Based on the data of ALOS image of Yiliang County,Yunnan Province,this paper discusses the use of the maximum likelihood method,support vector machine method and object-oriented support vector machine(SVM).The results show that maximum like-lihood classification accuracy is 79.33%,SVM classification accuracy 82.25%,oriented object based support vector machine classification accuracy 86.13%,and oriented-object based support vector machine classification method has better classification results.The results can provide a reference for the study of high-resolution remote sensing image classification。
TENG Quanxiao
,
XU Tianshu
. ALOS Remote Sensing Classification of Vegetation Based on Different Classification Methods[J]. Forest and Grassland Resources Research, 2015
, 0(4)
: 69
-72
.
DOI: 10.13466/j.cnki.lyzygl.2015.04.012
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