• DocumentCode
    1540923
  • Title

    Remote Sensing Contributions to Prediction and Risk Assessment of Natural Disasters Caused by Large-Scale Rift Valley Fever Outbreaks

  • Author

    Anyamba, Assaf ; Linthicum, Kenneth J. ; Small, Jennifer ; Britch, Seth C. ; Tucker, Compton J.

  • Author_Institution
    NASA Goddard Space Flight Center, Univ. Space Res. Assoc., Greenbelt, MD, USA
  • Volume
    100
  • Issue
    10
  • fYear
    2012
  • Firstpage
    2824
  • Lastpage
    2834
  • Abstract
    Remotely sensed vegetation measurements for the last 30 years combined with other climate data sets such as rainfall and sea surface temperatures have come to play an important role in the study of the ecology of arthropod-borne diseases. We show that epidemics and epizootics of previously unpredictable Rift Valley fever (RVF) are directly influenced by large-scale flooding associated with the El Niño/Southern Oscillation (ENSO). This flooding affects the ecology of disease transmitting arthropod vectors through vegetation development and other bioclimatic factors. This information is now utilized to monitor, model, and map areas of potential RVF outbreaks and is used as an early warning system for risk reduction of outbreaks to human and animal health, trade, and associated economic impacts. The continuation of such satellite measurements is critical to anticipating, preventing, and managing disease epidemics and epizootics and other climate-related disasters.
  • Keywords
    El Nino Southern Oscillation; climatology; disasters; diseases; ecology; epidemics; ocean temperature; rain; remote sensing; risk management; vegetation; ENSO; El Niño/Southern Oscillation; RVF outbreaks; arthropod-borne diseases; bioclimatic factors; climate data sets; climate-related disasters; disease epidemics; disease transmitting arthropod vectors; early warning system; ecology; epizootics; large-scale Rift Valley fever outbreaks; large-scale flooding; natural disaster prediction; natural disaster risk assessment; rainfall; remote sensing contributions; sea surface temperatures; vegetation development; vegetation measurements; Disaster management; Diseases; Meteorology; Predictive models; Remote sensing; Risk management; Vegetation mapping; Arthropod-borne virus; El Niño/Southern Oscillation (ENSO); Rift Valley fever virus (RVFV); climate variability; normalized difference vegetation index; predictive model; risk management and mitigation;
  • fLanguage
    English
  • Journal_Title
    Proceedings of the IEEE
  • Publisher
    ieee
  • ISSN
    0018-9219
  • Type

    jour

  • DOI
    10.1109/JPROC.2012.2194469
  • Filename
    6218155