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Land-cover change detection using one-class support vector machine / P. Li in Photogrammetric Engineering & Remote Sensing, PERS, vol 76 n° 3 (March 2010)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 76 n° 3 (March 2010) . - pp 255 - 263 Titre : Land-cover change detection using one-class support vector machine Type de document : Article/Communication Auteurs : P. Li, Auteur ; H. Xu, Auteur Année de publication : 2010 Article en page(s) : pp 255 - 263 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image [Termes IGN] analyse comparative [Termes IGN] classification par séparateurs à vaste marge [Termes IGN] détection de changement [Termes IGN] données multitemporelles [Termes IGN] Kappa de Cohen [Termes IGN] occupation du sol [Termes IGN] traitement d'image Résumé : (Auteur) Change detection using remote sensing has considerable potential for monitoring land-cover change. Commonly, one specific class of change is of interest in many applications. In this paper, a recently developed one-class classifier, the One-Class Support Vector Machine (OCSVM), is proposed for the change detection of one specific class by multitemporal classification. The classifier only requires samples from the change class of interest as the training data. The performance of the proposed method was evaluated in two applications by comparing with conventional post-classification comparison methods. The results demonstrated the proposed method achieved both higher overall accuracy and higher kappa coefficient than the conventional methods, and demonstrated good potential for further application. The study also indicated that with the ocsvm, the analysis can focus only on the specific class of interest and does not need to treat other classes, thus providing highly accurate change detection. The OCSVM-based change detection method, as a general and easily implemented method, can be used for applications where only the change of one specific class is of interest. Copyright ASPRS Numéro de notice : A2010-087 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.76.3.255 En ligne : https://doi.org/10.14358/PERS.76.3.255 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=30283 [article]

Intercalibration of vegetation indices from different sensor systems / M.D. Steven in Remote sensing of environment, vol 88 n° 4 (30/12/2003)  

Public [article]  inRemote sensing of environment > vol 88 n° 4 (30/12/2003) . - pp 412 - 422 Titre : Intercalibration of vegetation indices from different sensor systems Type de document : Article/Communication Auteurs : M.D. Steven, Auteur ; T.J. Malthus, Auteur ; F. Baret, Auteur ; H. Xu, Auteur ; M. Chopping, Auteur Année de publication : 2003 Article en page(s) : pp 412 - 422 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image [Termes IGN] données multicapteurs [Termes IGN] indice de végétation [Termes IGN] luminance lumineuse [Termes IGN] réflectance végétale [Termes IGN] simulation d'étalonnage Résumé : (Auteur) Spectroradiometric measurements were made over a range of crop canopy densities, soil backgrounds and foliage colour. The reflected spectral radiances were convoluted with the spectral response functions of a range of satellite instruments to simulate their responses. When Normalised Difference Vegetation Indices (NDVI) from the different instruments were compared, they varied by a few percent, but the values were strongly linearly related, allowing vegetation indices from one instrument to be intercalibrated against another. A table of conversion coefficents is presented for AVHRR, ATSR2, Landsat MSS, TM and ETM+, SPOT-2 and SPOT-4 HRV, IRS, IKONOS, SEAWIFS, MISR, MODIS, POLDER, Quickbird and MERIS (see Appendix A for glossary of acronyms). The same set of coefficients was found to apply, within the margin of error of the analysis, for the Soil Adjusted Vegetation Index SAVI. The relationships for SPOT vs. TM and for ATSR-2 vs. AVHRR were directly validated by comparison of atmospherically corrected image data. The results indicate that vegetation indices can be interconverted to a precision of 12%. This result offers improved opportunities for monitoring crops through the growing season and the prospects of better continuity of long-term monitoring of vegetation responses to environmental change. Numéro de notice : A2003-367 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2003.08.010 En ligne : https://doi.org/10.1016/j.rse.2003.08.010 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=26447 [article]