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Data mining techniques for identification of spectrally homogeneous areas using NDVI temporal profiles of soybean crop REA
Johann,Jerry A.; Rocha,Jansle V.; Oliveira,Stanley R. de M.; Rodrigues,Luiz H. A.; Lamparelli,Rubens A. C..
The aim of this study was to group temporal profiles of 10-day composites NDVI product by similarity, which was obtained by the SPOT Vegetation sensor, for municipalities with high soybean production in the state of Paraná, Brazil, in the 2005/2006 cropping season. Data mining is a valuable tool that allows extracting knowledge from a database, identifying valid, new, potentially useful and understandable patterns. Therefore, it was used the methods for clusters generation by means of the algorithms K-Means, MAXVER and DBSCAN, implemented in the WEKA software package. Clusters were created based on the average temporal profiles of NDVI of the 277 municipalities with high soybean production in the state and the best results were found with the K-Means...
Tipo: Info:eu-repo/semantics/article Palavras-chave: Annual crop; MODIS; SPOT Vegetation; MAXVER; K-Means.
Ano: 2013 URL:
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