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Potentiality of feed-forward neural networks for classifying dark formations to oil spills and look-alikes / Konstantinos Topouzelis in Geocarto international, vol 24 n° 3 (June - July 2009)  

Public [article]  inGeocarto international > vol 24 n° 3 (June - July 2009) . - pp 179 - 191 Titre : Potentiality of feed-forward neural networks for classifying dark formations to oil spills and look-alikes Type de document : Article/Communication Auteurs : Konstantinos Topouzelis, Auteur ; V. Karathanassi, Auteur ; P. Pavlaskis, Auteur ; D. Rokos, Auteur Année de publication : 2009 Article en page(s) : pp 179 - 191 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] classification par réseau neuronal [Termes IGN] détection [Termes IGN] fonction de base radiale [Termes IGN] hydrocarbure [Termes IGN] image radar [Termes IGN] marée noire [Termes IGN] Perceptron multicouche [Termes IGN] pollution des mers [Termes IGN] rétrodiffusion Résumé : (Auteur) Radar backscatter values from oil spills are very similar to backscatter values from very calm sea areas and other ocean phenomena. Several studies aiming at oil spill detection have been conducted. Most of these studies rely on the detection of dark areas, which have high Bayesian probability of being oil spills. The drawback of these methods is a complex process, mainly because non-linearly separable datasets are introduced in statistically based decisions. The use of neural networks (NNs) in remote sensing has increased significantly, as NNs can simultaneously handle non-linear data of a multidimensional input space. In this article, we investigate the ability of two commonly used feed-forward NN models: multilayer perceptron (MLP) and radial basis function (RBF) networks, to classify dark formations in oil spills and look-alike phenomena. The appropriate training algorithm, type and architecture of the optimum network are subjects of research. Inputs to the networks are the original synthetic aperture radar image and other images derived from it. MLP networks are recognized as more suitable for oil spill detection. Numéro de notice : A2009-186 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106040802488526 Date de publication en ligne : 19/05/2009 En ligne : https://doi.org/10.1080/10106040802488526 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29816 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
059-09031	RAB	Revue	Centre de documentation	En réserve L003	Disponible

Assessing image processing techniques for geological mapping: a case study in Eljufra, Libya / N.M. Saadi in Geocarto international, vol 24 n° 3 (June - July 2009)  

Public [article]  inGeocarto international > vol 24 n° 3 (June - July 2009) . - pp 241 - 253 Titre : Assessing image processing techniques for geological mapping: a case study in Eljufra, Libya Type de document : Article/Communication Auteurs : N.M. Saadi, Auteur ; K. Watanabe, Auteur Année de publication : 2009 Article en page(s) : pp 241 - 253 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] carte géologique [Termes IGN] fusion d'images [Termes IGN] géologie locale [Termes IGN] image ERS-SAR [Termes IGN] image Landsat-ETM+ [Termes IGN] linéament [Termes IGN] lithologie [Termes IGN] MNS SRTM [Termes IGN] réponse spectrale [Termes IGN] tectonique des plaques [Termes IGN] traitement d'image [Termes IGN] zone aride Résumé : (Auteur) Various image processing techniques were experimented with in this study to evaluate their efficiency for geological mapping in the Eljufra area of northwest Libya. Remote sensing data including multi-spectral optical Landsat Enhanced Thematic Mapper (ETM+), Synthetic Aperture Radar (ERS-2 SAR) and Digital Elevation Models (DEMs) extracted from the Shuttle Radar Topography Mission (SRTM) data were used to trace different lithological units as well as extracting geological lineaments in the study area. The study area is located in an arid environment mostly devoid of any vegetation. Most lithological and structural units are distinguishable based on their topographic form and spectral properties. Fusion of ETM+ and ERS-2 images was experimented with to further identify lithological units. Shaded relief techniques were implemented to enhance terrain perspective views and to extract geological lineaments. The results discriminated different rock units and modified formation boundaries and revealed new geological lineaments. Nine rock units were identified and plotted in the new geological map defined by the new boundaries. The dominant lineaments tend to run in the NNW-SSE and NNE-SSW directions. Analysis and interpretation of the lineaments provided information about the tectonic evolution of the study area. Copyright Taylor & Francis Numéro de notice : A2009-187 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106040802556199 Date de publication en ligne : 19/05/2009 En ligne : https://doi.org/10.1080/10106040802556199 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29817 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
059-09031	RAB	Revue	Centre de documentation	En réserve L003	Disponible