Towards the use of sequential patterns for detection and characterization of natural and agricultural areas

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To access the full text documents, please follow this link: http://hdl.handle.net/2117/24336

dc.contributor	Universitat Politècnica de Catalunya. Departament d'Arquitectura de Computadors
dc.contributor	Universitat Politècnica de Catalunya. CAP - Grup de Computació d'Altes Prestacions
dc.contributor.author	Guttler, Fabio
dc.contributor.author	Ienco, Dino
dc.contributor.author	Teisseire, Maguelonne
dc.contributor.author	Nin Guerrero, Jordi
dc.contributor.author	Poncelet, Pascal
dc.date	2014
dc.identifier.citation	Guttler, F. [et al.]. Towards the use of sequential patterns for detection and characterization of natural and agricultural areas. A: International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems. "Information Processing and Management of Uncertainty in Knowledge-Based Systems: 15th International Conference, IPMU 2014: Montpellier, France, July 15-19, 2014: proceedings, part I". Montpellier: Springer, 2014, p. 97-106.
dc.identifier.citation	978-3-319-08795-5
dc.identifier.citation	10.1007/978-3-319-08795-5_11
dc.identifier.uri	http://hdl.handle.net/2117/24336
dc.language.iso	eng
dc.publisher	Springer
dc.relation	http://link.springer.com/chapter/10.1007%2F978-3-319-08795-5_11
dc.rights	info:eu-repo/semantics/openAccess
dc.subject	Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Radiocomunicació i exploració electromagnètica::Teledetecció
dc.subject	Àrees temàtiques de la UPC::Informàtica::Intel·ligència artificial::Sistemes experts
dc.subject	Expert systems (Computer science)
dc.subject	Data mining
dc.subject	Remote sensing
dc.subject	Data mining and remote sensing
dc.subject	Temporal patterns
dc.subject	Sistemes experts (Informàtica)
dc.subject	Mineria de dades
dc.subject	Imatges satel·litàries
dc.title	Towards the use of sequential patterns for detection and characterization of natural and agricultural areas
dc.type	info:eu-repo/semantics/submittedVersion
dc.type	info:eu-repo/semantics/conferenceObject
dc.description.abstract	Nowadays, a huge amount of high resolution satellite images are freely available. Such images allow researchers in environmental sciences to study the different natural habitats and farming practices in a remote way. However, satellite images content strongly depends on the season of the acquisition. Due to the periodicity of natural and agricultural dynamics throughout seasons, sequential patterns arise as a new opportunity to model the behaviour of these environments. In this paper, we describe some preliminary results obtained with a new framework for studying spatiotemporal evolutions over natural and agricultural areas using k-partite graphs and sequential patterns extracted from segmented Landsat images.

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