Mapping Density with Intensity: Spatial Disaggregation of Gridded Population Density using Stable Night Light Brightness

Christopher Small, Columbia University, csmall@columbia.edu (Presenter)
Christopher Elvidge, NOAA NGDC, chris.elvidge@noaa.gov
Gregory Yetman, Columbia University, gyetman@ciesin.columbia.edu
Kimberly Baugh, NOAA NGDC, kim.baugh@noaa.gov
Kytt MacManus, Columbia University, kmacmanu@ciesin.columbia.edu

Stable night lights provide globally consistent proxies for lighted development associated with a variety of human settlement types. Gridded census enumerations provide geospatial depictions of human population density associated with residential population distributions. Early work, most notably by Sutton, Elvidge and colleagues, has showed broad spatial correspondence of population density with night light intensity over a wide range of each. However, the large range of sizes of administrative units used in these early studies leads to widely varying spatial resolution of census enumerations, generally resulting in considerable spatial uncertainty of population and large disparities between night light intensity and interpolated population density. Recent improvements in both night light imaging and census data resolution have largely resolved this issue and now allow us to compare stable night light and residential population density with much greater spatial correspondence than previously possible. Quantitative comparison of population density and night light brightness provides a basis for estimation of density/intensity transfer functions in a diverse set of countries with spatially detailed census enumerations. We use night light brightness from the Visible/Infrared Imaging Radiometer Suite (VIIRS) on the NASA/NOAA Suomi satellite and population density grids from the NASA SEDAC Gridded Population of the World v.4 (GPWv4) product to derive density/intensity transfer functions for a wide range of urban/rural gradients in the USA, Brazil, Sri Lanka, Malawi, South Africa and Portugal. We find multiple forms of bivariate distribution and transfer functions with broad consistency both within and across countries over a range of intensities of development. Comparison with Landsat imagery suggests general consistency with land use inferred from land cover. These results suggest that VIIRS night lights may be used with GPW4 population density grids in countries with detailed census enumerations to derive more general transfer functions that can be used to produce simple, transparent ambient population products with spatial uncertainty estimates. Such products could be used for testing a wide range of environmental and socioeconomic scenarios in which a transparent depiction of ambient population density is required.

Presentation Type:  Poster

Session:  Theme 4: Human influence on global ecosystems   (Mon 4:30 PM)

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• Related Activity: Related Activity or Previously Funded CC&E Activity not listed ...details

Poster Location ID: 118