Higher Order Dynamic Conditional Random Fields Ensemble for Crop Type Classification in Radar Images

IEEE Transactions on Geoscience and Remote Sensing

Volumn 55, Issue 8, 2017, Pages 4638-4654

  Kenduiywo, Benson Kipkemboi ^a   Bargiel, Damian ^b   Soergel, Uwe ^c  

^a JOMO KENYATTA UNIVERSITY OF AGRICULTURE AND TECHNOLOGY   (Kenya)

^b DARMSTADT UNIVERSITY OF TECHNOLOGY   (Germany)

^c UNIVERSITY OF STUTTGART   (Germany)

Author keywords

Classifier ensemble; conditional random fields (CRFs); dynamic CRFs (DCRFs); phenology; radar; spatial temporal multitemporal classification

Indexed keywords

AGRICULTURE; BACKSCATTERING; BIOLOGY; CROPS; FOOD SUPPLY; FORESTRY; IMAGE CLASSIFICATION; IMAGE RECONSTRUCTION; IMAGE SEGMENTATION; MAXIMUM LIKELIHOOD; RADAR; RADAR IMAGING; RANDOM PROCESSES; REMOTE SENSING; VECTOR SPACES;

CLASSIFICATION TECHNIQUE; CONVENTIONAL TECHNIQUES; CROP TYPE CLASSIFICATION; ENSEMBLE CLASSIFICATION; HIGHER-ORDER DYNAMICS; MAXIMUM LIKELIHOOD CLASSIFIERS; POSTERIOR PROBABILITY; REMOTE SENSING IMAGES;

CLASSIFICATION (OF INFORMATION);

ACCURACY ASSESSMENT; BACKSCATTER; CROP PLANT; IMAGE CLASSIFICATION; LAND COVER; PHENOLOGY; PROBABILITY; RADAR; REMOTE SENSING; SATELLITE IMAGERY; SPATIOTEMPORAL ANALYSIS; TERRASAR-X;

EID: 85018913180     PISSN: 01962892     EISSN: None     Source Type: Journal    
DOI: 10.1109/TGRS.2017.2695326     Document Type: Article

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