About Fang Fang
Biography
Dr. Fang Fang joined DURP in September 2019 as a lecturer. Dr. Fang’s research uses geographic information systems (GIS), remote sensing, machine learning, and spatial modeling to understand trees and forests in the urban environment. Dr. Fang received her PhD in Geography from West Virginia University in August 2019. She earned her master’s in Environmental Engineering from Ulsan National Institute of Science and Technology and a bachelor’s in Urban and Regional Planning and Resource Management from Beijing Forestry University.
Education
- PhD, Geography, West Virginia University (2019)
- Master of Environmental Engineering, Ulsan National Institute of Science and Technology
- Bachelor of Urban and Regional Planning and Resource Management, Beijing Forestry University
Research and publications
Ongoing and upcoming research
Ongoing and Upcoming Research
- Use GIS and quantitative analysis to answer complex urban planning questions, e.g., connectivity, land use, and accessibility to services
- Urban tree species discrimination using high spatial resolution images and machine learning
- Object-based image analysis to describe urban tree health
Selected publications
Dye, A. W., Kim, J. B., McEvoy, A., Fang, F., & Riley, K. L. (2021). Evaluating rural Pacific Northwest towns for wildfire evacuation vulnerability. Natural Hazards, 1-25. https://doi.org/10.1007/s11069-021-04615-x
Fang, F., McNeil, B. E., Warner, T. A., Maxwell, A. E., Dahle, G. A., Eutsler, E., & Li, J. (2020). Discriminating tree species at different taxonomic levels using multi-temporal WorldView-3 imagery in Washington DC, USA. Remote Sensing of Environment, 246, 111811. https://doi.org/10.1016/j.rse.2020.111811
Fang, F., McNeil, B., Warner, T., Dahle, G., & Eutsler, E. (2020). Street tree health from space? An evaluation using WorldView-3 data and the Washington DC Street Tree Spatial Database. Urban Forestry & Urban Greening, 126634. https://doi.org/10.1016/j.ufug.2020.126634
Fang, F., McNeil, B. E., Warner, T. A., & Maxwell, A. E. (2018). Combining high spatial resolution multi-temporal satellite data with leaf-on LiDAR to enhance tree species discrimination at the crown level. International journal of remote sensing, 39(23), 9054-9072. https://doi.org/10.1080/01431161.2018.1504343
Fang, F., Im, J., Lee, J., & Kim, K. (2016). An improved tree crown delineation method based on live crown ratios from airborne LiDAR data. GIScience & Remote Sensing, 53(3), 402-419. https://doi.org/10.1080/15481603.2016.1158774
Teaching and advising
Classes taught
- UP 116 Urban Informatics
- UP 199-FF Data Science for Planners
- UP 418 GIS for Planners