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A patch-based image classification by integrating hyperspectral data with GIS / B. Zhang in International Journal of Remote Sensing IJRS, vol 27 n°15-16 (August 2006)
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Titre : A patch-based image classification by integrating hyperspectral data with GIS Type de document : Article/Communication Auteurs : B. Zhang, Auteur ; Xiuping Jia, Auteur ; et al., Auteur Année de publication : 2006 Article en page(s) : pp 3337 - 3346 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] classification dirigée
[Termes IGN] classification pixellaire
[Termes IGN] image hyperspectrale
[Termes IGN] image PHI
[Termes IGN] système d'information géographiqueRésumé : (Auteur) Hyperspectral remote sensing data provide detailed spectral information and are widely used for pixel-based image classification. However, without considering spatial correlation among neighbouring pixels, a generated thematic map may have a ‘salt-and-pepper’ appearance. With the development of the Geographic Information System (GIS), the spatial relationship between a pixel and its neighbours can be recorded readily and used together with remote sensing data. The objective of this study was to integrate hyperspectral data with the GIS for effective thematic mapping. To date, GIS data have been used mainly in field surveys or training field selection for remote sensing data interpretation. Here we propose a patch-classification based on integration of the GIS with remote sensing data. The classification results obtained by using this method can be easily saved in a vector format as used for GIS files. Computational cost is decreased compared with a pixel-by-pixel classification. The issue of how to identify pure or mixed patches is addressed and a three-level simple and effective checking method is developed. A case study is presented with a hyperspectral data set recorded by the Pushbroom Hyperspectral Imager (PHI) and related GIS data. Numéro de notice : A2006-337 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431160500409577 En ligne : https://doi.org/10.1080/01431160500409577 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28061
in International Journal of Remote Sensing IJRS > vol 27 n°15-16 (August 2006) . - pp 3337 - 3346[article]Exemplaires(1)
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