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Geostatistics and remote sensing methods in the classification of images of areas cultivated with citrus REA
Silva,Alessandra F.; Barbosa,Ana Paula; Zimback,Célia R. L.; Landim,Paulo M. B..
This study compares the precision of three image classification methods, two of remote sensing and one of geostatistics applied to areas cultivated with citrus. The 5,296.52ha area of study is located in the city of Araraquara - central region of the state of São Paulo (SP), Brazil. The multispectral image from the CCD/CBERS-2B satellite was acquired in 2009 and processed through the Geographic Information System (GIS) SPRING. Three classification methods were used, one unsupervised (Cluster), and two supervised (Indicator Kriging/IK and Maximum Likelihood/Maxver), in addition to the screen classification taken as field checking.. Reliability of classifications was evaluated by Kappa index. In accordance with the Kappa index, the Indicator kriging method...
Tipo: Info:eu-repo/semantics/article Palavras-chave: Indicator Kriging; Cluster; Maxver; CBERS-2B satellite; Spatial classification.
Ano: 2013 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162013000600017
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