A multi-sensor data-driven methodology for all-sky passive microwave inundation retrieval
A multi-sensor data-driven methodology for all-sky passive microwave inundation retrieval
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DOI：
10.5194/hess-21-2685-2017
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发表时间：
2017-06-08
影响因子：
6.3
通讯作者：
Foufoula-Georgiou, Efi
中科院分区：
文献类型：
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作者：
Takbiri, Zeinab;Ebtehaj, Ardeshir M.;Foufoula-Georgiou, Efi
我们提出了一种多传感器贝叶斯被动微波检索算法，用于高空间和时间分辨率的洪水淹没绘图。该算法利用光学、短红外和微波波段多个传感器的观测结果，从而可以在几乎全天空条件下检测和绘制淹没区域的亚像素部分。该方法依赖于最近邻搜索和现代稀疏性促进反演方法，该方法利用两个联合字典形式的先验数据集。这些词典包含国防气象卫星计划 (DMSP) F17 卫星上的特殊传感器微波成像仪和发声器 (SSMIS) 以及 Aqua 和 Terra 卫星上的中分辨率成像光谱仪 (MODIS) 几乎重叠的观测结果。对湄公河三角洲反演算法的评估表明，它能够很好地捕捉局部对流降水引起的淹没日变化。在较长的时间尺度上，结果表明与地面水位观测结果一致，表明该方法正确捕获了响应区域季风降雨的洪水季节模式。计算出的欧几里德距离、等级相关性以及联结分位数分析表明算法的输出与每月和每日时间尺度上观测到的水位之间具有良好的一致性。目前的淹没产品分辨率为 12.5 公里，每天拍摄两次，但使用与全球降水任务 (GPM) 微波成像仪 (GMI) 产品填充的字典相同的算法，可以实现更高分辨率（5 公里量级，每 3 小时一次）。
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.