Please use this identifier to cite or link to this item: http://repositorio.lnec.pt:8080/jspui/handle/123456789/1010042
Title: Cera: an open-source tool for coastal erosion risk assessment
Authors: Narra, P.
Coelho, C.
Sancho, F. E.
Palalane, J.
Keywords: Vulnerability;Consequence;Hazard;Exposure;GIS;Aveiro;Macaneta
Issue Date: Jun-2017
Publisher: Elsevier
Citation: https://doi.org/10.1016/j.ocecoaman.2017.03.013
Abstract: Coastal zones are socially and economically very important, leading to a high pressure for its permanent development. Simultaneously, these zones are subject to several maritime hazards, able to cause coastal erosion. Therefore, a thoughtful management of these zones is required in order to protect society, economy and natural environments. This work presents a GIS-based tool that aims to provide a quick assessment to coastal erosion risk, called CERA: Coastal Erosion Risk Assessment. The simple processes and small amount of data required by the tool provides a viable alternative to other methods, which are often more complex and difficult to apply. The assessment method used in CERA is divided in two parts. The first part is a vulnerability assessment, which combines several parameters that influence coastal erosion, each being classified in a scale of 1e5. The second part, a consequence assessment, follows the same procedure, but considering socio-economic aspects. Then, a risk matrix is applied to determine a risk classification, also divided in 5 classes, from I to V. Aveiro, in Portugal, and Macaneta spit, in Mozambique, were selected to test the application. Data was gathered for both locations. While in Aveiro it was used a considerable amount of available georeferenced data, for the Macaneta spit the data was mainly prevenient from previous publications and local expert knowledge. The results show that both study areas have similar vulnerabilities to coastal erosion, with classes IV and V dominating along the areas closer to the shoreline. On the other hand, the consequence classification in Aveiro is higher than in Macaneta, resulting in a higher risk level in several regions in Aveiro district. The higher level of detail in Aveiro data also resulted in a more even distribution across all class levels in the results. ©
URI: https://repositorio.lnec.pt/jspui/handle/123456789/1010042
Appears in Collections:DHA/NEC - Comunicações a congressos e artigos de revista

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