Spatiotemporal aggregation for temporally extensive international microdata

Research output: Contribution to journalArticlepeer-review

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Abstract

We describe a strategy for regionalizing subnational administrative units in conjunction with harmonizing changes in unit boundaries over time that can be applied to provide small-area geographic identifiers for census microdata. The availability of small-area identifiers blends the flexibility of individual microdata with the spatial specificity of aggregate data. Regionalizing microdata by administrative units poses a number of challenges, such as the need to aggregate individual scale data in a way that ensures confidentiality and issues arising from changing spatial boundaries over time. We describe a regionalization and harmonization strategy that creates units that satisfy spatial and other constraints while maximizing the number of units in a way that supports policy and research use. We describe this regionalization strategy for three test cases of Malawi, Brazil, and the United States. We test different algorithms and develop a semi-automated strategy for regionalization that meets data restrictions, computation, and data demands from end users.

Original languageEnglish (US)
Pages (from-to)26-37
Number of pages12
JournalComputers, Environment and Urban Systems
Volume63
DOIs
StatePublished - May 1 2017

Bibliographical note

Funding Information:
This work was funded by the National Science Foundation DataNet program, Award ACI-0940818 (Terra Populus project) the National Institutes of Health, Grant R24HD041023 (Minnesota Population Center, Center Grant).

Publisher Copyright:
© 2016 Elsevier Ltd

Keywords

  • Census microdata
  • Cluster analysis
  • Regionalization

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