Faculty of Information Engineering, China University of Geosciences, Wuhan, China.
Wuhan Regional Climate Centre, Wuhan, China.
Environ Monit Assess. 2018 Feb 9;190(3):129. doi: 10.1007/s10661-018-6499-4.
Floods are among the most expensive natural hazards experienced in many places of the world and can result in heavy losses of life and economic damages. The objective of this study is to analyze flood inundation in ungauged basins by performing near-real-time detection with flood extent and depth based on multi-source remote sensing data. Via spatial distribution analysis of flood extent and depth in a time series, the inundation condition and the characteristics of flood disaster can be reflected. The results show that the multi-source remote sensing data can make up the lack of hydrological data in ungauged basins, which is helpful to reconstruct hydrological sequence; the combination of MODIS (moderate-resolution imaging spectroradiometer) surface reflectance productions and the DFO (Dartmouth Flood Observatory) flood database can achieve the macro-dynamic monitoring of the flood inundation in ungauged basins, and then the differential technique of high-resolution optical and microwave images before and after floods can be used to calculate flood extent to reflect spatial changes of inundation; the monitoring algorithm for the flood depth combining RS and GIS is simple and easy and can quickly calculate the depth with a known flood extent that is obtained from remote sensing images in ungauged basins. Relevant results can provide effective help for the disaster relief work performed by government departments.
洪水是世界上许多地方遭遇的最昂贵的自然灾害之一，可能导致重大生命损失和经济损失。本研究的目的是通过使用多源遥感数据进行洪水范围和深度的近实时检测，分析无测站流域的洪水泛滥情况。通过洪水范围和深度的时间序列空间分布分析，可以反映洪水淹没状况和洪水灾害特征。结果表明，多源遥感数据可以弥补无测站流域的水文数据不足，有助于重建水文序列；MODIS（中等分辨率成像光谱仪）地表反射率产品与 DFO（达特茅斯洪水观测站）洪水数据库的结合，可以实现无测站流域洪水泛滥的宏观动态监测，然后利用洪水前后高分辨率光学和微波图像的差值技术来计算洪水范围，以反映淹没的空间变化；结合 RS 和 GIS 的洪水深度监测算法简单易行，可以快速计算出无测站流域遥感图像中已知洪水范围的深度。相关结果可为政府部门开展的救灾工作提供有效帮助。
