DocumentCode :
57229
Title :
Near Real-Time Flood Volume Estimation From MODIS Time-Series Imagery in the Indus River Basin
Author :
Youngjoo Kwak ; Jonggeol Park ; Fukami, Kazuhiko
Author_Institution :
Int. Centre for Water Hazard & Risk Manage. (ICHARM), UNESCO, Tsukuba, Japan
Volume :
7
Issue :
2
fYear :
2014
fDate :
Feb. 2014
Firstpage :
578
Lastpage :
586
Abstract :
Satellite images have been widely applied in near real-time flood inundation maps in many cases. Such images have significant potential to predict the time, place and scale of a flood event, and can be very useful in emergency response efforts. The detection of floodwaters and the estimation of flood volumes are important to determine a hazard in flood risk. In this study, we conducted surface water detection based on the spatial distribution of the 2010 Indus River flood, which affected the entire Pakistan area. A modified surface water index derived from near-real-time Moderate Resolution Imaging Spectrometer (MODIS) images coupled with a digital elevation model (DEM) was used. We also developed and applied a simplified algorithm to extract the 3D volume of floodplain surface water considering surface heights. The results found that the MODIS-DEM combined approach was feasible for automatic, instant flood detection. This approach shows a methodological possibility as an integrated algorithm for producing flood maps at local to global scales.
Keywords :
digital elevation models; floods; remote sensing; risk analysis; volume measurement; 3D volume; AD 2010; Indus River Basin; MODIS time series imagery; Moderate Resolution Imaging Spectrometer images; Pakistan; digital elevation model; emergency response; flood inundation maps; flood risk; floodwater detection; near real time flood volume estimation; satellite images; surface water detection; Floods; Indexes; Land surface; MODIS; Remote sensing; Rivers; Volume measurement; DEM; Indus River flood; MODIS; flood volume; water index;
fLanguage :
English
Journal_Title :
Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of
Publisher :
ieee
ISSN :
1939-1404
Type :
jour
DOI :
10.1109/JSTARS.2013.2284607
Filename :
6636079
Link To Document :
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