1 August 2014 Weekly flood monitoring with multitemporal moderate resolution imaging spectroradiometer data using water fraction model
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Abstract
Flood is one of the most devastating and frequent disasters. Information on spatiotemporal flood dynamics is essential for planners to devise successful strategies for flood monitoring and mitigation of its negative effects. This study aimed to develop an approach for weekly monitoring of floods with the moderate resolution imaging spectroradiometer (MODIS) data in the Mekong River Delta, South Vietnam, using the water fraction model (WFM). We processed the data for 2009 and 2010 through three main steps: (1) data preprocessing to construct a smooth time series of the difference in the values between land surface water index and enhanced vegetation index, (2) flood derivation using WFM, and (3) accuracy assessment. The results compared to the ground reference data indicated satisfactory results with the overall accuracies and Kappa coefficients of 81.1% and 0.62 for 2009 and 80.3% and 0.61 for 2010, respectively. These results were reaffirmed by a close correlation between the MODIS-derived flood area and that of the ground reference map at the provincial level, with the correlation coefficients (R2) of 0.88 for 2009 and 0.83 for 2010. The results also confirmed the earlier arrival and greater intensity of floods in 2009 compared to 2010.
© 2014 Society of Photo-Optical Instrumentation Engineers (SPIE) 0091-3286/2014/$25.00 © 2014 SPIE
Nguyen-Thanh Son, Chi-Farn Chen, and Cheng-Ru Chen "Weekly flood monitoring with multitemporal moderate resolution imaging spectroradiometer data using water fraction model," Journal of Applied Remote Sensing 8(1), 083581 (1 August 2014). https://doi.org/10.1117/1.JRS.8.083581
Published: 1 August 2014
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KEYWORDS
Floods

MODIS

Data modeling

Earth observing sensors

Image resolution

Landsat

Associative arrays

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