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Towards the use of sequential patterns for detection and characterization of natural and agricultural areas
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.contributor.other | Universitat Politècnica de Catalunya. Departament d'Arquitectura de Computadors |
dc.date.accessioned | 2014-10-10T09:40:51Z |
dc.date.available | 2014-12-31T03:30:57Z |
dc.date.created | 2014 |
dc.date.issued | 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.isbn | 978-3-319-08795-5 |
dc.identifier.uri | http://hdl.handle.net/2117/24336 |
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. |
dc.format.extent | 10 p. |
dc.language.iso | eng |
dc.publisher | Springer |
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.lcsh | Expert systems (Computer science) |
dc.subject.lcsh | Data mining |
dc.subject.lcsh | Remote sensing |
dc.subject.other | Data mining and remote sensing |
dc.subject.other | Temporal patterns |
dc.title | Towards the use of sequential patterns for detection and characterization of natural and agricultural areas |
dc.type | Conference report |
dc.subject.lemac | Sistemes experts (Informàtica) |
dc.subject.lemac | Mineria de dades |
dc.subject.lemac | Imatges satel·litàries |
dc.contributor.group | Universitat Politècnica de Catalunya. CAP - Grup de Computació d'Altes Prestacions |
dc.identifier.doi | 10.1007/978-3-319-08795-5_11 |
dc.relation.publisherversion | http://link.springer.com/chapter/10.1007%2F978-3-319-08795-5_11 |
dc.rights.access | Open Access |
local.identifier.drac | 15225865 |
dc.description.version | Postprint (author’s final draft) |
local.citation.author | Guttler, F.; Ienco, D.; Teisseire, M.; Nin, J.; Poncelet, P. |
local.citation.contributor | International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems |
local.citation.pubplace | Montpellier |
local.citation.publicationName | Information Processing and Management of Uncertainty in Knowledge-Based Systems: 15th International Conference, IPMU 2014: Montpellier, France, July 15-19, 2014: proceedings, part I |
local.citation.startingPage | 97 |
local.citation.endingPage | 106 |