Protecting Privacy in Mapping

Lin, Y. (2023). Geo-indistinguishable masking: Enhancing privacy protection in spatial point mapping. Cartography 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 method. The 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. Census. Population Research and Policy Review, 42(5), 81.

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