Population Modeling Methods and Projects:

Implications for Data Use

Greg YetmanCIESIN, Columbia University

gyetman@ciesin.columbia.eduGEO Meningitis Environmental Risk Consultative

Meeting, September, 2007

World Data Center for Human Interactions in the Environment

Outline

• Population Surfaces: Two Cases• Population Modeling Methods and Projects• Implications of Methods and Inputs for Data Use • Derivative Data Products

Population Surfaces: Census and Ambient Populations

• Where census is the only input or considered “truth”, population model shows where people live. (GPW, GRUMP, Accessibility Model)

• Ambient populations include day and night population locations (highways, airports, commercial/industrial land use)

Midtown Manhattan

Persons/km2

0

1 - 10

11 - 100

101 - 1,000

1,001 - 10,000

10,001 +

Simple Allocation

• Proportional distribution of population across grid cells in administrative units

• Simple masking (water bodies, permanent ice) to remove uninhabited areas

• GPW data product uses simple allocation

Gridded Population of the World (GPW)

Version (pub) GPW v1 (1995) GPW v2 (2000) GPW v3 (2003)

Estimates for 1994 1990, 1995 1990, 1995, 2000

Input units 19,000 127,000 400,000

Accessibility Modeling

• Populated places (points) and roads used as population centers

• Optionally, city stable lights (satellite-derived) used to add detail to accessibility surface

• Administrative unit population reallocated within units using surface

• UNEP, CIESIN Population surfaces

Accessibility Surface

Accessibility Model UNEP, CIAT, WRI, & NCGIA, 1996+

Weighted Interpolation

• Multiple input layers used to interpolate population surface.

• Landscan from Oak Ridge National Laboratory reallocates administrative population esimates using:– Lights at Night– Elevation/Slope– Distance to Roads– Distance to Rivers– Land Cover

Landscan: Published Annually

Global Rural Urban Mapping Project (GRUMP)

Points PolygonsGridded surface

1 km

Hybrid approach that uses administrative data as “truth” and reallocates based on city lights and points.

Detailed Urban Extents from Satellite Data

• Automated and semi-automated extraction of urban extents from moderate or high-resolution imagery (Landsat, SPOT, Quickbird, Ikonos) or non-visible data (RADAR)

• Oxford University malaria mapping project is using Landsat and Radarsat data to define detailed urban extents in parts of Africa

Implications of Methods and Inputs for Data Use

• Variable dependence– Know the population model inputs to avoid

endogeneity• Night vs. day populations

– Estimating day vs. night populations with existing population surfaces is problematic

• Variable spatial inputs for most projects create issues in inter-regional comparison

Where practical, running the analysis with multiple population surfaces will provide an assessment of the variability (range) of population estimates.

Beyond Population: Derivative Data Products

Population Migration

• Little systematic data on global or regional basis– Landscan re-modeling by Oak Ridge based on

newspaper reports in war-torn countries

• Potential Approaches:– Update administrative boundaries based on survey

data or reports and produce model output(s) appropriate for application

– Re-allocate population surfaces using weighted interpolation based on population movement estimates

– Model population as a network, similar to hydrologic modeling with sources and sinks

Thanks!

Questions?

Greg Yetman

gyetman@ciesin.columbia.edu