![]() ![]() This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.įunding: AJT acknowledges funding support from the RAPIDD program of the Science and Technology Directorate, Department of Homeland Security, and the Fogarty International Center, National Institutes of Health, and is also supported by grants from the Bill and Melinda Gates Foundation (#49446 and #1032350). ![]() Received: SeptemAccepted: JanuPublished: February 13, 2013Ĭopyright: © 2013 Gaughan et al. The 20 datasets produced are freely available as a product of the AsiaPop Project and can be downloaded from: Citation: Gaughan AE, Stevens FR, Linard C, Jia P, Tatem AJ (2013) High Resolution Population Distribution Maps for Southeast Asia in 20. Using existing data, it is possible to produce detailed, contemporary and easily updatable population distribution datasets for Southeast Asia. Results indicate mapping accuracies are consistently higher when incorporating land cover and settlement information into the AsiaPop modelling process. These products were compared with those from two other methods used to construct commonly used global population datasets. Landsat-derived settlement maps and land cover information were combined with ancillary datasets on infrastructure to model population distributions for 20. Here we outline approaches to construct a database of GIS-linked circa 2010 census data and methods used to construct fine-scale (∼100 meters spatial resolution) population distribution datasets for each country in the Southeast Asia region. The Southeast Asia region has undergone rapid urbanization and population growth over the past decade, yet existing spatial population distribution datasets covering the region are based principally on population count data from censuses circa 2000, with often insufficient spatial resolution or input data to map settlements precisely. Spatially accurate, contemporary data on human population distributions are vitally important to many applied and theoretical researchers. ![]()
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