Finding the Slippery Slope
Challenges and Opportunities to Investigate Landslides from Space
![](upload/docs/image/jpeg/2020-02/conf_kirschbaum.jpg)
Infos
Quartier Village 4, Clos Mercator 3
4000 Liège Voir la carte
The Faculty of Sciences and the Geographical Society of Liège have the pleasure to invite you to the lecture by Dr Dalia Kirschbaum entitled "Finding the Slippery Slope: Challenges and Opportunities to Investigate Landslides from Space".
Dr. Dalia Kirschbaum is a Research Physical Scientist in the Hydrological Sciences Laboratory at NASA Goddard Space Flight Center, Greenbelt, MD. Her research interests center on the application of remotely sensed data to characterize, model and observe rainfall-triggered landslides at multiple spatial and temporal scales. The modeling and data developed through this work has been integrated within the Rio de Janeiro, Brazil landslide alerting system and model outputs are used routinely by other groups including the Pacific Disaster Center, Army Geospatial Center, and Mexico Disaster Atlas, among others. Dr. Kirschbaum is also the Global Precipitation Measurement (GPM) Mission Deputy Project Scientist for Applications. In this role, she provides scientific support for applications research and activities. Dr. Kirschbaum serves as one of the NASA Goddard coordinators for an agency-wide Disaster Response team that aims to improve the utilization of NASA satellite and model products for disaster response and recovery. Dr. Kirschbaum has been a Civil Servant at NASA Goddard since 2011. She received her M.S. and Ph.D. in Earth and Environmental Sciences from Columbia University with a focus in Natural Hazards and Remote Sensing and her A.B. in Geosciences from Princeton University.
Finding the Slippery Slope: Challenges and Opportunities to Investigate Landslides from Space
Rainfall-triggered landslides occur in nearly every country in the world, causing billions of dollars in damages and thousands of fatalities each year. Accurately resolving the time, location, and impacts of these hazards is vital for characterizing their variability, providing appropriate and timely responses to disaster events, supporting robust recovery plans and formulating mitigation strategies. However the multi-faceted failure mechanisms, heterogeneous data inputs and dearth of globally-available landslide data for validation make characterizing and modeling these processes over broader spatial and temporal scales very challenging. Global satellite and model data provide a unique perspective to approximate where and when landslides may be occurring at regional to global scales as well as to monitor or map landslide distribution and movement over smaller areas. This presentation will outline several on-going efforts to better characterize landslide activity at different spatial and temporal scales using an array of modeling, mapping and citizen science methods.