Comparison of Random Forest, k-Nearest Neighbor, and Support Vector Machine Classifiers for Land Cover Classification Using Sentinel-2 Imagery

Sensors (Basel, Switzerland)

Volumn 18, Issue 1, 2017, Pages

  Thanh Noi, Phan ^a,b   Kappas, Martin ^a  

^a UNIVERSITY OF GÖTTINGEN   (Germany)

^b VIETNAM NATIONAL UNIVERSITY OF AGRICULTURE   (Viet Nam)

Author keywords

classification algorithms; k Nearest Neighbor (kNN); Random Forest (RF); Sentinel 2; Support Vector Machine (SVM); training sample size

Indexed keywords

ARTICLE; CLASSIFICATION ALGORITHM; CONTROLLED STUDY; HUMAN; HUMAN EXPERIMENT; IMAGERY; K NEAREST NEIGHBOR; LAND USE; RANDOM FOREST; RIVER; SAMPLE SIZE; SUPPORT VECTOR MACHINE; VIET NAM;

EID: 85058234347     PISSN: None     EISSN: 14248220     Source Type: Journal    
DOI: 10.3390/s18010018     Document Type: Article

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