A generic index to assess the building exposure to shoreline retreat using box segmentation: Case study of the Pays de la Loire sandy coast (west of France)

Abstract : Coastal zones are exposed to natural hazards in the context of global change and the concentration of human activities, which justifies the interest in assessing at-risk territories. This paper proposes a reproducible method to identify the erosion risk territories on the basis of an exposure index creation. An assessment of the building exposure to shoreline retreat is conducted along 350 km of the Atlantic French coast (Pays de la Loire regional administrative division) including rocky coasts, coastal barriers and sand spits, estuaries, bays, and coasts with protection structures. The segmentation of a 100-m landward strip is carried out with 30*100 m boxes. Three geoindicators are computed within each box: (i) the shortest shoreline-building distance (ii) the building footprint of the first row (iii) the coastal erosion along sandy coasts. The aggregation of these geoindicators within each box leads to the creation of an exposure index. Thus, this spatial framework provides a reproducible method to improve the synthetic knowledge of the erosion risk in the Pays de la Loire Region. The whole of the risk situation is detected at 1/5000 scale, which is original and significant progress. The accuracy of this study is due to the generic data used and the 30*100 m segmentation. This spatial resolution leads to finer results than previous studies. This new method can detect all the exposures in order to anticipate crises management through the deployment of a real operational alert system.
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Submitted on : Wednesday, January 10, 2018 - 10:25:23 AM
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Martin Juigner, Marc Robin, Françoise Debaine, Florian Hélen. A generic index to assess the building exposure to shoreline retreat using box segmentation: Case study of the Pays de la Loire sandy coast (west of France). Ocean & Coastal Management, 2017, 148, pp.40 - 52. ⟨10.1016/j.ocecoaman.2017.07.014⟩. ⟨hal-01677917⟩

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