With numerous technological and organizational advances, the amount of rapidly available information streams surrounding regional impacts after an earthquake has increased dramatically. Specifically, the post-disaster damage is either predicted with rapid loss models, estimated with remote sensing information, or measured through field surveys. SURI is developing a methodology to integrate these data sources to a single spatial distribution of a tangible damage metric which can inform response and recovery decisions.
This is part of a broader collaboration in which we are using the 2015 earthquake in Nepal as a case study to analyze post-disaster damages (disaster-induced losses) and needs (disaster-induced vulnerability).
World Bank Global Facility for Disaster Risk Reduction (GFDRR) and World Bank Big Data Program
NASA Jet Propulsion Lab and Advanced Rapid Imaging and Analysis Center (NASA-JPL/ARIA)
Loos, S., Lallemant, D., Baker, J. W., McCaughery, J., Yun, S.-H., Budhathoki, N., Khan, F., and Singh, R. (2020). “G-DIF: A geospatial data integration framework to rapidly estimate post-earthquake damage.” Earthquake Spectra, (in press).