2020
DOI: 10.9734/ajgr/2020/v3i230101
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Contribution of Sentinel 1 Radar Data to Flood Mapping in the San-Pédro River Basin (South-west Côte d’Ivoire)

Abstract: Floods result from the overflow of water which submerges the surrounding land. They are frequent on the coast of Côte d'Ivoire during the rainy season and have more or less serious consequences on the populations, property and the environment. The study site is the San Pedro river basin. It is a coastal catchment area characterized by an average annual rainfall of up to 2000 mm and subject to recurrent flooding. The objective of this study is to assess the risk of flooding during the great rainy season of 2017… Show more

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Cited by 5 publications
(8 citation statements)
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“…The characterization of the flood hazard, carried out using the thresholding his- October 2020 in the locality of Grand-Bassam. Similar studies carried out by [6] in San-Pédro also showed heavy flooded areas. These are areas of economic and social interest marked by the presence of habitats and industrial and food crops.…”
Section: Discussionsupporting
confidence: 82%
See 1 more Smart Citation
“…The characterization of the flood hazard, carried out using the thresholding his- October 2020 in the locality of Grand-Bassam. Similar studies carried out by [6] in San-Pédro also showed heavy flooded areas. These are areas of economic and social interest marked by the presence of habitats and industrial and food crops.…”
Section: Discussionsupporting
confidence: 82%
“…The advantage of this filter lies in its ability to effectively reduce speckles in homogeneous and heterogeneous areas and to conserve both K. H. Kouassi et al DOI: 10.4236/ars.2020.94007 121 Advances in Remote Sensing the spatial resolution and the reflectivity levels of targets or isolated heterogeneous structures[8]. This filter is one of the filters best suited to processing multipolarized SAR images[6] [9][10]. It was possible to isolate the flood zones by simply thresholding the numerical values of the radar backscatter coefficient.…”
mentioning
confidence: 99%
“…Using Conversion Tools, the flood depth raster converted into a point (shapefile), in which this point will have a flood depth elevation value. Inside the attribute table of flood depth point shapefile, this value is multiplied with the raster size (e.g., 30.1595 m × 30.1595 m). The result represents the flood volume per-point or per-cell.…”
Section: • Flood Volume Calculationmentioning
confidence: 99%
“…The inland water bodies could be detected after thorough processing of certain algorithms using infrared (IR), short-wave infrared (SWIR) bands [26], and global navigation satellite system reflectometry (GNSS-R) [27][28][29]. Kouassi et al [30] mapped the devastating flood in South-west Cote d'Ivoire during the high rainfall season in 2017. Tavus et al [31] used the Sentinel-1 data to map the flood in Ankara, Turkey, and provide high accuracy.…”
Section: Introductionmentioning
confidence: 99%
“…The use of Radar in flood studies in Africa has been growing over the years (Barasa & Wanyama, 2020;Dada et al, 2020;DeVries et al, 2020;Di Baldassarre et al, 2011;Lundberg, 2020;Rebelo, 2010;Rosenqvist et al, 1999). However, its use in Western Africa for monitoring flood events is just emerging (Dada et al, 2020;Frappart et al, 2015;Kouassi et al, 2020). This study, therefore, is aimed at assessing the 2018 flood event in Lokoja, Kogi State, Nigeria, using the Dual Polarimetric Synthetic Aperture Radar (SAR) imagery, a European Space Agency (ESA) product, for effective flood risk assessment and management.…”
Section: Introductionmentioning
confidence: 99%