부산대학교 도서관

Flooding is one of the most prevalent and costliest global disasters. Disaster managers face significant challenges in managing essential information for preparedness, response, and recovery efforts. The development of an open access global flood alerting system for effective classification of potential impacts and the formulation of effective emergency response measures requires the incorporation of a wide variety of flood outputs derived from hydrologic and hydraulic models as well as from remote sensing derived data sets from multiple satellite/sensor platforms. We seek to rapidly classify flood severity using a model of models (MoM) approach that leverages products of existing flood models and incorporates Synthetic Aperture Radar (SAR) derived outputs for ground-truthing of model results and delineation of flood impact areas. The flood severity classification along with potential impacts estimated by using optical imagery will be disseminated as alerts using the Pacific Disaster Center's DisasterAWARE® decision support platform to users globally.