Skakun Sergii, Kussul Nataliia, Shelestov Andrii, Kussul Olga
Space Research Institute NASU-SSAU, Kyiv, 03680, Ukraine; National University of Life and Environmental Sciences of Ukraine, Kyiv, 03680, Ukraine.
Risk Anal. 2014 Aug;34(8):1521-37. doi: 10.1111/risa.12156. Epub 2013 Dec 24.
In this article, the use of time series of satellite imagery to flood hazard mapping and flood risk assessment is presented. Flooded areas are extracted from satellite images for the flood-prone territory, and a maximum flood extent image for each flood event is produced. These maps are further fused to determine relative frequency of inundation (RFI). The study shows that RFI values and relative water depth exhibit the same probabilistic distribution, which is confirmed by Kolmogorov-Smirnov test. The produced RFI map can be used as a flood hazard map, especially in cases when flood modeling is complicated by lack of available data and high uncertainties. The derived RFI map is further used for flood risk assessment. Efficiency of the presented approach is demonstrated for the Katima Mulilo region (Namibia). A time series of Landsat-5/7 satellite images acquired from 1989 to 2012 is processed to derive RFI map using the presented approach. The following direct damage categories are considered in the study for flood risk assessment: dwelling units, roads, health facilities, and schools. The produced flood risk map shows that the risk is distributed uniformly all over the region. The cities and villages with the highest risk are identified. The proposed approach has minimum data requirements, and RFI maps can be generated rapidly to assist rescuers and decisionmakers in case of emergencies. On the other hand, limitations include: strong dependence on the available data sets, and limitations in simulations with extrapolated water depth values.
本文介绍了利用卫星图像时间序列进行洪水灾害制图和洪水风险评估的方法。从卫星图像中提取洪水易发生地区的淹没区域，并为每个洪水事件生成最大洪水范围图像。这些地图进一步融合以确定淹没相对频率（RFI）。研究表明，RFI值和相对水深呈现相同的概率分布，这通过柯尔莫哥洛夫-斯米尔诺夫检验得到证实。生成的RFI地图可作为洪水灾害地图，特别是在洪水建模因缺乏可用数据和高不确定性而变得复杂的情况下。导出的RFI地图进一步用于洪水风险评估。本文所提出方法的有效性在卡蒂马穆利洛地区（纳米比亚）得到了验证。利用本文提出的方法对1989年至2012年获取的一系列陆地卫星5/7号卫星图像进行处理，以导出RFI地图。本研究在洪水风险评估中考虑了以下直接损失类别：住宅单元、道路、卫生设施和学校。生成的洪水风险地图显示，风险在整个区域均匀分布。确定了风险最高的城市和村庄。所提出的方法数据要求最低，并且可以快速生成RFI地图，以便在紧急情况下协助救援人员和决策者。另一方面，局限性包括：强烈依赖可用数据集，以及在外推水深值的模拟中存在局限性。
