Détail de l'auteur
Auteur Abdellah Algouti |
Documents disponibles écrits par cet auteur (1)
Ajouter le résultat dans votre panier Affiner la recherche Interroger des sources externes
Evolution of sand encroachment using supervised classification of Landsat data during the period 1987–2011 in a part of Laâyoune-Tarfaya basin of Morocco / Ali Aydda in Geocarto international, vol 34 n° 13 ([15/10/2019])
[article]
Titre : Evolution of sand encroachment using supervised classification of Landsat data during the period 1987–2011 in a part of Laâyoune-Tarfaya basin of Morocco Type de document : Article/Communication Auteurs : Ali Aydda, Auteur ; Omar F. Althuwaynee, Auteur ; Ahmed Algouti, Auteur ; Abdellah Algouti, Auteur Année de publication : 2019 Article en page(s) : pp 1514 - 1529 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] carte géomorphologique
[Termes IGN] classification barycentrique
[Termes IGN] classification dirigée
[Termes IGN] classification par maximum de vraisemblance
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] dune
[Termes IGN] image Landsat
[Termes IGN] image multitemporelle
[Termes IGN] littoral
[Termes IGN] Maroc
[Termes IGN] sable
[Termes IGN] vent de sableRésumé : (auteur) The study anticipated to understand sand encroachment evolution through analysis of sand contribution across space and time using remote sensing in Laâyoune-Tarfaya basin, Morocco, over the period from 1987 to 2011. The assessment based on supervised classifications of Landsat imagery orthorectified data, using Maximum Likelihood (ML), Minimum Distance (MD) and Support Vector Machine (SVM) classifiers. In order to ameliorate the information, principal components analysis (PCA) and co-occurrence measurement algorithm were used for choosing bands and data transformation. Images differencing was applied on image pairs derived from classification to analyze sand encroachment evolution. All classifiers present enhanced performances, and revealed that area covered by sand was increased by 7%, 4.66% and 4.59% for ML, MD and SVM, respectively. Consequently, images differencing results confirmed that sand material increasing arise not only from coastal area contribution but also mostly from erosion of complicated sand dunes exist in the middle part of the studied area. Evaluating of the presented phenomenon dimensions and its consequences are extremely important to increase the local authorities awareness and mainly for avoiding or minimizing the consequences of the future sand dunes threats. Numéro de notice : A2019-511 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2018.1493154 Date de publication en ligne : 07/09/2018 En ligne : https://doi.org/10.1080/10106049.2018.1493154 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93820
in Geocarto international > vol 34 n° 13 [15/10/2019] . - pp 1514 - 1529[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 059-2019131 RAB Revue Centre de documentation En réserve L003 Disponible