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
Link To Document :
بازگشت