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Using fraction images derived from modis data for coffee crop mapping REA
Bispo,Rafael C.; Lamparelli,Rubens A. C.; Rocha,Jansle V..
Coffee production was closely linked to the economic development of Brazil and, even today, coffee is an important product of the national agriculture. The State of Minas Gerais currently accounts for 52% of the whole coffee area in Brazil. Remote sensing data can provide information for monitoring and mapping of coffee crops, faster and cheaper than conventional methods. In this context, the objective of this study was to assess the effectiveness of coffee crop mapping in Monte Santo de Minas municipality, Minas Gerais State, Brazil, from fraction images derived from MODIS data, in both dry and rainy seasons. The Spectral Linear Mixing Model was used to derive fraction images of soil, coffee, and water/shade. These fraction images served as input data for...
Tipo: Info:eu-repo/semantics/article Palavras-chave: Spectral linear mixing model; Supervised classification; Overall Accuracy; Kappa Index.
Ano: 2014 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162014000100012
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