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. © Springer International Publishing Switzerland 2014.
CITATION STYLE
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 Communications in Computer and Information Science (Vol. 442 CCIS, pp. 97–106). Springer Verlag. https://doi.org/10.1007/978-3-319-08795-5_11
Mendeley helps you to discover research relevant for your work.