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Assessment of Nigeriasat-1 satellite data for urban land use/land cover analysis using object-based image analysis in Abuja, Nigeria / Christopher Ifechukwude Chima in Geocarto international, vol 33 n° 9 (September 2018)  

Public [article]  inGeocarto international > vol 33 n° 9 (September 2018) . - pp 893 - 911 Titre : Assessment of Nigeriasat-1 satellite data for urban land use/land cover analysis using object-based image analysis in Abuja, Nigeria Type de document : Article/Communication Auteurs : Christopher Ifechukwude Chima, Auteur ; Nigel Trodd, Auteur ; Matthew Blackett, Auteur Année de publication : 2018 Article en page(s) : pp 893 - 911 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] analyse comparative [Termes IGN] analyse d'image orientée objet [Termes IGN] classification par maximum de vraisemblance [Termes IGN] image Landsat-ETM+ [Termes IGN] image NigeriaSat [Termes IGN] image SPOT 5 [Termes IGN] image SPOT-HRG [Termes IGN] occupation du sol Résumé : (Auteur) This study assesses the usefulness of Nigeriasat-1 satellite data for urban land cover analysis by comparing it with Landsat and SPOT data. The data-sets for Abuja were classified with pixel- and object-based methods. While the pixel-based method was classified with the spectral properties of the images, the object-based approach included an extra layer of land use cadastre data. The classification accuracy results for OBIA show that Landsat 7 ETM, Nigeriasat-1 SLIM and SPOT 5 HRG had overall accuracies of 92, 89 and 96%, respectively, while the classification accuracy for pixel-based classification were 88% for Landsat 7 ETM, 63% for Nigeriasat-1 SLIM and 89% for SPOT 5 HRG. The results indicate that given the right classification tools, the analysis of Nigeriasat-1 data can be compared with Landsat and SPOT data which are widely used for urban land use and land cover analysis. Numéro de notice : A2018-336 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2017.1316778 Date de publication en ligne : 08/05/2017 En ligne : https://doi.org/10.1080/10106049.2017.1316778 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90550 [article]