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Ranking evolution maps for Satellite Image Time Series exploration: application to crustal deformation and environmental monitoring

Meger, Nicolas and Rigotti, Christophe and Pothier, Catherine and Nguyen, Tuan and Lodge, Felicity and Gueguen, Lionel and Andreoli, Remi and Doin, Marie-Pierre and Datcu, Mihai (2018) Ranking evolution maps for Satellite Image Time Series exploration: application to crustal deformation and environmental monitoring. Data Mining and Knowledge Discovery (2018), pp. 1-37. Springer. DOI: 10.1007/s10618-018-0591-9 ISSN 1384-5810

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Official URL: https://hal.archives-ouvertes.fr/hal-01898015/file/2018_Ranking_Evolution_Maps_for_Satellite_Image_Time_Series_Exploration_N_Meger_et_al.pdf

Abstract

Satellite Image Time Series (SITS) are large datasets containing spatiotemporal information about the surface of the Earth. In order to exploit the potential of such series, SITS analysis techniques have been designed for various applications such as earthquake monitoring, urban expansion assessment or glacier dynamic analysis. In this paper, we present an unsupervised technique for browsing SITS in preliminary explorations, before deciding whether to start deeper and more time consuming analyses. Such methods are lacking in today's analyst toolbox, especially when it comes to stimulating the reuse of the ever growing list of available SITS. The method presented in this paper builds a summary of a SITS in the form of a set of maps depicting spatiotemporal phenomena. These maps are selected using an entropy-based ranking and a swap randomization technique. The approach is general and can handle either optical or radar SITS. As illustrated on both kinds of SITS, meaningful summaries capturing crustal deformation and environmental phenomena are produced. They can be computed on demand or precomputed once and stored together with the SITS for further usage.

Item URL in elib:https://elib.dlr.de/123454/
Document Type:Article
Title:Ranking evolution maps for Satellite Image Time Series exploration: application to crustal deformation and environmental monitoring
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Meger, NicolasUniversit́e Savoie Mont BlancUNSPECIFIED
Rigotti, ChristopheUniversité de LyonUNSPECIFIED
Pothier, CatherineUniversité de LyonUNSPECIFIED
Nguyen, TuanUniversit́e Savoie Mont BlancUNSPECIFIED
Lodge, FelicityUniversit́e Savoie Mont BlancUNSPECIFIED
Gueguen, LionelUber TechnologiesUNSPECIFIED
Andreoli, RemiBluecham SASUNSPECIFIED
Doin, Marie-PierreUniv. Grenoble AlpesUNSPECIFIED
Datcu, MihaiMihai.Datcu (at) dlr.deUNSPECIFIED
Date:September 2018
Journal or Publication Title:Data Mining and Knowledge Discovery
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In SCOPUS:Yes
In ISI Web of Science:Yes
DOI :10.1007/s10618-018-0591-9
Page Range:pp. 1-37
Publisher:Springer
ISSN:1384-5810
Status:Published
Keywords:SITS, Environment Monitoring, mutual Information
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Erdbeobachtung
DLR - Research theme (Project):R - Vorhaben hochauflösende Fernerkundungsverfahren
Location: Oberpfaffenhofen
Institutes and Institutions:Remote Sensing Technology Institute > EO Data Science
Deposited By: Dumitru, Corneliu Octavian
Deposited On:17 Dec 2018 11:02
Last Modified:17 Dec 2018 11:02

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