Monitoring urban sprawl from Satellite Image Time Series

Francois Petitjean; Anne Puissant; Pierre Gançarski

doi:10.1109/IGARSS.2012.6352250

Monitoring urban sprawl from Satellite Image Time Series

Francois Petitjean, Anne Puissant, Pierre Gançarski

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

2 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. It has been shown that the Dynamic Time Warping (DTW) similarity measure makes it possible to compare radiometric time series with different lengths and sampling. This work aims at showing that DTW is also able to capture distorted phenomena sensed over a long satellite image time series. This article details the analysis of a satellite image time series sensed over 20 years; we show that DTW makes it possible to extract static phenomena, as well as distorted ones such as urbanized areas.

Original language	English
Title of host publication	IGARSS 2012 - 2012 IEEE International Geoscience and Remote Sensing Symposium
Publisher	IEEE, Institute of Electrical and Electronics Engineers
Pages	5963-5966
Number of pages	4
DOIs	https://doi.org/10.1109/IGARSS.2012.6352250
Publication status	Published - 2012
Externally published	Yes
Event	IEEE International Geoscience and Remote Sensing Symposium 2012 - International Congress Centre, Munich, Germany Duration: 22 Jul 2012 → 27 Jul 2012 Conference number: 32nd http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=6334512 (IEEE Conference Proceedings)

Conference

Conference	IEEE International Geoscience and Remote Sensing Symposium 2012
Abbreviated title	IGARSS 2012
Country/Territory	Germany
City	Munich
Period	22/07/12 → 27/07/12
Internet address	http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=6334512 (IEEE Conference Proceedings)

Keywords

Image classification
Image sequences
Remote Sensing
Time series analysis
Urban areas

UN SDGs

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

Access to Document

10.1109/IGARSS.2012.6352250

Cite this

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title = "Monitoring urban sprawl from Satellite Image Time Series",

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. It has been shown that the Dynamic Time Warping (DTW) similarity measure makes it possible to compare radiometric time series with different lengths and sampling. This work aims at showing that DTW is also able to capture distorted phenomena sensed over a long satellite image time series. This article details the analysis of a satellite image time series sensed over 20 years; we show that DTW makes it possible to extract static phenomena, as well as distorted ones such as urbanized areas.",

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year = "2012",

doi = "10.1109/IGARSS.2012.6352250",

language = "English",

pages = "5963--5966",

booktitle = "IGARSS 2012 - 2012 IEEE International Geoscience and Remote Sensing Symposium",

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

address = "United States of America",

note = "IEEE International Geoscience and Remote Sensing Symposium 2012, IGARSS 2012 ; Conference date: 22-07-2012 Through 27-07-2012",

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}

Petitjean, F, Puissant, A & Gançarski, P 2012, Monitoring urban sprawl from Satellite Image Time Series. in IGARSS 2012 - 2012 IEEE International Geoscience and Remote Sensing Symposium., 6352250, IEEE, Institute of Electrical and Electronics Engineers, pp. 5963-5966, IEEE International Geoscience and Remote Sensing Symposium 2012, Munich, Berlin, Germany, 22/07/12. https://doi.org/10.1109/IGARSS.2012.6352250

Monitoring urban sprawl from Satellite Image Time Series. / Petitjean, Francois; Puissant, Anne; Gançarski, Pierre.

IGARSS 2012 - 2012 IEEE International Geoscience and Remote Sensing Symposium. IEEE, Institute of Electrical and Electronics Engineers, 2012. p. 5963-5966 6352250.

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

TY - GEN

T1 - Monitoring urban sprawl from Satellite Image Time Series

AU - Petitjean, Francois

AU - Puissant, Anne

AU - Gançarski, Pierre

N1 - Conference code: 32nd

PY - 2012

Y1 - 2012

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. It has been shown that the Dynamic Time Warping (DTW) similarity measure makes it possible to compare radiometric time series with different lengths and sampling. This work aims at showing that DTW is also able to capture distorted phenomena sensed over a long satellite image time series. This article details the analysis of a satellite image time series sensed over 20 years; we show that DTW makes it possible to extract static phenomena, as well as distorted ones such as urbanized areas.

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. It has been shown that the Dynamic Time Warping (DTW) similarity measure makes it possible to compare radiometric time series with different lengths and sampling. This work aims at showing that DTW is also able to capture distorted phenomena sensed over a long satellite image time series. This article details the analysis of a satellite image time series sensed over 20 years; we show that DTW makes it possible to extract static phenomena, as well as distorted ones such as urbanized areas.

KW - Image classification

KW - Image sequences

KW - Remote Sensing

KW - Time series analysis

KW - Urban areas

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DO - 10.1109/IGARSS.2012.6352250

M3 - Conference Paper

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BT - IGARSS 2012 - 2012 IEEE International Geoscience and Remote Sensing Symposium

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T2 - IEEE International Geoscience and Remote Sensing Symposium 2012

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ER -

Monitoring urban sprawl from Satellite Image Time Series

Abstract

Conference

Keywords

UN SDGs

Access to Document

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Cite this