Löw, Fabian und Schorcht, Gunther und Michel, U. und Dech, Stefan und Conrad, Christopher (2012) Per-field crop classification in irrigated agricultural regions in middle Asia using random forest and support vector machine ensemble. In: Proc. SPIE 8538, Earth Resources and Environmental Remote Sensing/GIS Applications III, 85380R, Seiten 1-11. SPIE Remote Sensing, 2012-09-24 - 2012-09-27, Edinburgh, UK. doi: 10.1117/12.974588.
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Offizielle URL: http://proceedings.spiedigitallibrary.org/proceeding.aspx?articleid=1387492
Kurzfassung
Accurate crop identification and crop area estimation are important for studies on irrigated agricultural systems, yield and water demand modeling, and agrarian policy development. In this study a novel combination of Random Forest (RF) and Support Vector Machine (SVM) classifiers is presented that (i) enhances crop classification accuracy and (ii) provides spatial information on map uncertainty. The methodology was implemented over four distinct irrigated sites in Middle Asia using RapidEye time series data. The RF feature importance statistics was used as feature-selection strategy for the SVM to assess possible negative effects on classification accuracy caused by an oversized feature space. The results of the individual RF and SVM classifications were combined with rules based on posterior classification probability and estimates of classification probability entropy. SVM classification performance was increased by feature selection through RF. Further experimental results indicate that the hybrid classifier improves overall classification accuracy in comparison to the single classifiers as well as user´s and producer´s accuracy.
elib-URL des Eintrags: | https://elib.dlr.de/91639/ | ||||||||||||||||||||||||
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Dokumentart: | Konferenzbeitrag (Vortrag) | ||||||||||||||||||||||||
Titel: | Per-field crop classification in irrigated agricultural regions in middle Asia using random forest and support vector machine ensemble | ||||||||||||||||||||||||
Autoren: |
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Datum: | 2012 | ||||||||||||||||||||||||
Erschienen in: | Proc. SPIE 8538, Earth Resources and Environmental Remote Sensing/GIS Applications III, 85380R | ||||||||||||||||||||||||
Referierte Publikation: | Ja | ||||||||||||||||||||||||
Open Access: | Nein | ||||||||||||||||||||||||
Gold Open Access: | Nein | ||||||||||||||||||||||||
In SCOPUS: | Nein | ||||||||||||||||||||||||
In ISI Web of Science: | Nein | ||||||||||||||||||||||||
DOI: | 10.1117/12.974588 | ||||||||||||||||||||||||
Seitenbereich: | Seiten 1-11 | ||||||||||||||||||||||||
Status: | veröffentlicht | ||||||||||||||||||||||||
Stichwörter: | Ensemble classifier, feature selection, Hughes phenomenon, map uncertainty, random forest (RF), RapidEye, support vector machine (SVM) | ||||||||||||||||||||||||
Veranstaltungstitel: | SPIE Remote Sensing | ||||||||||||||||||||||||
Veranstaltungsort: | Edinburgh, UK | ||||||||||||||||||||||||
Veranstaltungsart: | internationale Konferenz | ||||||||||||||||||||||||
Veranstaltungsbeginn: | 24 September 2012 | ||||||||||||||||||||||||
Veranstaltungsende: | 27 September 2012 | ||||||||||||||||||||||||
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 - Geowissenschaftl. Fernerkundungs- und GIS-Verfahren | ||||||||||||||||||||||||
Standort: | Oberpfaffenhofen | ||||||||||||||||||||||||
Institute & Einrichtungen: | Deutsches Fernerkundungsdatenzentrum Deutsches Fernerkundungsdatenzentrum > Leitungsbereich DFD | ||||||||||||||||||||||||
Hinterlegt von: | Wöhrl, Monika | ||||||||||||||||||||||||
Hinterlegt am: | 12 Dez 2014 14:50 | ||||||||||||||||||||||||
Letzte Änderung: | 24 Apr 2024 19:57 |
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