中国岩溶2011，Vol.30Issue(2)：227-232,6.
基于面向对象分类方法在SPOT影像中的地物信息提取
Surface features' information extraction from SPOT images with object-oriented classification method
摘要
Abstract
With eCognition software of the object-oriented classification method, different segmentation parameters for each surface features in the images is set in the study area of Zhaidi, Guilin. When initial segmentation parameter is 30, shape is 0. 1, color is 0. 9, compactness is 0. 7 and smoothness is 0. 3, vegetation , non-vegetation and water body can be parted accurately. Further separation for vegetation and non-vegetation according to the established classification hierarchy, it is concluded that the results close to ideal if the selected segmentation scale is 80 and 50. Classification to the surface features that have been cut by means of eCognition and manually modification has resulted in relatively high accuracy - the general accuracy up to 96. 28% and the Kappa coefficient 95. 23%. Contrasting with the result by traditional way, the object-oriented classification method is of greater advantage in classifying high-resolution remote sensing data.关键词
eCognition/面向对象分类/类层次结构/分割/最大似然法分类Key words
eCognition/ object-oriented classification/ class hierarchy structure/ segmentation/ maximum likelihood classification分类
信息技术与安全科学引用本文复制引用
祖琪,袁希平,莫源富,袁磊..基于面向对象分类方法在SPOT影像中的地物信息提取[J].中国岩溶,2011,30(2):227-232,6.基金项目
中国地质科学院岩溶地质研究所基本科研业务费项目(2009016) （2009016）
