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Fusion of multi-spectral SPOT-5 images and very high resolution texture information extracted from digital orthophotos for automatic classification of complex Alpine areas / C. Mariz in International Journal of Remote Sensing IJRS, vol 30 n°11-12 (June 2009)  

Public [article]  inInternational Journal of Remote Sensing IJRS > vol 30 n°11-12 (June 2009) . - pp 2859 - 2873 Titre : Fusion of multi-spectral SPOT-5 images and very high resolution texture information extracted from digital orthophotos for automatic classification of complex Alpine areas Type de document : Article/Communication Auteurs : C. Mariz, Auteur ; D. Gianelle, Auteur ; et al., Auteur Année de publication : 2009 Article en page(s) : pp 2859 - 2873 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] alpes orientales [Termes IGN] carte de la végétation [Termes IGN] classe d'objets [Termes IGN] classification automatique [Termes IGN] extraction de traits caractéristiques [Termes IGN] fusion d'images [Termes IGN] image à très haute résolution [Termes IGN] image multibande [Termes IGN] image SPOT 5 [Termes IGN] orthoimage [Termes IGN] texture d'image [Termes IGN] Trente Résumé : (Auteur) In areas with complex three-dimensional features, slope and aspect interact with light conditions and significantly affect the spatial structure of images acquired by remote sensing instruments (for example, by changing the distribution of shadows and affecting the texture of high resolution imagery). In this scenario, this paper analyses the potential and the effectiveness of an automatic classification system to identify three fundamental vegetation classes (forest, grassland and crops) in the complex topography of the Italian Alps (Autonomous Province of Trento, Italy). This classification system is based on the fusion of spectral information provided by the SPOT-5 multi-spectral channels (Ground Instantaneous Field of View, GIFOV, equal to 10 m) and textural information extracted from airborne digital orthophotos (GIFOV equal to 1 m) and is designed to be user-friendly. The texture of the digital orthophotos was modelled using defined bidirectional variograms, thereby extracting additional information unavailable in first-order texture analyses. Using SPOT-5 multi-spectral information alone, the classification accuracy in the investigated alpine area was equal to 87.5%, but increased to 92.1% when texture information was included. In particular, the texture information significantly increased the classification accuracy for crops (from 68.9% to 87.9%), especially orchards that tend to be classified as lowland deciduous forests, and herbaceous crops (such as maize) that are often misclassified as grasslands. A further simple majority analysis increased the ability of detecting grassland, crops and urban zones. The combination of the majority analysis and the proposed automatic classification system seems an effective approach to classifying vegetation types in highly fragmented and complex Alpine landscapes on a regional scale. Copyright Taylor & Francis Numéro de notice : A2009-258 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431160802558600 En ligne : https://doi.org/10.1080/01431160802558600 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29888 [article]

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