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Auteur A.R.S. Marcal |
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Land covers update by supervised classification of segmented ASTER images / A.R.S. Marcal in International Journal of Remote Sensing IJRS, vol 26 n° 7 (April 2005)
[article]
Titre : Land covers update by supervised classification of segmented ASTER images Type de document : Article/Communication Auteurs : A.R.S. Marcal, Auteur ; J.S. Borges, Auteur ; et al., Auteur Année de publication : 2005 Article en page(s) : pp 1347 - 1362 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse discriminante
[Termes IGN] carte d'occupation du sol
[Termes IGN] classificateur paramétrique
[Termes IGN] classification barycentrique
[Termes IGN] classification dirigée
[Termes IGN] classification floue
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] image multibande
[Termes IGN] image Terra-ASTER
[Termes IGN] mise à jour cartographique
[Termes IGN] Portugal
[Termes IGN] segmentation d'imageRésumé : (Auteur) The revision of the 1995 land cover dataset for the Vale do Sousa region, in the northwest of Portugal, was carried out by supervised classification of a multispectral image from the Advanced Spaceborne Thermal Emission and Reflectance Radiometer (ASTER) sensor. The nine reflective bands of ASTER were used, covering the spectral range from 0.52-2.43 um. The image was initially ortho-rectified and segmented into 51 186 objects, with an average object size of 135 pixels (about 3 ha). A total of 582 of these objects were identified for training nine land cover classes. The image was classified using an algorithm based on a fuzzy classifier, Support Vector Machines (SVM), K Nearest Neighbours (K-NN) and a Logistic Discrimination (LD) classifier. The results from the classification were evaluated using a set of 277 validation sites, independently gathered. The overall accuracy was 44.6%, for the fuzzy classifier. 70.5%, for the SVM, 60.9% for the K-NN and 72.2% for the LD classifier. The difficulty in discriminating between some of the forest land cover classes was examined by separability analysis and unsupervised classification with hierarchical clustering. The forest classes were found to overlap in the multi-spectral space defined by the nine ASTER bands used. Numéro de notice : A2005-179 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431160412331291233 En ligne : https://doi.org/10.1080/01431160412331291233 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27316
in International Journal of Remote Sensing IJRS > vol 26 n° 7 (April 2005) . - pp 1347 - 1362[article]Exemplaires(1)
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