Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4/W2, 117-120, 2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.
05 Jul 2017
C. T. Lloyd WorldPop, Geography and Environment, University of Southampton, Highfield Campus, Southampton, SO17 1BJ, UK
Keywords: WorldPop, human population, open access archive, high resolution, global, spatial dataset Abstract. Open access geospatial data represent a range of metrics relevant to global human population mapping at fine spatial scales. Detailed and contemporary spatial datasets that accurately describe population distributions are vital in order to measure impacts of population growth, monitor change, and plan interventions. To construct such datasets the harmonisation of geospatial data layers is a prerequisite because layer specifications differ widely.

To this end the WorldPop Project is producing an open access archive of 3 and 30 arc-second (~ 100 m and ~ 1 km, respectively) resolution gridded data in a predominantly open source environment, using OSGEO4W utilities. Five tiled raster datasets form the basis of the archive: (i) Viewfinder Panoramas topography clipped to CIESIN national level administrative coastlines; (ii) a matching ISO 3166 country identification grid; (iii) country area; (iv) pixel area; (v) and slope layer. Further layers will include transport networks, landcover, urban extent, nightlights, climate, travel time to major cities, forest stand change, livestock densities, vegetation indices, and waterways. We here describe the base datasets and the production methodology in development. The alpha version of the archive can be downloaded both from the WorldPop Dataverse Repository and the WorldPop Project website. The improved and expanded beta version of the archive is in development for release next year, and will offer significantly improved standardisation of country boundaries, and inland water boundaries (forthcoming), to global census unit data.

Conference paper (PDF, 570 KB)

Citation: Lloyd, C. T.: HIGH RESOLUTION GLOBAL GRIDDED DATA FOR USE IN POPULATION STUDIES, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4/W2, 117-120,, 2017.

BibTeX EndNote Reference Manager XML