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
影响因子:
4.6
通讯作者:
Wright J
中科院分区:
文献类型:
--
作者:
Li C;Dash J;Asamoah M;Sheffield J;Dzodzomenyo M;Gebrechorkos SH;Anghileri D;Wright J
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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影响因子:
4.3
作者:
Afriyie, Kwadwo;Ganle, John Kuumuori;Santos, Eric
通讯作者:
Santos, Eric
影响因子:
2.2
作者:
Kienberger, Stefan
通讯作者:
Kienberger, Stefan
影响因子:
3.4
作者:
Asare-Kyei, Daniel;Forkuor, Gerald;Venus, Valentijn
通讯作者:
Venus, Valentijn
DOI:
10.1109/jstars.2021.3092340
发表时间:
2021
影响因子:
5.5
作者:
Du J;Kimball JS;Sheffield J;Pan M;Fisher CK;Beck HE;Wood EF
通讯作者:
Wood EF
影响因子:
3.7
作者:
Adnan, Mohammed Sarfaraz Gani;Dewan, Ashraf;Abdullah, Abu Yousuf Md
通讯作者:
Abdullah, Abu Yousuf Md