2 papers
cs.LG2026
Geospatial foundation-model embeddings improve population estimation unevenly across space and scale
Wenbin Zhang, Eimear Cleary, Francisco Rowe +4
Reliable subnational population estimates are essential for applications, yet remain difficult where censuses are sparse, outdated or spatially coarse. Existing population-mapping…
stat.AP2026
Social Media Data for Population Mapping: A Bayesian Approach to Address Representativeness and Privacy Challenges
Paolo Andrich, Shengjie Lai, Halim Jun +4
Accurate and timely population data are essential for disaster response and humanitarian planning, but traditional censuses often cannot capture rapid demographic changes. Social m…