Gridded Population Maps Informed by Different Built Settlement Products

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 r...

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Bibliographic Details
Published in:Data (Basel) 2018-09, Vol.3 (3), p.33-33
Main Authors: Reed, Fennis J, Gaughan, Andrea E, Stevens, Forrest R, Yetman, Greg, Sorichetta, Alessandro, Tatem, Andrew J
Format: Article
Language:English
Subjects:
binary dasymetric
built areas
Climate change
Construction
Data Descriptor
Datasets
geographic information systems
geography
gridded population distribution
Land settlement
Model accuracy
Population growth
Population statistics
random forest
regression
Remote sensing
Spatial distribution
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Summary: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.
ISSN:2306-5729
2306-5729
DOI:10.3390/data3030033