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Dasymetric population mapping based on US census data and 30-m gridded estimates of impervious surface

  • Rachel H. Swanwick
  • , Quentin D. Read
  • , Steven M. Guinn
  • , Matthew A. Williamson
  • , Kelly L. Hondula
  • , Andrew J. Elmore
  • National Socio-Environmental Synthesis Center (SESYNC)
  • University of Vermont
  • United States Department of Agriculture
  • University of Maryland Center for Environmental Science
  • Arizona State University

Research output: Contribution to journalArticlepeer-review

26 Scopus citations

Abstract

Assessment of socio-environmental problems and the search for solutions often require intersecting geospatial data on environmental factors and human population densities. In the United States, Census data is the most common source for information on population. However, timely acquisition of such data at sufficient spatial resolution can be problematic, especially in cases where the analysis area spans urban-rural gradients. With this data release, we provide a 30-m resolution population estimate for the contiguous United States. The workflow dasymetrically distributes Census block level population estimates across all non-transportation impervious surfaces within each Census block. The methodology is updatable using the most recent Census data and remote sensing-based observations of impervious surface area. The dataset, known as the U.G.L.I (updatable gridded lightweight impervious) population dataset, compares favorably against other population data sources, and provides a useful balance between resolution and complexity.

Original languageEnglish
Article number523
JournalScientific Data
Volume9
Issue number1
DOIs
StatePublished - 27 Aug 2022

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