A Bayesian approach to produce 100 m gridded population estimates using census microdata and recent building footprints.
收藏DataCite Commons2021-02-26 更新2025-04-17 收录
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https://data.worldpop.org/repo/docs/leasure2020bayesian/
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资源简介：
This report describes a novel Bayesian statistical method that combines recent building footprints from Ecopia.AI and Maxar Technologies with publicly-available census microdata from IPUMS International to produce 100 m gridded population estimates for Ghana. The model was used to estimate total populations, populations within specific age-sex groups, number of households, people per household, and households per building. Bayesian estimates of uncertainty are provided with all parameter estimates. Supplementary files are included with input data and statistical model code in the Stan programming language. This method is generalizable to additional countries where IPUMS data and building footprints are available.
提供机构：
University of Southampton
创建时间：
2020-11-19
