Algorithms of Expert Classification Applied in Quickbird Satellite Images for Land Use Mapping

dc.creator	Perea,Alberto Jesús
dc.creator	Meroño,José Emilio
dc.creator	Aguilera,María Jesús
dc.date	2009-09-01
dc.date.accessioned	2019-04-24T21:18:52Z
dc.date.available	2019-04-24T21:18:52Z
dc.identifier	https://scielo.conicyt.cl/scielo.php?script=sci_arttext&pid=S0718-58392009000300013
dc.identifier.uri	http://revistaschilenas.uchile.cl/handle/2250/55469
dc.description	The objective of this paper was the development of a methodology for the classification of digital aerial images, which, with the aid of object-based classification and the Normalized Difference Vegetation Index (NDVI), can quantify agricultural areas, by using algorithms of expert classification, with the aim of improving the final results of thematic classifications. QuickBird satellite images and data of 2532 plots in Hinojosa del Duque, Spain, were used to validate the different classifications, obtaining an overall classification accuracy of 91.9% and an excellent Kappa statistic (87.6%) for the algorithm of expert classification.
dc.format	text/html
dc.language	en
dc.publisher	Instituto de Investigaciones Agropecuarias, INIA
dc.relation	10.4067/S0718-58392009000300013
dc.rights	info:eu-repo/semantics/openAccess
dc.source	Chilean journal of agricultural research v.69 n.3 2009
dc.subject	expert classification
dc.subject	vegetation index
dc.subject	land cover
dc.subject	object-based classification
dc.title	Algorithms of Expert Classification Applied in Quickbird Satellite Images for Land Use Mapping