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

Abstract : Nowadays, a huge amount of high resolution satellite images are freely available. Such images allow researchers in environmental sciences to study the di↵erent 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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https://hal.inrae.fr/hal-02600411
Contributor : Migration Irstea Publications <>
Submitted on : Friday, December 11, 2020 - 11:51:19 AM
Last modification on : Thursday, April 22, 2021 - 3:31:48 AM

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Fabio Güttler, Dino Ienco, Maguelonne Teisseire, Jordi Nin, Pascal Poncelet. Towards the use of sequential patterns for detection and characterization of natural and agricultural areas. 15th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems (IPMU), Jul 2014, Montpellier, France. pp.97-106, ⟨10.1007/978-3-319-08795-5_11⟩. ⟨hal-02600411⟩

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