one publication added to basket [382868] | Monitoring of a coastal protection scheme through satellite remote sensing: a case study in Ghana
das Neves, L.; Andrade, C.; Sarmento, M.F.; Rosa-Santos, P. (2023). Monitoring of a coastal protection scheme through satellite remote sensing: a case study in Ghana. J. Mar. Sci. Eng. 11(9): 1771. https://dx.doi.org/10.3390/jmse11091771
In: Journal of Marine Science and Engineering. MDPI: Basel. ISSN 2077-1312; e-ISSN 2077-1312
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shoreline monitoring; CoastSat; disaster risk reduction; climate change adaptation; West Africa; the Volta Delta; satellite imagery; groynes |
Authors | | Top |
- das Neves, L.
- Andrade, C.
- Sarmento, M.F.
- Rosa-Santos, P.
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Abstract |
Earth observation can provide managers with valuable information on ongoing coastal processes and major trends in coastline evolution, especially in data-poor regions. This paper examines the use of optical satellite images in the mapping of the changes in shoreline position before, during, and after the implementation of a protection scheme. The aim of this paper is twofold: (i) to demonstrate the potential of satellite imagery as an effective, robust, and low-cost tool to remotely monitor the effectiveness of protective structures based on a large-scale case study in West Africa; and (ii) to compile lessons learned from this case study that can be used in the design of future interventions. The analysis shows that before the implementation of the protection scheme, the coastal sector was retreating at a rate of −1.6 m/year, which is in line with the average retreat rates reported in other studies for the region. After project implementation, this trend reversed into shoreline accretion at a rate of +1.0 m/year, locally experiencing positive and negative oscillations in the short term. Furthermore, the shoreline-extracted positions proved useful in assessing the impact of differences in the groynes’ permeability with respect to temporary leeside erosion. Finally, it is recommended to continue this monitoring to assess long-term trends.
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