SciDataCon September, 2016 Greg Yetman Kytt MacManus Gridded Population of the World Version 4 Basic Demographic Characteristics and Data Quality Metrics SciDataCon September, 2016 Greg Yetman Kytt MacManus

Socioeconomic Data & Applications Center (SEDAC) Focus on human dimensions of environmental change Integration of social and earth science data, especially with remote sensing Direct support to scientists, applied and operational users, decision makers, and policy communities

Gridded Population of the World Gridded (raster) data product developed to provide a spatially-disaggregated population surface that is compatible with data sets from social, economic, and Earth science fields. Census population data are transformed from their native spatial units to a global grid of quadrilateral latitude-longitude cells (Balk et al. 2010) Free and openly available GPW version 3, 2000 population density Transforming census units to a grid

Development of GPW GPWv1 GPWv2 GPWv3 GPWv4 Publication Year Years of Estimation Grid Resolution Number of Input Units (subnational geographic units) Census variables Population Density Grid GPWv1 1995 1994 5 arc-minutes 19,000 Total Population GPWv2 2000 1990, 1995 2.5 arc-minutes 127,000 GPWv3 2005 1990, 1995, 2000 ~ 400,000 GPWv4 2015 2000, 2005, 2010, 2015, 2020 30 arc-seconds (1 km) ~ 13,000,000 Total Population, Sex, Age, Urban/Rural status 1994 1995 2000 2010

GPWv4: Population Density

Additional Demographic Characteristics Sex ratio Age: 5-year age groups Some exceptions where only three age categories may be available (child/youth, adult, elderly) Select countries have single-year breakdowns Urban/Rural status—as designated by national census or mapping organizations Issues in harmonization, matching in time

Addition of gridded census variables % Rural population, 2010, Panama % Urban population, 2010, Panama

Data Quality Metrics: Data Context Approximately 13.8m square km are in uninhabited, no households, and protected area categories. About 117k square km are in the other categories Categorizes pixels with no population estimate based on information from census documents.

Data Quality Metrics: Water Mask Distinguishes between pixels that are completely water or ice and pixels that also contain land.

Data Quality Metrics Mean Administrative Unit Areas Area of the input census unit from which each pixel is derived. Where multiple units cover a pixel, the mean of the input units is used.

Using the Mean Administrative Unit Area Data Aggregation regions larger than the input census units are highlighted

Population Estimation Service

HazPop App for iOS Free in the App Store

Thanks! Questions? Greg Yetman gyetman@ciesin.columbia.edu Kytt MacManus kmacmanu@ciesin.columbia.edu sedac.ciesin.columbia.edu/gpw