ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Volume VI-3/W1-2020
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., VI-3/W1-2020, 107–113, 2020
https://doi.org/10.5194/isprs-annals-VI-3-W1-2020-107-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., VI-3/W1-2020, 107–113, 2020
https://doi.org/10.5194/isprs-annals-VI-3-W1-2020-107-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

  17 Nov 2020

17 Nov 2020

DisasterAWARE – A GLOBAL ALERTING PLATFORM FOR FLOOD EVENTS

P. Sharma1, J. Wang2, M. Zhang1, C. Woods3, B. Kar4, D. Bausch5, Z. Chen1, K. Tiampo3, M. Glasscoe6, G. Schumann7, M. Pierce2, and R. Eguchi8 P. Sharma et al.
  • 1School of computing and engineering, University of Missouri, Kansas City, Kansas City, MO 64110, USA
  • 2Cyberinfrastructure Integration Research Center, Indiana University, Bloomington, IN 47405, USA
  • 3Geological Sciences, University of Colorado, Boulder, CO 80309, USA
  • 4Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
  • 5Pacific Disaster Center, Kihei, HI 96753, USA
  • 6Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109, USA
  • 7Dartmouth Flood Observatory, Hanover, NH 03755, USA
  • 8ImageCat Inc., Long Beach, CA 90802, USA

Keywords: Flood forecasting, Alerting, Synthetic Aperture Radar, Model of Models, Impact Assessment, Geospatial Data Fusion

Abstract. The rising number of flooding events combined with increased urbanization is contributing to significant economic losses due to damages to structures and infrastructures. From a risk reduction and resilience perspective, it is not only essential to forecast flood risk and potential impacts, but also to disseminate the information to stakeholders on the ground for rapid implementation of mitigation and response measures. This paper provides (i) an introduction to DisasterAWARE®, a global alerting system, that is used to disseminate flood risk information to stakeholders across the globe, and (ii) a discussion of the models implemented using earth observation data (Synthetic Aperture Radar and optical imagery) for near real-time assessment of flood severity and potential flood impacts to infrastructures. While the models are still in their nascent stage, a case study implementation of the models for the 2020 flooding event in Africa is presented to showcase the model integration with DisasterAWARE®.