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Improvements in land use mapping for irrigated agriculture from satellite sensor data using a multi-stage maximum likelihood classification / I.A. El-Magd in International Journal of Remote Sensing IJRS, vol 24 n° 21 (November 2003)  

Public [article]  inInternational Journal of Remote Sensing IJRS > vol 24 n° 21 (November 2003) . - pp 4197 - 4206 Titre : Improvements in land use mapping for irrigated agriculture from satellite sensor data using a multi-stage maximum likelihood classification Type de document : Article/Communication Auteurs : I.A. El-Magd, Auteur ; T.W. Tanton, Auteur Année de publication : 2003 Article en page(s) : pp 4197 - 4206 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] carte agricole [Termes IGN] carte d'occupation du sol [Termes IGN] classification par maximum de vraisemblance [Termes IGN] cultures [Termes IGN] cultures irriguées [Termes IGN] image Landsat-ETM+ [Termes IGN] rizière [Termes IGN] utilisation du sol Résumé : (Auteur) The accuracy of conventional land use classification of irrigated agriculture from optical satellite images using maximum likelihood supervised classification was compared with a classification based on multistage maxinium likelihood supervised classification. In the multistage maximum likelihood classification series of sub-classifications were carried out which included masking and/or omitting certain crops from the classifications. These series of classifications improved the identification of individual crops/land use types. The output from the optimum sub-classifications were stacked to give an overall crop types/land use map. When the multistage classification was tested against a single stage classification on a large irrigation scheme in Central Asia the final accuracy of crop/land use classification increased from 85% to 94%. Field verification confirmed the accuracy at 93.5%. These results were achieved with a single Landsat 7 Enhanced Thematic Mapper (ETM+) sensor dataset as of 2 August 1999 over an area of 38.5 km. Numéro de notice : A2003-305 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/0143116031000139791 En ligne : https://doi.org/10.1080/0143116031000139791 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=22601 [article]

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