The Spatial Sciences Census Research Node (SSCRN) will foster a connection between the spatial and the survey sciences. This bridge will yield both immediate and long-term benefits for the estimation, dissemination, and usability of the small area statistics produced by the Census Bureau. Small area statistics describe the character of the population within small geographic zones, such as census tracts. Small area estimates from the American Community Survey (ACS) are imprecise. Historically, very little attention has been paid to the geographic distribution of populations within these small areas. The basic research of SSCRN will increase knowledge about the organization of the American population within small geographic areas for the purpose of improving small area estimates. Apart from the impractical solution of increasing the sample size, the only way to reduce the uncertainty of survey estimates is to utilize ancillary information about the population. SSCRN will exploit new forms of geographic information and recent advances in spatial statistics to make small area estimates more accurate. In addition to improving small area population estimates, an improved understanding of the geographic micro-structure of the American population is of broad scientific interest and may expand knowledge about socio-spatial processes like segregation and neighborhood effects.

SSCRN will bridge the spatial and the survey sciences through basic research that addresses the current needs of the Census Bureau and yields tangible products for researchers. SSCRN will develop and disseminate training materials, software, and research for a broad community of Census data users and producers. SSCRN will convene a series of interdisciplinary meetings designed to identify research frontiers at the intersection of the spatial and the survey sciences. The meetings will be used to design and refine a novel curriculum and workshop series aimed at developing a cohort of scientists that are capable of establishing and elucidating links between the spatial and survey sciences. SSCRN will develop software tools that will enhance the usability of ACS small area estimates by allowing users to intelligently combine tracts to reduce uncertainty in variables of interest. SSCRN will educate and train a large group of students, post docs, and scientists through meetings, structured mentoring, and workshops. The impact of these activities will be multiplied through design and dissemination of a broadly accessible model curriculum and training workshop. Finally, SSCRN will have a broad impact by releasing a novel form of spatial microdata that will improve small area estimation and enable researchers to explore the spatial structure of the American population. This activity is supported by the NSF-Census Research Network funding opportunity.

National Science Foundation (NSF)
Division of Social and Economic Sciences (SES)
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Cheryl L. Eavey
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University of Colorado at Boulder
United States
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