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

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

In previous classification studies, three non-parametric classifiers, Random Forest (RF), k-Nearest Neighbor (kNN), and Support Vector Machine (SVM), were reported as the foremost classifiers at producing high accuracies. However, only a few studies have compared the performances of these classifier...

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Bibliographic Details
Main Authors: Phan Thanh Noi, Martin Kappas
Format: Article
Language:English
Published: MDPI AG 2017-12-01
Series:Sensors
Subjects:
Sentinel-2
Random Forest (RF)
Support Vector Machine (SVM)
k-Nearest Neighbor (kNN)
classification algorithms
training sample size
Online Access:https://www.mdpi.com/1424-8220/18/1/18

Internet

https://www.mdpi.com/1424-8220/18/1/18

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