Teaching students to analyze spatial data using Python and R programming to inform on global challenges is one of the most rewarding parts of my work.
I’m a spatial data scientist who develops computational approaches to integrate and validate data on physical and human systems for decision making during disasters. A core aspect of my research is the evaluation of citizen science data to improve monitoring of environmental hazards at local scales. I serve as co-chair of the Committee on Data (CODATA) Participatory Mapping task group of the International Science Council.
- Bucherie A., Hultquist C., Adamo S., Neely C., Ayala F., Bazo J. and Kruczkiewicz A. (2022) A comparison of social vulnerability indices specific to flooding in Ecuador: principal component analysis (PCA) and expert knowledge. International Journal of Disaster Risk Reduction 73 http://dx.doi.org/10.1016/j.ijdrr.2022.102897.
- Hultquist C. and Tubbeh RM. (2022) Digital Sociotechnical Systems of Mutual Aid: How Communities Connected, Adapted, and Innovated During the COVID-19 Pandemic in New York City. Citizen Science: Theory and Practice 7(1) http://dx.doi.org/10.5334/cstp.454.
- Hultquist C., de Sherbinin A., Bowser A. and Schade S. (2022) Editorial: Open Citizen Science Data and Methods. Frontiers in Climate 4 http://dx.doi.org/10.3389/fclim.2022.943534.
- Tedesco M., Hultquist C. and De Sherbinin A. (2022) A New Dataset Integrating Public Socioeconomic, Physical Risk, and Housing Data for Climate Justice Metrics: A Test-Case Study in Miami. Environmental Justice 15(3): 149-159. http://dx.doi.org/10.1089/env.2021.0059.
- Tedesco M., Keenan JM. and Hultquist C. (2022) Measuring, mapping, and anticipating climate gentrification in Florida: Miami and Tampa case studies. Cities http://dx.doi.org/10.1016/j.cities.2022.103991.