LARO) with a case study on traffic accidents. Abstracts of the ICA, 3, 318.
- Wu, Y. (2019). Integration of Earth Observation and in Situ Data for Analyzing Lake Level Changes in Minnesota (1992–2016). Master’s thesis, State University of New York at Binghamton.
Presentations
2025
- Digitizing the Past: Reconstructing Historical Cities Using Machine Learning, SWAAG, November
- Automatic Reconstruction of Historical Buildings through Deep Learning and Map Analysis, Arkansas GIS User Forum, October
- Reconstructing Historical Urban Landscapes: A Machine Learning Approach to 3D City Modeling, AAG, March
2024
- Understanding the role of geographical environments in emergency dispatch, AAG, March
2023
- Identify geographical environments influencing emergency response performance, SWAAG
- Modeling of emergency incidents with GPS trajectory data using random forest algorithm, ICC
- Assessing the role of geographical context in modeling the likelihood of emergency response, AAG