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Automated detection of lineaments express geological linear features of a tropical region using topographic fabric grain algorithm and the SRTM DEM / Samy Ismail Elmahdy in Geocarto international, vol 36 n° 1 ([01/01/2021])  

Public [article]  inGeocarto international > vol 36 n° 1 [01/01/2021] . - pp 76 - 95 Titre : Automated detection of lineaments express geological linear features of a tropical region using topographic fabric grain algorithm and the SRTM DEM Type de document : Article/Communication Auteurs : Samy Ismail Elmahdy, Auteur ; Mohamed Mostafa Mohamed, Auteur ; Tarig A Ali, Auteur Année de publication : 2021 Article en page(s) : pp 76 - 95 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] carte géologique [Termes IGN] linéament [Termes IGN] Malaisie [Termes IGN] milieu tropical [Termes IGN] MNS SRTM [Termes IGN] modèle numérique de surface [Termes IGN] structure géologique Résumé : (Auteur) The availability of the large volume of remote sensing data has allowed for the developing of several automated algorithms for detecting linear geological features and more reliable analysis. However, most of the algorithms focus on edge detection and tone change on a satellite image, which represents all geological and non-geological features. In this study, a topographic fabric algorithm, which calculates the slope and aspect at each point in a DEM, is applied for automatically geological linear features mapping in Bau Goldfield, Malaysia using the new version of the Shuttle Radar Topographic Mission (SRTM) DEM. A series of topographic fabric input parameters was tested using different combinations of input values in order to decide the optimal parameters that provided the suitable detection parameters, best fit and the highest accuracy. Comparison with the geological map demonstrated that the tested parameters made the algorithm able to automatically detect geological structures. Numéro de notice : A2021-052 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2019.1594393 Date de publication en ligne : 29/05/2019 En ligne : https://doi.org/10.1080/10106049.2019.1594393 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96776 [article]

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