Shelby Corning
Researcher
Agriculture, Forestry, and Ecosystem Services Research Group
Biodiversity and Natural Resources Program
Biography
Shelby Corning is a researcher in the Agriculture, Forestry, and Ecosystem Services Research Group of the IIASA Biodiversity and Natural Resources Program. Her current research focuses on the utilization of machine learning and cloud computing technology for disturbance detection and forest management, as well as wildfire mapping and risk modeling.Corning started at IIASA as an intern as part of her master’s program, where she researched historical wildfire occurrence in Rocky Mountain National Park using cloud computing and remote sensing time series. Before coming to IIASA, her work included a wide range of experiences in the natural resources field, including hiking trail construction, wildfire mitigation, forest management, and plant and wildlife monitoring, as well as several seasons as a ski patroller (ski medic) in Colorado, USA.
She received a BSc in Environmental Sciences from the University of Rochester in NY, USA and is currently completing her MSc in European Forestry through the University of Eastern Finland and the University of Natural Resources and Life Sciences (BOKU), Vienna. Her thesis is on machine learning methods for forest disturbance detection in the Wienerwald Biosphere Reserve.
Outside of research, she is an avid runner, reader, and all-around outdoorswoman.
Last update: 09 DEC 2022
Publications
Corning, S., Krasovskiy, A. , Kiparisov, P., San Pedro, J., Viana, C.M., & Kraxner, F. (2024). Anticipating Future Risks of Climate-Driven Wildfires in Boreal Forests. Fire 7 (4) e144. 10.3390/fire7040144.
Jo, H.-W., Corning, S., Kiparisov, P., San Pedro, J., Krasovskiy, A. , Kraxner, F., & Lee, W.-K. (2024). Integrating Human Domain Knowledge into Artificial Intelligence for Hybrid Forest Fire Prediction: Case Studies from South Korea and Italy. DOI:10.5194/egusphere-egu24-12320. In: EGU General Assembly 2024, 14-19 April 2024, Vienna.
San Pedro, J., Krasovskiy, A. , Corning, S., Kiparisov, P., & Kraxner, F. (2024). Modeling Wildfire Dynamics in Latin America Using the FLAM Framework. DOI:10.5194/egusphere-egu24-16369. In: EGU General Assembly 2024, 14-19 April 2024, Vienna.
Lutz, W. & Pachauri, S. (2023). Systems Analysis for Sustainable Wellbeing. 50 years of IIASA research, 40 years after the Brundtland Commission, contributing to the post-2030 Global Agenda. IIASA Report. Laxenburg, Austria: International Institute for Applied Systems Analysis (IIASA) 10.5281/zenodo.8214208.
Krasovskiy, A. , Corning, S., Cimdins, R., & Kraxner, F. (2023). Modeling risks of climate-driven wildfires in boreal forest: the FLAM approach. In: 20th IBFRA Conference, 28-31 August 2023, Helsinki.