Clustering of satellite image time series under time warping

François Petitjean; Jordi Inglada; Pierre Gançarski

doi:10.1109/Multi-Temp.2011.6005050

Clustering of satellite image time series under time warping

François Petitjean, Jordi Inglada, Pierre Gançarski

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Other › peer-review

9 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 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 language	English
Title of host publication	2011 6th International Workshop on the Analysis of Multi-Temporal Remote Sensing Images, Multi-Temp 2011 - Proceedings
Publisher	IEEE, Institute of Electrical and Electronics Engineers
Pages	69-72
Number of pages	4
ISBN (Print)	9781457712036
DOIs	https://doi.org/10.1109/Multi-Temp.2011.6005050
Publication status	Published - 2011
Externally published	Yes
Event	International Workshop on the Analysis of Multi-Temporal Remote Sensing Images 2011 - Trento, Italy Duration: 12 Jul 2011 → 14 Jul 2011 Conference number: 6th

Workshop

Workshop	International Workshop on the Analysis of Multi-Temporal Remote Sensing Images 2011
Abbreviated title	Multi-Temp 2011
Country/Territory	Italy
City	Trento
Period	12/07/11 → 14/07/11

Keywords

Clustering
Dynamic Time Warping
Remote Sensing
Satellite Image Time Series

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1109/Multi-Temp.2011.6005050

Cite this

Petitjean, F., Inglada, J., & Gançarski, P. (2011). Clustering of satellite image time series under time warping. In 2011 6th International Workshop on the Analysis of Multi-Temporal Remote Sensing Images, Multi-Temp 2011 - Proceedings (pp. 69-72). Article 6005050 IEEE, Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/Multi-Temp.2011.6005050

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title = "Clustering of satellite image time series under time warping",

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 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.",

keywords = "Clustering, Dynamic Time Warping, Remote Sensing, Satellite Image Time Series",

author = "Fran{\c c}ois Petitjean and Jordi Inglada and Pierre Gan{\c c}arski",

year = "2011",

doi = "10.1109/Multi-Temp.2011.6005050",

language = "English",

isbn = "9781457712036",

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booktitle = "2011 6th International Workshop on the Analysis of Multi-Temporal Remote Sensing Images, Multi-Temp 2011 - Proceedings",

publisher = "IEEE, Institute of Electrical and Electronics Engineers",

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note = "International Workshop on the Analysis of Multi-Temporal Remote Sensing Images 2011, Multi-Temp 2011 ; Conference date: 12-07-2011 Through 14-07-2011",

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Petitjean, F, Inglada, J & Gançarski, P 2011, Clustering of satellite image time series under time warping. in 2011 6th International Workshop on the Analysis of Multi-Temporal Remote Sensing Images, Multi-Temp 2011 - Proceedings., 6005050, IEEE, Institute of Electrical and Electronics Engineers, pp. 69-72, International Workshop on the Analysis of Multi-Temporal Remote Sensing Images 2011, Trento, Italy, 12/07/11. https://doi.org/10.1109/Multi-Temp.2011.6005050

Clustering of satellite image time series under time warping. / Petitjean, François; Inglada, Jordi; Gançarski, Pierre.
2011 6th International Workshop on the Analysis of Multi-Temporal Remote Sensing Images, Multi-Temp 2011 - Proceedings. IEEE, Institute of Electrical and Electronics Engineers, 2011. p. 69-72 6005050.

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Other › peer-review

TY - GEN

T1 - Clustering of satellite image time series under time warping

AU - Petitjean, François

AU - Inglada, Jordi

AU - Gançarski, Pierre

N1 - Conference code: 6th

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Y1 - 2011

N2 - 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.

AB - 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.

KW - Clustering

KW - Dynamic Time Warping

KW - Remote Sensing

KW - Satellite Image Time Series

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U2 - 10.1109/Multi-Temp.2011.6005050

DO - 10.1109/Multi-Temp.2011.6005050

M3 - Conference Paper

AN - SCOPUS:80053108950

SN - 9781457712036

SP - 69

EP - 72

BT - 2011 6th International Workshop on the Analysis of Multi-Temporal Remote Sensing Images, Multi-Temp 2011 - Proceedings

PB - IEEE, Institute of Electrical and Electronics Engineers

T2 - International Workshop on the Analysis of Multi-Temporal Remote Sensing Images 2011

Y2 - 12 July 2011 through 14 July 2011

ER -

Clustering of satellite image time series under time warping

Abstract

Workshop

Keywords

UN SDGs

Access to Document

Other files and links

Efficient satellite image time series analysis under time warping

Cite this