Yue Lin
Yue Lin Office: Phone: Email
Assistant Instructional Professor of GIScience

Yue Lin is an Assistant Instructional Professor of Geographic Information Science in the Division of the Social Sciences and the College. Her research is focused on geocomputation, geospatial data science, and digital privacy and justice. Her current work involves developing computational methods to ensure privacy, fidelity, and equity in the dissemination and mining of geospatial data. Yue received her doctorate in Geography from the Ohio State University in 2023.

Recent Research / Recent Publications

Refereed Journal Articles

Lin, Y. (2023). Geo-indistinguishable masking: Enhancing privacy protection in spatial point mappingCartography and Geographic Information Science. In Press. doi: 10.1080/15230406.2023.2267967.

Lin, Y. & Xiao, N. (2023). Generating small areal synthetic microdata from public aggregated data using an optimization methodThe Professional Geographer. In Press. doi:10.1080/00330124.2023.2207640.

Lin, Y. & Xiao, N. (2023). Assessing the impact of differential privacy on population uniques in geographically aggregated data: The case of the 2020 U.S. CensusPopulation Research and Policy Review, 42(5), 81.

Lin, Y., Xu, C., & Wang, J. (2023). sandwichr: Spatial prediction in R based on spatial stratified heterogeneityTransactions in GIS, 27(5), 1579–1598.

Lin, Y., Li, J., Porr, A., Logan, G., Xiao, N. & Miller, H. (2023). Creating building-level, three-dimensional digital models of historic urban neighborhoods from Sanborn Fire Insurance maps using machine learningPLoS ONE, 18(6), e0286340.

Lin, Y. & Xiao, N. (2023). A computational framework for preserving privacy and maintaining utility of geographically aggregated data: A stochastic spatial optimization approachAnnals of the American Association of Geographers, 113(5), 1035–1056.

Lin, Y. & Xiao, N. (2022). Identifying high accuracy regions in traffic camera images to enhance the estimation of road traffic metrics: A quadtree-based methodTransportation Research Record, 2676(12), 522–534.

Refereed Conference Proceedings

Lin, Y. & Xiao, N. (2023). Investigating MAUP effects on census data using approximately equal-population aggregations12th International Conference on Geographic Information Science (GIScience 2023), September 12–15, Leeds, UK.

Lin, Y. & Xiao, N. (2022). Developing synthetic individual-level population datasets: The case of contextualizing maps of privacy-preserving census dataAutoCarto 2022, November 2–4, Redlands, CA.


Lin, Y., Xu, C., & Wang, J. sandwichr: Spatial prediction based on spatial stratified heterogeneity. R package version 1.0.4.