Algorithms of expert classification applied in quickbird satellite images for land use mapping
View/ Open
Author
Perea Moreno, Alberto Jesús
Meroño de Larriva, José Emilio
Aguilera Ureña, M. Jesús
Publisher
Instituto de Investigaciones Agropecuarias (Chile)Date
2009Subject
Expert classificationVegetation index
Land cover
Object-based classification
METS:
Mostrar el registro METSPREMIS:
Mostrar el registro PREMISMetadata
Show full item recordAbstract
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