DOI: 10.5194/hess-21-2685-2017
Scopus记录号: 2-s2.0-85020463886
论文题名: A multi-sensor data-driven methodology for all-sky passive microwave inundation retrieval
作者: Takbiri Z ; , Ebtehaj A ; M ; , Foufoula-Georgiou E
刊名: Hydrology and Earth System Sciences
ISSN: 10275606
出版年: 2017
卷: 21, 期: 6 起始页码: 2685
结束页码: 2700
语种: 英语
Scopus关键词: Flood control
; Floods
; Image reconstruction
; Image retrieval
; Mapping
; Microwaves
; Nearest neighbor search
; Precipitation (meteorology)
; Radiometers
; Rain
; Satellite imagery
; Satellites
; Water levels
; Convective precipitation
; Defense Meteorological Satellite Programs
; Flood inundation mappings
; Global precipitation missions
; Moderate resolution imaging spectroradiometer
; Retrieval algorithms
; Spatial and temporal resolutions
; Special sensor microwave imagers
; Microwave sensors
; algorithm
; Aqua (satellite)
; data set
; diurnal variation
; imaging method
; MODIS
; pixel
; sensor
; SSM-I
; Terra (satellite)
; timescale
; Mekong Delta
; Viet Nam
英文摘要: 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 for 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 dataset 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 inundation diurnal variability due to localized convective precipitation. At longer timescales, 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 timescales. The current inundation products are at a resolution of 12.5 km and taken twice per day, but a higher resolution (order of 5 km and every 3 h) can be achieved using the same algorithm with the dictionary populated by the Global Precipitation Mission (GPM) Microwave Imager (GMI) products. © Author(s) 2017. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/79162
Appears in Collections: 气候变化事实与影响
There are no files associated with this item.
作者单位: Department of Civil, Environmental and Geo- Engineering, St. Anthony Falls Laboratory, University of Minnesota, Twin Cities, Minneapolis, MN, United States; Department of Civil and Environmental Engineering, University of California, Irvine, CA, United States
Recommended Citation:
Takbiri Z,, Ebtehaj A,M,et al. A multi-sensor data-driven methodology for all-sky passive microwave inundation retrieval[J]. Hydrology and Earth System Sciences,2017-01-01,21(6)