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WorldPop-RF, Version 2b.1.1

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Version 3 2015-07-22, 19:48
Version 2 2015-07-22, 19:48
Version 1 2015-07-22, 18:41
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posted on 2015-07-22, 18:41 authored by Forrest R. StevensForrest R. Stevens, Andrea E. Gaughan, Catherine Linard, Andrew J. Tatem, Alessandro Sorichetta, Graeme M. Hornby, Nirav N. Patel, Jeremiah Nieves

The source stored here represent the Python and R scripts backing the WorldPop project's mapping efforts to produce gridded population density estimates of people per ~100 m pixel. These are produced using a Random Forest (RF) model as described in Stevens, et al. (2015). The published article contains a description of the RF model and its covariates, their sources and any metadata collected for each covariate. An estimated prediction weighting layer is used to dasymetrically redistribute the census counts and project counts to match estimated populations based on UN estimates for the final population maps provided by WorldPop.

These data and the code represent the methods and algorithms employed through the end of production for the Asian and Americas datasets.

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