Global Rural-Urban Mapping Project (GRUMP), v1

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Introduction

Urbanization poses both challenges and opportunities for sustainable development and environmental management. Improved data on patterns of human settlement and trends in population can help researchers and policy makers better understand differences between urban and rural areas in terms of their impacts on the environment and vulnerability to environmental variability and change. The Global Rural-Urban Mapping Project, Version 1 (GRUMPv1) data collection is a valuable resource both for researchers studying human-environment interactions and for applied users working to address critical environmental and societal issues.

GRUMPv1 consists of eight global data sets: population count grids, population density grids, urban settlement points, urban-extents grids, land/geographic unit area grids, national boundaries, national identifier grids, and coastlines. All grids are provided at a resolution of 30 arc-seconds (~1km), with population estimates normalized to the years 2000, 1995, and 1990. All eight data sets are available for download as global products, and the first five data sets are also available as continental, regional, and national subsets.

The population density and population count grids build on SEDAC’s Gridded Population of the World, Version 3 data set (GPWv3), which does not distinguish between urban and rural areas. GRUMPv1 identifies urban areas based in part on observations of lights at night collected by a series of Department of Defense meteorological satellites over several decades. The night-light data were carefully processed by the U.S. National Geophysical Data Center (NGDC) in Boulder, Colorado. SEDAC then used these and other supplementary data to develop an urban-rural “mask,” or urban extents grid, which identifies those areas of the Earth’s land surface that appear to be urbanized. GRUMPv1 also includes a geo-referenced database of urban settlements with populations greater than 5,000 persons that may be downloaded in both tabular and shapefile formats.