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Classification of wheat crop with multi-temporal images: performance of maximum likelihood and artificial neural networks / C.S. Murthy in International Journal of Remote Sensing IJRS, vol 24 n° 23 (December 2003)  

Public [article]  inInternational Journal of Remote Sensing IJRS > vol 24 n° 23 (December 2003) . - pp 4871 - 4890 Titre : Classification of wheat crop with multi-temporal images: performance of maximum likelihood and artificial neural networks Type de document : Article/Communication Auteurs : C.S. Murthy, Auteur ; P.V. Raju, Auteur ; K.V.S. Badrinath, Auteur Année de publication : 2003 Article en page(s) : pp 4871 - 4890 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image [Termes IGN] agriculture [Termes IGN] analyse diachronique [Termes IGN] classification par maximum de vraisemblance [Termes IGN] classification par réseau neuronal [Termes IGN] cultures [Termes IGN] image multitemporelle [Termes IGN] neurone artificiel Résumé : (Auteur) the need for multi-temporal data analysis for delineation of wheat crop has been demonstrated first. It is found that Maximum Likelihood Classification (MLC) with the composite data of multi-temporal images is limited by the problem of large null set containing crop pixels. Therefore, for effective classification of multi-temporal images, two approaches are evaluated : (1) MLC with different strategies-sequential MLC (s_MLC), MLC with Principal Components (pca_MLC) and iterative MLC (i_MLC) ; and (2) Artificial Neural Network (ANN) with back-propagation method. These classifiers were applied on multi-temporal Indian Remote-Sending satellite (IRS)-1 B images to classify wheat crop in two areas of India, one with dominant wheat and the other with less dominant wheat cultivation. Among the three strategies of MLC, i_MLC has resulted in relatively better classification of wheat. However, the correctness of labelling of wheat pixels. The performance of ANN is proved to be better, in both the situations of dominant wheat and less dominant wheat cultivation. Numéro de notice : A2003-314 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/0143116031000070490 En ligne : https://doi.org/10.1080/0143116031000070490 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=22610 [article]

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