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Evaluation of a spatially adaptive approach for land surface classification from digital elevation models / Maria Dekavalla in International journal of geographical information science IJGIS, vol 31 n° 9-10 (September - October 2017)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 31 n° 9-10 (September - October 2017) . - pp 1978 - 2000 Titre : Evaluation of a spatially adaptive approach for land surface classification from digital elevation models Type de document : Article/Communication Auteurs : Maria Dekavalla, Auteur ; Demetre Argialas, Auteur Année de publication : 2017 Article en page(s) : pp 1978 - 2000 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes IGN] classification [Termes IGN] géomorphométrie [Termes IGN] information sémantique [Termes IGN] modèle numérique de surface [Termes IGN] modélisation spatiale [Termes IGN] morphologie [Termes IGN] photogrammétrie spatiale [Termes IGN] relief Résumé : (Auteur) Classification of land surface to landforms is fundamental to interpretation of various environmental processes. The heterogeneous landform descriptions and classification approaches, in combination with the scale dependence of digital elevation models (DEMs) and their products, defy the development of an interoperable and transferable automated landform classification approach. A theoretical framework has proposed that land surface should be regionalised to morphologic meaningful objects, delimited by discontinuities (i.e. slope breaks and inflections) and subsequently classified with morphometric and contextual criteria. However, an automated methodology meeting these conditions is still lacking. This study is an attempt to automate this framework through the investigation of a modified version of a spatially adaptive pattern-based approach and its potential to produce morphologic meaningful objects of various shapes and sizes, present at the given DEM resolution. These objects were classified to 15 landform element classes based on semantic descriptions, including criteria of morphometry, relative topographic position and topological relations. Results were visually analysed by draping them over DEMs and contours and quantitatively assessed with fuzzy classification tools. The modified pattern-based approach was proven to be efficient for delineation of morphologic meaningful objects in DEMs. The classification approach was transferable to various landscapes and DEM resolutions, given that it uses spatially flexible fuzzy criteria. Numéro de notice : A2017-507 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2017.1344984 En ligne : http://dx.doi.org/10.1080/13658816.2017.1344984 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=86453 [article]

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