Towards the Use of Sequential Patterns for Detection and Characterization of Natural and Agricultural Areas

Fabio Guttler; Dino Ienco; Maguelonne Teisseire; J. Nin; Pascal Poncelet

doi:10.1007/978-3-319-08795-5_11

Towards the Use of Sequential Patterns for Detection and Characterization of Natural and Agricultural Areas

Fabio Guttler, Dino Ienco, Maguelonne Teisseire, J. Nin, Pascal Poncelet

Producció científica: Capítol de llibre › Contribució a congrés/conferència › Avaluat per experts

1 Citació (Scopus)

Resum

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.

Idioma original	Anglès
Títol de la publicació	Information Processing and Management of Uncertainty in Knowledge-Based Systems - 15th International Conference, IPMU 2014, Proceedings
Editor	Springer Verlag
Pàgines	97-106
Nombre de pàgines	10
Edició	PART 1
ISBN (imprès)	9783319087948
DOIs	https://doi.org/10.1007/978-3-319-08795-5_11
Estat de la publicació	Publicada - 2014
Publicat externament	Sí
Esdeveniment	15th International Conference on Information Processing and Management of Uncertainty in Knowledge-based Systems, IPMU 2014 - Montpellier, France Durada: 15 de jul. 2014 → 19 de jul. 2014

Sèrie de publicacions

Nom	Communications in Computer and Information Science
Nombre	PART 1
Volum	442 CCIS
ISSN (imprès)	1865-0929

Conferència

Conferència	15th International Conference on Information Processing and Management of Uncertainty in Knowledge-based Systems, IPMU 2014
País/Territori	France
Ciutat	Montpellier
Període	15/07/14 → 19/07/14

Accés al document

10.1007/978-3-319-08795-5_11

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Guttler, F., Ienco, D., Teisseire, M., Nin, J., & Poncelet, P. (2014). Towards the Use of Sequential Patterns for Detection and Characterization of Natural and Agricultural Areas. In Information Processing and Management of Uncertainty in Knowledge-Based Systems - 15th International Conference, IPMU 2014, Proceedings (PART 1 ed., pàg. 97-106). (Communications in Computer and Information Science; Vol. 442 CCIS, Núm. PART 1). Springer Verlag. https://doi.org/10.1007/978-3-319-08795-5_11

Guttler, Fabio ; Ienco, Dino ; Teisseire, Maguelonne et al. / Towards the Use of Sequential Patterns for Detection and Characterization of Natural and Agricultural Areas. Information Processing and Management of Uncertainty in Knowledge-Based Systems - 15th International Conference, IPMU 2014, Proceedings. PART 1. ed. Springer Verlag, 2014. pàg. 97-106 (Communications in Computer and Information Science; PART 1).

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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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Guttler, F, Ienco, D, Teisseire, M, Nin, J & Poncelet, P 2014, Towards the Use of Sequential Patterns for Detection and Characterization of Natural and Agricultural Areas. in Information Processing and Management of Uncertainty in Knowledge-Based Systems - 15th International Conference, IPMU 2014, Proceedings. PART 1 ed., Communications in Computer and Information Science, núm. PART 1, vol. 442 CCIS, Springer Verlag, pàg. 97-106, 15th International Conference on Information Processing and Management of Uncertainty in Knowledge-based Systems, IPMU 2014, Montpellier, France, 15/07/14. https://doi.org/10.1007/978-3-319-08795-5_11

Towards the Use of Sequential Patterns for Detection and Characterization of Natural and Agricultural Areas. / Guttler, Fabio; Ienco, Dino; Teisseire, Maguelonne et al.
Information Processing and Management of Uncertainty in Knowledge-Based Systems - 15th International Conference, IPMU 2014, Proceedings. PART 1. ed. Springer Verlag, 2014. pàg. 97-106 (Communications in Computer and Information Science; Vol. 442 CCIS, Núm. PART 1).

Producció científica: Capítol de llibre › Contribució a congrés/conferència › Avaluat per experts

TY - GEN

T1 - Towards the Use of Sequential Patterns for Detection and Characterization of Natural and Agricultural Areas

AU - Guttler, Fabio

AU - Ienco, Dino

AU - Teisseire, Maguelonne

AU - Nin, J.

AU - Poncelet, Pascal

PY - 2014

Y1 - 2014

N2 - 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.

AB - 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.

KW - Data Mining and Remote Sensing

KW - Temporal Patterns

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U2 - 10.1007/978-3-319-08795-5_11

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AN - SCOPUS:84904995664

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T3 - Communications in Computer and Information Science

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EP - 106

BT - Information Processing and Management of Uncertainty in Knowledge-Based Systems - 15th International Conference, IPMU 2014, Proceedings

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T2 - 15th International Conference on Information Processing and Management of Uncertainty in Knowledge-based Systems, IPMU 2014

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Guttler F, Ienco D, Teisseire M, Nin J, Poncelet P. Towards the Use of Sequential Patterns for Detection and Characterization of Natural and Agricultural Areas. In Information Processing and Management of Uncertainty in Knowledge-Based Systems - 15th International Conference, IPMU 2014, Proceedings. PART 1 ed. Springer Verlag. 2014. pàg. 97-106. (Communications in Computer and Information Science; PART 1). doi: 10.1007/978-3-319-08795-5_11

Towards the Use of Sequential Patterns for Detection and Characterization of Natural and Agricultural Areas

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