Increased flooded area and exposure in the White Volta river basin in Western Africa, identified from multi-source remote sensing data.

Increased flooded area and exposure in the White Volta river basin in Western Africa, identified from multi-source remote sensing data.
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DOI:
10.1038/s41598-022-07720-4
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发表时间:
2022-03-08
期刊:
影响因子:
4.6
通讯作者:
Wright J
Wright J
中科院分区:
综合性期刊3区
文献类型:
--
作者:
Li C;Dash J;Asamoah M;Sheffield J;Dzodzomenyo M;Gebrechorkos SH;Anghileri D;Wright J

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关于洪水范围和暴露程度的准确信息对于撒哈拉以南非洲(SSA)等数据稀缺的脆弱地区的灾害管理至关重要。然而,洪水范围的不确定性影响洪水暴露估计。这项研究制定了一个框架,以审查洪水的时空格局,并通过利用卫星图像、地面参与性洪水范围测绘和社会经济数据评估洪水风险。借鉴在西非的白色沃尔特盆地的案例研究,我们的研究结果表明,协同使用多时相雷达和光学卫星数据提高洪水测绘精度(77%的总体协议相比,参与式测绘输出),与现有的全球洪水数据集(43%的总体协议中分辨率成像光谱仪(MODIS)近实时(NRT)全球洪水产品)。根据我们的分类产品以及两种现有的全球洪水产品,观察到洪水范围增加。同样,也观察到洪水风险增加,但其估计仍然高度不确定,对所使用的输入数据集敏感。根据所使用的人口数据集的不同,人口暴露量差异很大,而最大的农田和基础设施暴露量是使用来自三种产品的复合洪水图估计的,每个洪水产品的暴露量较低。该研究表明,有相当大的空间,以开发一个准确的洪水测绘系统,在SSA,从而提高洪水风险评估和制定缓解和干预计划。
Accurate information on flood extent and exposure is critical for disaster management in data-scarce, vulnerable regions, such as Sub-Saharan Africa (SSA). However, uncertainties in flood extent affect flood exposure estimates. This study developed a framework to examine the spatiotemporal pattern of floods and to assess flood exposure through utilization of satellite images, ground-based participatory mapping of flood extent, and socio-economic data. Drawing on a case study in the White Volta basin in Western Africa, our results showed that synergetic use of multi-temporal radar and optical satellite data improved flood mapping accuracy (77% overall agreement compared with participatory mapping outputs), in comparison with existing global flood datasets (43% overall agreement for the moderate-resolution imaging spectroradiometer (MODIS) Near Real-Time (NRT) Global Flood Product). Increases in flood extent were observed according to our classified product, as well as two existing global flood products. Similarly, increased flood exposure was also observed, however its estimation remains highly uncertain and sensitive to the input dataset used. Population exposure varied greatly depending on the population dataset used, while the greatest farmland and infrastructure exposure was estimated using a composite flood map derived from three products, with lower exposure estimated from each flood product individually. The study shows that there is considerable scope to develop an accurate flood mapping system in SSA and thereby improve flood exposure assessment and develop mitigation and intervention plans.
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