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Feature extraction and machine learning for the classification of active cropland in the Aral Sea Basin

Dimov, Dimo and Löw, Fabian and Ibrakhimov, Mirzahayot and Schönbrodt-Stitt, Sarah and Conrad, Christopher (2017) Feature extraction and machine learning for the classification of active cropland in the Aral Sea Basin. In: 2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), pp. 1-4. 2017 IEEE International Geoscience and Remote Sensing Symposium, 23.-28.07.2017, Fort Worth, Texas, USA.

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Item URL in elib:https://elib.dlr.de/115961/
Document Type:Conference or Workshop Item (Poster)
Title:Feature extraction and machine learning for the classification of active cropland in the Aral Sea Basin
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Dimov, Dimodimo.dimov (at) uni-wuerzburg.deUNSPECIFIED
Löw, Fabianfabian.loew (at) uni-wuerzburg.deUNSPECIFIED
Ibrakhimov, MirzahayotUNSPECIFIEDUNSPECIFIED
Schönbrodt-Stitt, Sarahsarah.schoenbrodt-stitt (at) uni-wuerzburg.deUNSPECIFIED
Conrad, Christopherchristopher.conrad (at) uni-wuerzburg.deUNSPECIFIED
Date:2017
Journal or Publication Title:2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)
Refereed publication:No
Open Access:No
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
Page Range:pp. 1-4
Status:Published
Keywords:Landsat, Crop classification, Feature extraction, Machine learning
Event Title:2017 IEEE International Geoscience and Remote Sensing Symposium
Event Location:Fort Worth, Texas, USA
Event Type:international Conference
Event Dates:23.-28.07.2017
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 Geowissenschaftl. Fernerkundungs- und GIS-Verfahren
Location: Oberpfaffenhofen
Institutes and Institutions:German Remote Sensing Data Center
Deposited By: Wöhrl, Monika
Deposited On:04 Dec 2017 11:36
Last Modified:15 Mar 2018 14:01

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