Towards the use of sequential patterns for detection and characterization of natural and agricultural areas
Document typeConference report
Rights accessOpen Access
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.
CitationGuttler, 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.