Leichtle, Tobias und Geiß, Christian und Wurm, Michael und Lakes, Tobia und Taubenböck, Hannes (2017) Evaluation of clustering algorithms for unsupervised change detection in VHR remote sensing imagery. In: 2017 Joint Urban Remote Sensing Event (JURSE), Seiten 1-4. IEEE Xplore. Joint Urban Remote Sensing Event (JURSE) 2017, 2017-03-06 - 2017-03-08, Dubai, UAE. doi: 10.1109/JURSE.2017.7924625. ISBN 978-1-5090-5808-2.
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Offizielle URL: http://ieeexplore.ieee.org/document/7924625/
Kurzfassung
Remote sensing has proven to be an adequate tool for observation of changes to the Earth’s surface. Especially modern space-borne sensors with very-high spatial resolution offer new capabilities for monitoring of dynamic urban environments. In this context, clustering is a well suited technique for unsupervised and thus highly automatic detection of changes. In this study, seven partitioning clustering algorithms from different methodological categories are evaluated regarding their suitability for unsupervised change detection. In addition, object-based feature sets of different characteristics are included in the analysis assessing their discriminative power for classification of changed against unchanged buildings. In general, the most important property of favorable algorithms is that they do not require additional arbitrary input parameters except the number of clusters. Best results were achieved based on the clustering algorithms k-means, partitioning around medoids, genetic k-means and self-organizing map clustering with accuracies in terms of κ statistics of 0.8 to 0.9 and beyond.
elib-URL des Eintrags: | https://elib.dlr.de/111485/ | ||||||||||||||||||||||||
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Dokumentart: | Konferenzbeitrag (Poster) | ||||||||||||||||||||||||
Titel: | Evaluation of clustering algorithms for unsupervised change detection in VHR remote sensing imagery | ||||||||||||||||||||||||
Autoren: |
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Datum: | 2017 | ||||||||||||||||||||||||
Erschienen in: | 2017 Joint Urban Remote Sensing Event (JURSE) | ||||||||||||||||||||||||
Referierte Publikation: | Ja | ||||||||||||||||||||||||
Open Access: | Ja | ||||||||||||||||||||||||
Gold Open Access: | Nein | ||||||||||||||||||||||||
In SCOPUS: | Nein | ||||||||||||||||||||||||
In ISI Web of Science: | Nein | ||||||||||||||||||||||||
DOI: | 10.1109/JURSE.2017.7924625 | ||||||||||||||||||||||||
Seitenbereich: | Seiten 1-4 | ||||||||||||||||||||||||
Verlag: | IEEE Xplore | ||||||||||||||||||||||||
Name der Reihe: | 2017 Joint Urban Remote Sensing Event (JURSE) | ||||||||||||||||||||||||
ISBN: | 978-1-5090-5808-2 | ||||||||||||||||||||||||
Status: | veröffentlicht | ||||||||||||||||||||||||
Stichwörter: | change detection; clustering; object-based image analysis; very-high resolution (VHR) remote sensing | ||||||||||||||||||||||||
Veranstaltungstitel: | Joint Urban Remote Sensing Event (JURSE) 2017 | ||||||||||||||||||||||||
Veranstaltungsort: | Dubai, UAE | ||||||||||||||||||||||||
Veranstaltungsart: | internationale Konferenz | ||||||||||||||||||||||||
Veranstaltungsbeginn: | 6 März 2017 | ||||||||||||||||||||||||
Veranstaltungsende: | 8 März 2017 | ||||||||||||||||||||||||
HGF - Forschungsbereich: | Luftfahrt, Raumfahrt und Verkehr | ||||||||||||||||||||||||
HGF - Programm: | Raumfahrt | ||||||||||||||||||||||||
HGF - Programmthema: | Erdbeobachtung | ||||||||||||||||||||||||
DLR - Schwerpunkt: | Raumfahrt | ||||||||||||||||||||||||
DLR - Forschungsgebiet: | R EO - Erdbeobachtung | ||||||||||||||||||||||||
DLR - Teilgebiet (Projekt, Vorhaben): | R - Vorhaben Zivile Kriseninformation und Georisiken (alt) | ||||||||||||||||||||||||
Standort: | Oberpfaffenhofen | ||||||||||||||||||||||||
Institute & Einrichtungen: | Deutsches Fernerkundungsdatenzentrum > Georisiken und zivile Sicherheit Deutsches Fernerkundungsdatenzentrum > Landoberfläche | ||||||||||||||||||||||||
Hinterlegt von: | Leichtle, Tobias | ||||||||||||||||||||||||
Hinterlegt am: | 27 Mär 2017 14:37 | ||||||||||||||||||||||||
Letzte Änderung: | 24 Apr 2024 20:16 |
Verfügbare Versionen dieses Eintrags
- Evaluation of clustering algorithms for unsupervised change detection in VHR remote sensing imagery. (deposited 27 Mär 2017 14:37) [Gegenwärtig angezeigt]
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