Clustering of satellite image time series under time warping

François Petitjean, Jordi Inglada, Pierre Gançarski

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

9 Citations (Scopus)


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 irregularly sensed time series. In this paper, we present an approach to satellite image time series analysis which is able to both deal with irregularly sampled series and to capture distorted behaviors. We present the Dynamic Time Warping from a theoretical point of view and illustrate its abilities for satellite image time series clustering.

Original languageEnglish
Title of host publication2011 6th International Workshop on the Analysis of Multi-Temporal Remote Sensing Images, Multi-Temp 2011 - Proceedings
PublisherIEEE, Institute of Electrical and Electronics Engineers
Number of pages4
ISBN (Print)9781457712036
Publication statusPublished - 2011
Externally publishedYes
EventInternational Workshop on the Analysis of Multi-Temporal Remote Sensing Images 2011 - Trento, Italy
Duration: 12 Jul 201114 Jul 2011
Conference number: 6th


WorkshopInternational Workshop on the Analysis of Multi-Temporal Remote Sensing Images 2011
Abbreviated titleMulti-Temp 2011


  • Clustering
  • Dynamic Time Warping
  • Remote Sensing
  • Satellite Image Time Series

Cite this