Journal cover Journal topic
Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
doi:10.5194/hess-2016-560
© Author(s) 2016. This work is distributed
under the Creative Commons Attribution 3.0 License.
Research article
01 Nov 2016
Review status
A revision of this discussion paper is under review for the journal Hydrology and Earth System Sciences (HESS).
A Multi-sensor Data-driven methodology for all-sky Passive Microwave Inundation Retrieval
Zeinab Takbiri1,2, Ardeshir M. Ebtehaj1, and Efi Foufoula-Georgiou1,3 1Department of Civil, Environmental and Geo-Engineering and St. Anthony Falls Laboratory, University of Minnesota, Twin Cities, Minneapolis, USA
2Department of Electrical and Computer Engineering, University of Minnesota, Twin Cities, Minneapolis, USA
3Department of Civil and Environmental Engineering, University of California, Irvine, USA
Abstract. We present a multi-sensor Bayesian passive microwave retrieval algorithm for flood inundation mapping at high spatial and temporal resolutions. The algorithm takes advantage of observations from multiple sensors in optical, short-infrared, and microwave bands, thereby allowing detection and mapping of the sub-pixel fraction of inundated areas under almost all-sky conditions. The method relies on a nearest neighbor search and a modern sparsity-promoting inversion method that make use of an a priori database in the form of two joint dictionaries. These dictionaries contain almost overlapping observations by the Special Sensor Microwave Imager and Sounder (SSMIS) on board the Defense Meteorological Satellite Program (DMSP) F17 satellite and the Moderate Resolution Imaging Spectroradiometer (MODIS) on board the Aqua and Terra satellites. Evaluation of the retrieval algorithm over the Mekong delta shows that it is capable of capturing to a good degree the diurnal variability (i.e., morning and evening) of inundation due to localized convective precipitation. At longer time-scales, the results demonstrate consistency with the ground-based water level observations, denoting that the method is properly capturing inundation seasonal patterns in response to regional monsoonal rain. The calculated Euclidean distance, rank-correlation and also Copula quantile analysis demonstrate a good agreement between the outputs of the algorithm and the observed water levels at monthly and daily time scales.

Citation: Takbiri, Z., Ebtehaj, A. M., and Foufoula-Georgiou, E.: A Multi-sensor Data-driven methodology for all-sky Passive Microwave Inundation Retrieval, Hydrol. Earth Syst. Sci. Discuss., doi:10.5194/hess-2016-560, in review, 2016.
Zeinab Takbiri et al.
Zeinab Takbiri et al.

Data sets

An earth-gridded SSM/I data set for cryospheric studies and global change monitoring
R. L. Armstrong and M. J. Brodzik
doi:10.1016/0273-1177(95)00397-W
Zeinab Takbiri et al.

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Short summary
We present a multi-sensor retrieval algorithm for the flood extent mapping at high spatial and temporal resolution. While visible bands provide flood mapping at fine spatial resolution, their capability is very limited in a cloudy sky. Passive microwaves can penetrate through clouds but cannot detect small-scale flooded surfaces due to their coarse resolution. The proposed method takes the advantage of these two observations to retrieve sub-pixel flooded surfaces in all-sky condition.
We present a multi-sensor retrieval algorithm for the flood extent mapping at high spatial and...
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