Temporal domain adaptation under time warping

François Petitjean, Jordi Inglada, Pierre Gançarski

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

3 Citations (Scopus)

Abstract

Satellite Image Time Series are becoming increasingly available and will continue to do so in the coming years thanks to the launch of space missions which aim at providing a coverage of the Earth every few days with high spatial resolution. In the case of optical imagery, it will be possible to produce land use and cover change maps with detailed nomenclatures. However, due to meteorological phenomena, such as clouds, these time series will become irregular in terms of temporal sampling and one will need to compare time series with different lengths. In this paper we present an approach to image time series analysis which is able to deal with irregularly sampled series and which also allows the comparison of pairs of time series where each element of the pair has a different number of samples. We present the Dynamic Time Warping from a theoretical point of view and illustrate its capabilities for domain adaptation.

Original languageEnglish
Title of host publication2011 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2011 - Proceedings
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages3578-3581
Number of pages4
ISBN (Print)9781457710056
DOIs
Publication statusPublished - 2011
Externally publishedYes
EventIEEE International Geoscience and Remote Sensing Symposium 2011 - Vancouver Convention Center, Vancouver, Canada
Duration: 24 Jul 201129 Jul 2011
http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=6034618 (IEEE Conference Proceedings)

Conference

ConferenceIEEE International Geoscience and Remote Sensing Symposium 2011
Abbreviated titleIGARSS 2011
CountryCanada
CityVancouver
Period24/07/1129/07/11
Internet address

Keywords

  • Classification
  • Domain Adaptation
  • Dynamic Time Warping
  • Remote Sensing
  • Satellite Image Time Series

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