Geospatial Analysis
Point process modeling with spatiotemporal covariates for predicting crime
Development of Advanced Computational and Geographic Visualization Methods for Geospatial and Temporal Strategic Risk Assessment of Crime
Real-Time Crime Forecasting Challenge
The Real-Time Crime Forecasting Challenge sought to harness the advances in data science to address the challenges of crime and justice. It encouraged data scientists across all scientific disciplines to foster innovation in forecasting methods. The goal was to develop algorithms that advance place-based crime forecasting through the use of data from one police jurisdiction.
Expanding on Total Body Score with Use of Geographic Information Systems (GIS)
Investigating the Impacts of Institutional and Contextual Factors on Protection Order Decision-Making
Space-time study of youth and school violence
Integrating Emergency Department Data with Law Enforcement, Emergency Medical Service and Community Data to Reduce Violence
Tale of Four Cities: Improving Our Understanding of Gun Violence-Supplement
Policing predicted crime areas: An operationally-realistic randomized, controlled field experiment
Cops on Dots Doing What? The Differential Effects of Law Enforcement-Oriented Actions in Hot Spots
Translating “Near Repeat” Theory into a Geospatial Police Strategy
NIJ FY 14 Testing Geospatial Predictive Policing Strategies
NIJ is seeking proposals for research that links theory of any discipline (e.g., criminological, behavioral, economic, sociological) to geospatial predictive policing strategies. In particular, NIJ is interested in proposals that focus on linking theories to current policing strategies, discerning potential disconnects in the levels of analysis between theory and practice, explicating what effects this may have on findings, and, finally, addressing means of adapting theory...