Peer Reviewed Journal Articles
- Fowler, C, Frey, N, Folch, D.C., Nagle, N, and Spielman SE (2019) Who are the People in Your Neighborhood? The contextual fallacy. Geographical Analysis.
- Weinberg, D., Abowd, J., Belli, R., Cressie, N., Folch, D., Holan, S., Levenstein, M., Olson, K., Reiter, J., Shapiro, M., Smyth, J., Soh, L-K., Spencer, B., Spielman, SE., Vilhuber, L., Wikle, C. (2018) Effects of a Government-Academic Partnership: Has the NSF-Census Bureau Research Network Helped Improve the U.S. Statistical System? Journal of Survey Statistics and Methodology
- Jurevitch, J., Griffin, AL., Spielman, SE., Folch, DC., Merrick, M. (2018) Navigating Uncertainty: How Urban and Regional Planners Shape Policy With Fuzzy Data From the American Community Survey. Journal of the American Planning Association
- Folch, DC., Spielman, SE., Manduca, R. (2017) Fast Food Data: Where User Generated Content Works, and Where it Doesn’t. Geographical Analysis
- Spielman, SE., Xiao, N., Cockings, S., and Tanton, R. (2017) Spatial Analysis with Demographic Data: Emerging Issues and Innovative Approaches. Special Issue of Computers, Environment and Urban Systems.
- Spielman, SE., Xiao, N., Cockings, S., and Tanton, R. (2017) Statistical Systems and Census Data in the Spatial Sciences. Computers, Environment, and Urban Systems.
- Guttman, M., Brown, D., Cunningham, A., Dykes, J., Leonard, S.H., Little J., Mikecz, J, Rhode, P., Spielman, S.E., Sylvester, K.M. (2016) Migration in the 1930s: Beyond the Dust Bowl. Social Science History. **Winner of the Social Science History Founder’s Prize for Best Paper**
- Bellman, B., Spielman, S.E., Franklin, R. (2016). Local Population Change and Variations in Racial Integration in the United States, 2000-2010. International Regional Science Review
- Folch, D.C., Arribas-Bel, D., Koschinsky, J., and Spielman, S.E. (2016). Uncertain Uncertainty: Spatial Variation in the Quality of American Community Survey Estimates. Demography
- Singleton, A., Brundson, C., and Spielman, S.E. (2015) Establishing a Framework for Open Geographic Information Science. International Journal of Geographic Information Science. **IJGIS Most Read Paper 2016 Award**
- Spielman, S.E. and Singleton, A. (2015) Studying Neighborhoods with Uncertain Data From the American Community Survey. Annals of the Association of American Geographers
- Wood, N., Jones, J., Spielman, S.E., Schmidtlein, M. (2015) Community clusters of tsunami vulnerability in the U.S. Pacific Northwest. Proceedings of the National Academy of Science
- Spielman, S.E. and Folch, D.F. (2015) Reducing Uncertainty in the American Community Survey through Data-Driven Regionalization. PLOSOne
- Spielman, S.E., Folch, D., Nagle, N. (2014) Patterns and Causes of Uncertainty in the American Community Survey. Applied Geography (replication data and code)
- Spielman, S.E. (2014) Spatial Collective Intelligence? credibility, accuracy, and Volunteered Geographic Information. Cartography and Geographic Information Science (CaGIS)
- Folch, D. and Spielman, S.E. (2014) Identifying Regions based on Flexible User Defined Constraints. International Journal of Geographic Information Science.
- Nagle, N., Leyk, S., Buttenfield, B., Spielman, S.E. (2014) Dasymetric Modeling and Uncertainty. The Annals of the Association of American Geographers.
- Singleton, A. and Spielman, S.E. (2014) The Past, Present and Future of Geodemographic Research in the United States and United Kingdom. The Professional Geographer.
- Spielman, S.E. and Harrison, P. (2014). Residential segregation and the built environment at the turn of the 20th century: a Schelling model. Transactions in GIS.
- Spielman, S.E., Yoo, E.-H. and Linkletter, C. (2013) Neighborhoods and Geographic Patterns in Health and Behavior: Understanding the Role of Scale and Residential Sorting. Environment and Planning B. **Winner of the Michael Breheny Prize for Best Paper in EPB**
- Spielman, S.E. and Logan, J (2012). Using high resolution population data to identify neighborhoods and determine their boundaries. Annals of the Association of American Geographers.
- Logan, J., Spielman, S.E., Klein, P. (2011) Identifying Ethnic Neighborhoods. Urban Geography, 32(3)
- Spielman, S.E. and Yoo, E-H. (2009). The Spatial Dimensions of Neighborhood Effects. Social Science and Medicine, 68(6)
- Spielman, S.E. and Thill, J.C. (2008). Social Area Analysis, Data Mining, and GIS. Computers, Environment, and Urban Systems, 32(2)
- Erdemir, E. T., Batta R., Spielman, S. E., Rogerson P., et. al. (2008). Optimization of aeromedical base locations in New Mexico. Accident Analysis and Prevention, 40(3)
- Erdemir, E.T., Batta, R., Spielman, S.E., Rogerson, P., Blatt, A., and Flanigan, M.A (2008). Location Coverage Models with Demand Originating from Nodes and Paths: Application to Cellular Network Design. European Journal of Operations Research, 190(3)
- Borrell, L., Northridge, M. E., Miller, D., Golembeski, C., Spielman, S. E. (2007). Oral Health and Health Care for Older Adults: Addressing Disparities and Planning Services. Special Care in Dentistry, 26(6).
- Spielman, S. E. (2006). Appropriate use of the K-function in Urban Environments (Letter). American Journal of Public Health, 96(2).
- Spielman, S.E., Golembeski, C.A., Northridge, M.E., et al. (2006). Interdisciplinary Planning for Healthier Communities: Findings from the Harlem Children’s Zone Asthma Initiative. Journal of the American Planning Association, 72(1).
- Fowler, C, Frey, N, Folch, D.C., Nagle, N, and Spielman SE (2018) The Contextual Fallacy. SocArXiv
- Folch, D.C., Arribas-Bel, D., Koschinsky, J., and Spielman, S.E. (2014). Uncertain Uncertainty: Spatial Variation in the Quality of American Community Survey Estimates. Arizona State University, Geoda Center Working Paper Series.
- Spielman, S.E. and Folch, D.C. (2014). Reducing Uncertainty in the American Community Survey through Data-Driven Regionalization. University of Colorado, Institute of Behavioral Science Working Paper Series (Paper # POP2014-05).
Peer Reviewed Conference Proceedings
- Spielman, S.E. (2012) Exceptions to the Law: Negative Spatial Autocorrelation in Egocentric Spatial Analysis. GIScience 2012. (extended abstract)
- Spielman, S.E. (2012) Does Lifestyle Structure Activity Space? GIScience 2012. (extended abstract)
- Spielman, S.E., David Folch, John Logan, Nicholas N. Nagle (2012) Thinking inside the box: mapping the microstructure of urban environments (and why it matters). AutoCarto 2012.
- Nagle, N., Buttenfield, B., Leyk, S., and Spielman, S.E. (2012) An Uncertainty-Informed Penalized Maximum Entropy Dasymetric Model GIScience 2012. (extended abstract)
- Spielman, S.E. (2011) Time-Geography and the Twilight Zone, Proceedings of ISPRS-ICA Joint Commission on Geospatial Analysis and Modeling.
- Spielman, S.E., Yoo, E.-H. and Linkletter, C. (2011) Understanding the Role of Scale and Sorting in the Estimation of Neighborhood Effects, Proceedings of the 17th European Colloquium on Quantitative and Theoretical Geography.
- Spielman, S.E. and Logan, J. (2011) Western Regional Science Association Annual Meeting, Identifying neighborhoods.
Spielman, S.E. (In press) Point Pattern Analysis. International Encyclopedia of Geography.
- Spielman, S.E. (2016) Using big data to improve neighborhood level estimates from the American Community Survey. Chapter X in Seeing Cities Through Big Data – Research, Methods and Applications in Urban Informatics.
Spielman, S.E., Folch, D.C. (2015) Social Area Analysis with Self-Organizing Maps. Chapter 9 in Geocomputation Singleton and Brundson (eds.).
- Department of Interior Strategic Sciences Group, Operation Group Sandy, Technical Report (2013), Washington, D.C. 75p.
Currently in Review
- Does the Social Vulnerability Index (SoVI) Actually Measure Social Vulnerability?
- A critical analysis of the Social Vulnerability Index. Our paper demonstrates fragility and logical inconsistencies in a widely used social indicator.
- Meso-Scale Mobility: observing residential mobility in China using a novel form of big data.
- Using novel forms of big data to fill gaps in a national census. We identify methods for measuring residential mobility at high temporal and spatial resolutions from big data.
- Generalized Activity Spaces: a demographic structure in urban activity patterns.
- Do similar types of people use urban space in similar ways? Can we develop archetypical patterns in human mobility conditional on demographic, economic, and contextual factors? In this paper we develop a novel kind of segmentation for human activity patterns and show that individual characteristics may trump locational characteristics in determining travel patterns.