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.
All rights reserved. This work is protected by the corresponding intellectual and industrial property rights. Without prejudice to any existing legal exemptions, reproduction, distribution, public communication or transformation of this work are prohibited without permission of the copyright holder. If you wish to make any use of the work not provided for in the law, please contact: email@example.com