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Geospatial method for computing supplemental multi-decadal US coastal land use and land cover classification products, using Landsat data and C-CAP products / Joseph P. Spruce in Geocarto international, vol 29 n° 5 - 6 (August - October 2014)  

Public [article]  inGeocarto international > vol 29 n° 5 - 6 (August - October 2014) . - pp 470-485 Titre : Geospatial method for computing supplemental multi-decadal US coastal land use and land cover classification products, using Landsat data and C-CAP products Type de document : Article/Communication Auteurs : Joseph P. Spruce, Auteur ; James C. Smoot, Auteur ; Jean T. Ellis, Auteur ; et al., Auteur Année de publication : 2014 Article en page(s) : pp 470-485 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] classification ISODATA [Termes IGN] classification non dirigée [Termes IGN] détection de changement [Termes IGN] image Landsat [Termes IGN] image optique [Termes IGN] occupation du sol [Termes IGN] surveillance du littoral Résumé : (auteur) This paper discusses the development and implementation of a method that can be used with multi-decadal Landsat data for computing general coastal US land use and land cover (LULC) maps consisting of seven classes. With Mobile Bay, Alabama as the study region, the method that was applied to derive LULC products for nine dates across a 34-year time span. Classifications were computed and refined using decision rules in conjunction with unsupervised classification of Landsat data and Coastal Change and Analysis Program value-added products. Each classification’s overall accuracy was assessed by comparing stratified random locations to available high spatial resolution satellite and aerial imagery, field survey data and raw Landsat RGBs. Overall classification accuracies ranged from 83 to 91% with overall κ statistics ranging from 0.78 to 0.89. Accurate classifications were computed for all nine dates, yielding effective results regardless of season and Landsat sensor. This classification method provided useful map inputs for computing LULC change products. Numéro de notice : A2014-407 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2013.798357 Date de publication en ligne : 04/06/2013 En ligne : https://doi.org/10.1080/10106049.2013.798357 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=73944 [article]

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