A pattern-based method for handling confidence measures while mining satellite displacement field time series. Application to Greenland ice sheet and Alpine glaciers
International audience For more than 40 years, Earth observation satellites have been regularly providing images of glaciers that can be used to derive surface displacement fields and study their dynamics. In the context of global warming, the analysis of Displacement Field Time Series (DFTS) can pr...
Published in: | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
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Main Authors: | , , , , , , |
Other Authors: | , , , , , , , , , , , , , , , , , , , , , , , |
Format: | Article in Journal/Newspaper |
Language: | English |
Published: |
HAL CCSD
2018
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Subjects: | |
Online Access: | https://hal.science/hal-01912708 https://hal.science/hal-01912708/document https://hal.science/hal-01912708/file/main.pdf https://doi.org/10.1109/JSTARS.2018.2874499 |
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openpolar |
institution |
Open Polar |
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Portail HAL de l'Université Lumière Lyon 2 |
op_collection_id |
ftunivlyon2 |
language |
English |
topic |
data mining climate change confidence measure displacement field time series (DFTS) Satellite image time series (SITS) glacier dynamics [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG] [SDU.STU]Sciences of the Universe [physics]/Earth Sciences |
spellingShingle |
data mining climate change confidence measure displacement field time series (DFTS) Satellite image time series (SITS) glacier dynamics [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG] [SDU.STU]Sciences of the Universe [physics]/Earth Sciences Nguyen, Tuan Méger, Nicolas Rigotti, Christophe Pothier, Catherine Trouvé, Emmanuel Gourmelen, Noel Mugnier, Jean-Louis A pattern-based method for handling confidence measures while mining satellite displacement field time series. Application to Greenland ice sheet and Alpine glaciers |
topic_facet |
data mining climate change confidence measure displacement field time series (DFTS) Satellite image time series (SITS) glacier dynamics [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG] [SDU.STU]Sciences of the Universe [physics]/Earth Sciences |
description |
International audience For more than 40 years, Earth observation satellites have been regularly providing images of glaciers that can be used to derive surface displacement fields and study their dynamics. In the context of global warming, the analysis of Displacement Field Time Series (DFTS) can provide useful information. Efficient data mining techniques are thus required to extract meaningful displacement evolutions from such large and complex datasets. In this paper, a pattern-based data mining approach which handles confidence measures is proposed to analyze DFTS. In order to focus on the most reliable measurements, a displacement evolution reliability measure is defined. It is aimed at assessing the quality of each evolution and pruning the search space. Experiments on two different DFTS (annual displacement fields derived from optical data over Greenland ice sheet and 11-day displacement fields derived from SAR data over Alpine glaciers) show the potential of the proposed approach. |
author2 |
Université Savoie Mont Blanc (USMB Université de Savoie Université de Chambéry ) Polytech Annecy-Chambéry (EPU Ecole Polytechnique Universitaire de l'Université de Savoie ) Laboratoire d'Informatique, Systèmes, Traitement de l'Information et de la Connaissance (LISTIC) Data Mining and Machine Learning (DM2L) Laboratoire d'InfoRmatique en Image et Systèmes d'information (LIRIS) Université Lumière - Lyon 2 (UL2)-École Centrale de Lyon (ECL) Université de Lyon-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL) Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon) Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Université Lumière - Lyon 2 (UL2)-École Centrale de Lyon (ECL) Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS) Artificial Evolution and Computational Biology (BEAGLE) Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Inria Grenoble - Rhône-Alpes Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire de Biométrie et Biologie Evolutive - UMR 5558 (LBBE) Université Claude Bernard Lyon 1 (UCBL) Université de Lyon-Université de Lyon-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Centre National de la Recherche Scientifique (CNRS)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Centre National de la Recherche Scientifique (CNRS) Extraction de Caractéristiques et Identification (imagine) School of Geosciences Edinburgh University of Edinburgh (Edin.) Centre National de la Recherche Scientifique (CNRS) Institut des Sciences de la Terre (ISTerre) Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux (IFSTTAR)-Institut national des sciences de l'Univers (INSU - CNRS)-Institut de recherche pour le développement IRD : UR219-Université Savoie Mont Blanc (USMB Université de Savoie Université de Chambéry )-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes 2016-2019 (UGA 2016-2019 ) Funding for this project was provided by a grant from la Région Auvergne-Rhône-Alpes (Tuan Nguyen’s grant). The work was also supported by a University Savoie Mont Blanc AAP Montagne grant - project BG Big data pour la surveillance des Glaciers.Thanks to the German Aerospace Agency (DLR) for the TerraSAR-X images (project MTH0232). ANR-15-CE23-0012,PHOENIX,Parcimonie, observations non-stationnaires de grandes dimensions, modélisation des séries chronologiques d'images et télédétection(2015) ANR-10-LABX-0088,IMU,Urban Worlds Intelligences(2010) |
format |
Article in Journal/Newspaper |
author |
Nguyen, Tuan Méger, Nicolas Rigotti, Christophe Pothier, Catherine Trouvé, Emmanuel Gourmelen, Noel Mugnier, Jean-Louis |
author_facet |
Nguyen, Tuan Méger, Nicolas Rigotti, Christophe Pothier, Catherine Trouvé, Emmanuel Gourmelen, Noel Mugnier, Jean-Louis |
author_sort |
Nguyen, Tuan |
title |
A pattern-based method for handling confidence measures while mining satellite displacement field time series. Application to Greenland ice sheet and Alpine glaciers |
title_short |
A pattern-based method for handling confidence measures while mining satellite displacement field time series. Application to Greenland ice sheet and Alpine glaciers |
title_full |
A pattern-based method for handling confidence measures while mining satellite displacement field time series. Application to Greenland ice sheet and Alpine glaciers |
title_fullStr |
A pattern-based method for handling confidence measures while mining satellite displacement field time series. Application to Greenland ice sheet and Alpine glaciers |
title_full_unstemmed |
A pattern-based method for handling confidence measures while mining satellite displacement field time series. Application to Greenland ice sheet and Alpine glaciers |
title_sort |
pattern-based method for handling confidence measures while mining satellite displacement field time series. application to greenland ice sheet and alpine glaciers |
publisher |
HAL CCSD |
publishDate |
2018 |
url |
https://hal.science/hal-01912708 https://hal.science/hal-01912708/document https://hal.science/hal-01912708/file/main.pdf https://doi.org/10.1109/JSTARS.2018.2874499 |
geographic |
Greenland |
geographic_facet |
Greenland |
genre |
glacier Greenland Ice Sheet |
genre_facet |
glacier Greenland Ice Sheet |
op_source |
ISSN: 1939-1404 IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing https://hal.science/hal-01912708 IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2018, 11 (11), pp.4390 - 4402. ⟨10.1109/JSTARS.2018.2874499⟩ |
op_relation |
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op_rights |
info:eu-repo/semantics/OpenAccess |
op_doi |
https://doi.org/10.1109/JSTARS.2018.2874499 |
container_title |
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
container_volume |
11 |
container_issue |
11 |
container_start_page |
4390 |
op_container_end_page |
4402 |
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1802644502084583424 |
spelling |
ftunivlyon2:oai:HAL:hal-01912708v1 2024-06-23T07:53:02+00:00 A pattern-based method for handling confidence measures while mining satellite displacement field time series. Application to Greenland ice sheet and Alpine glaciers Nguyen, Tuan Méger, Nicolas Rigotti, Christophe Pothier, Catherine Trouvé, Emmanuel Gourmelen, Noel Mugnier, Jean-Louis Université Savoie Mont Blanc (USMB Université de Savoie Université de Chambéry ) Polytech Annecy-Chambéry (EPU Ecole Polytechnique Universitaire de l'Université de Savoie ) Laboratoire d'Informatique, Systèmes, Traitement de l'Information et de la Connaissance (LISTIC) Data Mining and Machine Learning (DM2L) Laboratoire d'InfoRmatique en Image et Systèmes d'information (LIRIS) Université Lumière - Lyon 2 (UL2)-École Centrale de Lyon (ECL) Université de Lyon-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL) Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon) Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Université Lumière - Lyon 2 (UL2)-École Centrale de Lyon (ECL) Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS) Artificial Evolution and Computational Biology (BEAGLE) Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Inria Grenoble - Rhône-Alpes Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire de Biométrie et Biologie Evolutive - UMR 5558 (LBBE) Université Claude Bernard Lyon 1 (UCBL) Université de Lyon-Université de Lyon-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Centre National de la Recherche Scientifique (CNRS)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Centre National de la Recherche Scientifique (CNRS) Extraction de Caractéristiques et Identification (imagine) School of Geosciences Edinburgh University of Edinburgh (Edin.) Centre National de la Recherche Scientifique (CNRS) Institut des Sciences de la Terre (ISTerre) Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux (IFSTTAR)-Institut national des sciences de l'Univers (INSU - CNRS)-Institut de recherche pour le développement IRD : UR219-Université Savoie Mont Blanc (USMB Université de Savoie Université de Chambéry )-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes 2016-2019 (UGA 2016-2019 ) Funding for this project was provided by a grant from la Région Auvergne-Rhône-Alpes (Tuan Nguyen’s grant). The work was also supported by a University Savoie Mont Blanc AAP Montagne grant - project BG Big data pour la surveillance des Glaciers.Thanks to the German Aerospace Agency (DLR) for the TerraSAR-X images (project MTH0232). ANR-15-CE23-0012,PHOENIX,Parcimonie, observations non-stationnaires de grandes dimensions, modélisation des séries chronologiques d'images et télédétection(2015) ANR-10-LABX-0088,IMU,Urban Worlds Intelligences(2010) 2018-10-30 https://hal.science/hal-01912708 https://hal.science/hal-01912708/document https://hal.science/hal-01912708/file/main.pdf https://doi.org/10.1109/JSTARS.2018.2874499 en eng HAL CCSD IEEE info:eu-repo/semantics/altIdentifier/doi/10.1109/JSTARS.2018.2874499 hal-01912708 https://hal.science/hal-01912708 https://hal.science/hal-01912708/document https://hal.science/hal-01912708/file/main.pdf doi:10.1109/JSTARS.2018.2874499 info:eu-repo/semantics/OpenAccess ISSN: 1939-1404 IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing https://hal.science/hal-01912708 IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2018, 11 (11), pp.4390 - 4402. ⟨10.1109/JSTARS.2018.2874499⟩ data mining climate change confidence measure displacement field time series (DFTS) Satellite image time series (SITS) glacier dynamics [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG] [SDU.STU]Sciences of the Universe [physics]/Earth Sciences info:eu-repo/semantics/article Journal articles 2018 ftunivlyon2 https://doi.org/10.1109/JSTARS.2018.2874499 2024-05-27T14:08:17Z International audience For more than 40 years, Earth observation satellites have been regularly providing images of glaciers that can be used to derive surface displacement fields and study their dynamics. In the context of global warming, the analysis of Displacement Field Time Series (DFTS) can provide useful information. Efficient data mining techniques are thus required to extract meaningful displacement evolutions from such large and complex datasets. In this paper, a pattern-based data mining approach which handles confidence measures is proposed to analyze DFTS. In order to focus on the most reliable measurements, a displacement evolution reliability measure is defined. It is aimed at assessing the quality of each evolution and pruning the search space. Experiments on two different DFTS (annual displacement fields derived from optical data over Greenland ice sheet and 11-day displacement fields derived from SAR data over Alpine glaciers) show the potential of the proposed approach. Article in Journal/Newspaper glacier Greenland Ice Sheet Portail HAL de l'Université Lumière Lyon 2 Greenland IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 11 11 4390 4402 |