2015
DOI: 10.1016/j.engappai.2014.09.001
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Spatio-temporal data classification through multidimensional sequential patterns: Application to crop mapping in complex landscape

Abstract: The main use of satellite imagery concerns the process of the spectral and spatial dimensions of the data. However, to extract useful information, the temporal dimension also has to be accounted for which increases the complexity of the problem. For this reason, there is a need for suitable data mining techniques for this source of data. In this work, we developed a data mining methodology to extract multidimensional sequential patterns to characterize temporal behaviors. We then used the extracted multidimens… Show more

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Cited by 12 publications
(5 citation statements)
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References 29 publications
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“…Use a space after authors' initials. Papers that have not been published should be cited as "unpublished" [4] been submitted for publication should be cited as "submitted for publication" [5]. Papers that have been accepted for publication, but not yet specified for an issue should be cited as "to be published" [6].…”
Section: Heuristicmentioning
confidence: 99%
See 1 more Smart Citation
“…Use a space after authors' initials. Papers that have not been published should be cited as "unpublished" [4] been submitted for publication should be cited as "submitted for publication" [5]. Papers that have been accepted for publication, but not yet specified for an issue should be cited as "to be published" [6].…”
Section: Heuristicmentioning
confidence: 99%
“…The approach does not consider the spatial patterns for efficient predictive analytics. A Spatio-temporal data classification method was presented in [5] with the multidimensional chronological patterns. But the feature selection was not performed to improve the Spatio-temporal data classification with minimum time.…”
Section: Introductionmentioning
confidence: 99%
“…A DFTS is indeed a large and complex spatiotemporal vectorial data volume that cannot be explored manually. As reported in [10] and [18], sequential pattern mining techniques can be successfully applied to SITS. They can also be used to mine DFTS, as evidenced in [17], allowing to discover interesting displacement evolutions over time and space.…”
Section: Introductionmentioning
confidence: 99%
“…The designed classifier failed to achieve more robust performance. A Spatio-temporal data classification method was developed in [10] with multidimensional patterns. But the method failed to improve the performance of data classification with minimum time.…”
Section: Introductionmentioning
confidence: 99%