Algorithms of expert classification applied in quickbird satellite images for land use mapping
Autor
Perea Moreno, Alberto Jesús
Meroño de Larriva, José Emilio
Aguilera Ureña, M. Jesús
Editor
Instituto de Investigaciones Agropecuarias (Chile)Fecha
2009Materia
Expert classificationVegetation index
Land cover
Object-based classification
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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