Gridded Population Maps Informed by Different Built Settlement Products

Fennis J. Reed, Andrea E. Gaughan, Forrest R. Stevens, Greg Yetman, Alessandro Sorichetta and Andrew J. Tatem
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Fennis J. Reed: Geography and Geosciences, University of Louisville, Louisville, KY 40292, USA
Andrea E. Gaughan: Geography and Geosciences, University of Louisville, Louisville, KY 40292, USA
Forrest R. Stevens: Geography and Geosciences, University of Louisville, Louisville, KY 40292, USA
Greg Yetman: CIESIN, Columbia University, Palisades, NY 10964, USA
Alessandro Sorichetta: WorldPop, Department Geography and Environment, University of Southampton, Southampton SO17 1B, UK
Andrew J. Tatem: WorldPop, Department Geography and Environment, University of Southampton, Southampton SO17 1B, UK

Data, 2018, vol. 3, issue 3, 1-11

Abstract: The spatial distribution of humans on the earth is critical knowledge that informs many disciplines and is available in a spatially explicit manner through gridded population techniques. While many approaches exist to produce specialized gridded population maps, little has been done to explore how remotely sensed, built-area datasets might be used to dasymetrically constrain these estimates. This study presents the effectiveness of three different high-resolution built area datasets for producing gridded population estimates through the dasymetric disaggregation of census counts in Haiti, Malawi, Madagascar, Nepal, Rwanda, and Thailand. Modeling techniques include a binary dasymetric redistribution, a random forest with a dasymetric component, and a hybrid of the previous two. The relative merits of these approaches and the data are discussed with regards to studying human populations and related spatially explicit phenomena. Results showed that the accuracy of random forest and hybrid models was comparable in five of six countries.

Keywords: gridded population distribution; geography; built areas; remote sensing; geographic information systems; random forest; regression; binary dasymetric (search for similar items in EconPapers)
JEL-codes: C8 C80 C81 C82 C83 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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