Spatio-Temporal Clustering and Active Learning for Change Classification in Satellite Image Time Series

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing

Volumn 9, Issue 8, 2016, Pages 3642-3650

  Débonnaire, Nicolas ^a   Stumpf, André ^a   Puissant, Anne ^a  

^a UNIVERSITÉ DE STRASBOURG   (France)

Author keywords

Image classification; machine learning; satellite time series analysis; spatio temporal clustering

Indexed keywords

ALGORITHMS; ALUMINUM; ARTIFICIAL INTELLIGENCE; CLASSIFICATION (OF INFORMATION); CLUSTERING ALGORITHMS; DECISION TREES; HEURISTIC ALGORITHMS; IMAGE CLASSIFICATION; IMAGE RECONSTRUCTION; LEARNING SYSTEMS; REMOTE SENSING; SUPERVISED LEARNING; TIME SERIES; TIME SERIES ANALYSIS;

CHANGE DETECTION; LEARNING CURVES; LONG TIME SERIES; REMOTE SENSING IMAGE CLASSIFICATION; SATELLITE IMAGES; STANDARD MACHINES; STATE OF THE ART; TEMPORAL CLUSTERING;

LEARNING ALGORITHMS;

ALGORITHM; CLUSTER ANALYSIS; IMAGE CLASSIFICATION; MACHINE LEARNING; REMOTE SENSING; SATELLITE IMAGERY; SPATIOTEMPORAL ANALYSIS; TIME SERIES ANALYSIS;

AQUITAINE; ARCACHON BAY; COLMAR; FRANCE; GIRONDE;

EID: 84960540449     PISSN: 19391404     EISSN: 21511535     Source Type: Journal    
DOI: 10.1109/JSTARS.2016.2525940     Document Type: Article

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