Ph.D., University of South Carolina (2012)
Office: AUST 430
Office phone: 860-486-3322
- Geospatial analysis of vulnerability and risk from natural hazards and disasters
- Machine learning applied to hazard impacts and recovery
- Index construction and validation
- Disaster resilience and recovery modeling
- Human-environmental interactions
UConn Geography Research Clusters:
Dr. Christopher G. Burton is specialized in the application of geospatial analysis and modeling to human-environmental problems. Dr. Burton's interests include the development of methods and metrics that are critical for evaluating interactions within and between natural, social, and engineered systems. Dr. Burton’s methods include the use of geospatial analytics, artificial intelligence (AI), data mining, and the integration of quantitative and qualitative methods to better understand factors that affect the spatial distribution of disaster impacts and recovery from damaging hazard events.
Burton, C.G., Toquica, M., Asad*, KMB, and Musori*, M. (2022). Validation and Development of Composite Indices for Measuring Vulnerability to Earthquakes using a Socio-economic Perspective. Natural Hazards 111: 1301-1334.
Khazai, B., Anhorn, H., and Burton C.G. (2018). Resilience Performance Scorecard: Measuring Urban Disaster Resilience at Multiple Levels of Geography. International Journal of Disaster Risk Reduction, 31: 604-616.
Burton C.G. and Silva V. (2016). Assessing Integrated Earthquake Risk in OpenQuake with an Application to Mainland Portugal. Earthquake Spectra, 32(3): 1383-1403.
Rufat, S., Tate, E. C., Burton C.G. and Sayeed Maroof, A. (2015). Social Vulnerability to Floods: Review of Case Studies and Implications for Measurement. International Journal of Disaster Risk Reduction, 14(4): 470–486.
Burton C.G. (2015). A Validation of Metrics for Community Resilience to Natural Hazards and Disasters using the Recovery from Hurricane Katrina as a Case Study. Annals of the Association of American Geographers, 150 (1): 67–86.