dc.contributorUniversidade Estadual de Campinas (UNICAMP)
dc.contributorUniversidade Estadual Paulista (UNESP)
dc.date.accessioned2022-04-30T22:28:33Z
dc.date.accessioned2022-12-20T03:34:39Z
dc.date.available2022-04-30T22:28:33Z
dc.date.available2022-12-20T03:34:39Z
dc.date.created2022-04-30T22:28:33Z
dc.date.issued2019-07-01
dc.identifierInternational Geoscience and Remote Sensing Symposium (IGARSS), p. 6586-6589.
dc.identifierhttp://hdl.handle.net/11449/232954
dc.identifier10.1109/IGARSS.2019.8898112
dc.identifier2-s2.0-85077688255
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/5413052
dc.description.abstractThe support of time series similarity searches might be crucial in phenology studies, in which long-term time series analysis based on the identification of similar and different phenological patterns shared by individuals belonging to different species is a widely common task. In this paper, we introduce the use of well-established Information Retrieval (IR) technologies in the search of time series. The solution comprises four main steps: extraction of an image-based time series representation; image content description to encode time series properties and patterns; textual signature extraction based on image content descriptions; and textual signature indexing using off-the-shelf IR approaches. In this paper, we demonstrate both the effectiveness and the efficiency of the proposed solution in time series retrieval problems related to the management of phenological data associated with near-surface vegetation images.
dc.languageeng
dc.relationInternational Geoscience and Remote Sensing Symposium (IGARSS)
dc.sourceScopus
dc.subjectinformation retrieval
dc.subjectphenology
dc.subjectrecurrence plot
dc.subjecttime series retrieval
dc.titlePixelwise Time Series Retrieval in Phenological Studies
dc.typeActas de congresos


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