The Center for Spatial Data Science (CSDS) addresses research questions where location represents an important dimension of the research problem, with applications in economic geography, environmental economics, sociology, criminology, public health, and other social sciences.
CSDS also develops new methods and open-source software tools for spatial econometric modeling, clustering, exploratory analysis, geovisual analytics, and CyberGIS (Geographic Information Systems).
A local indicator of multivariate spatial association: A new spatial statistic to identify local clusters in multivariate space
Gerrymandering and compactness: A quantitative framework for evaluating the implications of spatial constraints in districting reform
|Anselin, Kolak||Spatial econometrics and program evaluation (Anselin, Kolak, and Mobley)|
|Anselin et al.||Modeling health outcomes with spatial multilevel methods (Luc Anselin, Levi Wolf, and Lee Mobley)|
|James Saxon||Accessibility of primary healthcare: A new rational agent access model|
|Marynia Kolak||Open spatial technology frameworks: Integrating data and spatial analysis to continuously assess health programs and outcomes|
|Kolak et al.||Disparities in healthy food access in Chicago, 2007–2014|
|with M. Kolak||Spatial relation of local health department services and opioid overdose.|
|Kolak et al.||Mapping Census Tract Clusters of Type 2 Diabetes in a Primary Care Population|
|Kevin Credit||Transitive properties: a spatial econometric analysis of new business creation around transit|
|Kevin Credit||Quantifying the Retail Apocalypse|
|James Saxon||Local structures of human mobility in Chicago: Using mobile phone traces to construct a neighborhood-level mobility network|