Publication
Landslide susceptibility assessment in rocky coast subsystem of Essaouira coastal area - Morocco
| datacite.subject.sdg | 11:Cidades e Comunidades Sustentáveis | pt_PT |
| dc.contributor.author | Khouz, Abdellah | |
| dc.contributor.author | Trindade, Jorge | |
| dc.contributor.author | Oliveira, Sérgio | |
| dc.contributor.author | El Bchari, Fatima | |
| dc.contributor.author | Bougadir, Blaid | |
| dc.contributor.author | Garcia, Ricardo | |
| dc.contributor.author | Jadoud, Mourad | |
| dc.date.accessioned | 2022-12-19T10:08:21Z | |
| dc.date.available | 2022-12-19T10:08:21Z | |
| dc.date.issued | 2022 | |
| dc.description.abstract | In recent decades, multiple researchers have produced landslide susceptibility maps using different techniques and models, including the information value method, which is a statistical model that is widely applied to various coastal environments. This study aimed to evaluate the susceptibility to landslides in the Essaouira coastal area using bivariate statistical methods. In this study, 588 distinct landslides were identified, inventoried, and mapped. They primarily result from the observation and interpretation of different data sources, namely, high-resolution satellite images, aerial photographs, topographic maps, and extensive field surveys. The rocky coastal system of Essaouira is located in the middle of the Atlantic coast of Morocco. The study area was split into 1534 cliff terrain units 50 m in width. For training and validation purposes, the landslide inventory was divided into two independent groups: 70% for training and 30% for validation. Twenty-two layers of landslide-conditioning factors were prepared, namely elevation, slope angle, slope aspect, plan curvature, profile curvature, cliff height, topographic wetness index, topographic position index, slope over area ratio, solar radiation, presence of faulting, lithological units, toe lithology, presence and type of cliff toe protection, layer tilt, rainfall, streams, land-use patterns, normalized difference vegetation index, lithological material grain size, and presence of springs. The statistical relationship between the conditioning factors and different landslide types was calculated using the bivariate information value method in a pixel and in the elementary terrain units-based model. Coastal landside susceptibility maps were validated using landslide training group partitions. The receiver operating characteristic curve and area under the curve were used to assess the accuracy and prediction capacity of the different coastal landslide susceptibility models. Two methodologies, considering a pixel-based approach and using coastal terrain units, were adopted to evaluate coastal landslide susceptibility. The results allowed for the classification of 38% of the rocky coast subsystem with high susceptibility to landslides, which were mostly located in the southern part of the Essaouira coastal area. These susceptibility maps will be useful for future planned development activities as well as for environmental protection. | pt_PT |
| dc.description.version | info:eu-repo/semantics/submittedVersion | pt_PT |
| dc.identifier.doi | 10.5194/nhess-2022-76 | pt_PT |
| dc.identifier.uri | http://hdl.handle.net/10400.2/12755 | |
| dc.language.iso | eng | pt_PT |
| dc.peerreviewed | yes | pt_PT |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | pt_PT |
| dc.subject | Coastal landslide susceptibility mapping | pt_PT |
| dc.subject | Coastal landslide inventory | pt_PT |
| dc.subject | Conditioning factors | pt_PT |
| dc.subject | Information value | pt_PT |
| dc.subject | Essaouira coastal area | pt_PT |
| dc.subject | Morocco | pt_PT |
| dc.title | Landslide susceptibility assessment in rocky coast subsystem of Essaouira coastal area - Morocco | pt_PT |
| dc.type | journal article | |
| dspace.entity.type | Publication | |
| oaire.citation.title | Natural Hazards and Earth System Sciences | pt_PT |
| person.familyName | Khouz | |
| person.familyName | Trindade | |
| person.givenName | Abdellah | |
| person.givenName | Jorge | |
| person.identifier.ciencia-id | 911C-D5A7-F284 | |
| person.identifier.ciencia-id | 1411-A43D-9266 | |
| person.identifier.orcid | 0000-0003-4514-5281 | |
| person.identifier.orcid | 0000-0001-5610-5942 | |
| person.identifier.rid | M-9060-2013 | |
| person.identifier.scopus-author-id | 7003458343 | |
| rcaap.rights | openAccess | pt_PT |
| rcaap.type | article | pt_PT |
| relation.isAuthorOfPublication | f48eeb3f-121f-4cf3-b894-ccbaf2f901b3 | |
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| relation.isAuthorOfPublication.latestForDiscovery | ab80ebde-e734-424d-9df2-a211973d5827 |