Evaluation of feature selection methods for object-based land cover mapping of unmanned aerial vehicle imagery using random forest and support vector machine classifiers

ISPRS International Journal of Geo-Information

Volumn 6, Issue 2, 2017, Pages

  Ma, Lei ^a,b   Fu, Tengyu ^a   Blaschke, Thomas ^b   Li, Manchun ^a   Tiede, Dirk ^b   Zhou, Zhenjin ^a   Ma, Xiaoxue ^c   Chen, Deliang ^a  

^a NANJING UNIVERSITY   (China)

^b UNIVERSITY OF SALZBURG   (Austria)

^c JIANGSU SECOND NORMAL UNIVERSITY   (China)

Author keywords

CFS; Classification; Feature selection; High resolution image; Object based image analysis (OBIA); Random forest; Support vector machines; SVM RFE

Indexed keywords

EID: 85014908663     PISSN: None     EISSN: 22209964     Source Type: Journal    
DOI: 10.3390/ijgi6020051     Document Type: Article

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