Conti, José C.Farial, Fabio A.Almeida, JurandyAlberton, Bruna [UNESP]Morellato, Leonor P.C. [UNESP]Camolesi, LuizDa Torres, Ricardo S.2018-12-112018-12-112014-01-01Proceedings - International Conference on Pattern Recognition, p. 3126-3131.1051-4651http://hdl.handle.net/11449/177277Phenology is the study of periodic natural phenomena and their relationship to climate. Usually, phenology studies consider the identification of patterns on temporal data. In those studies, several phenological change patterns are often encoded in time series for analysis and knowledge extraction. In this paper, we evaluate the effectiveness of several time series similarity functions in the task of classifying time series related to phonological phenomena characterized by near-surface vegetation indices extracted from images. In addition, we performed a correlation analysis to identify potential candidates for combination.3126-3131engTrabalho apresentado em evento10.1109/ICPR.2014.539Acesso aberto2-s2.0-84919935087