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松辽平原黑土区Aster数据光谱特征及自动分类研究
引用本文:王耿明,姜琦刚,李远华,张红红.松辽平原黑土区Aster数据光谱特征及自动分类研究[J].世界地质,2007,26(3):313-318.
作者姓名:王耿明  姜琦刚  李远华  张红红
作者单位:吉林大学,地球探测科学与技术学院,长春,130026
基金项目:中国地质调查局松辽平原经济区第四系基础地质遥感调查项目
摘    要:为研究松辽平原黑土退化状况,以Aster数据光谱特征作为选择最佳波段组合的理论依据,人机交互处理达到计算机自动分类的目的。通过多波段假彩色合成对比发现,Aster数据可见光/近红外波段3N、2、1的组合效果最佳,选择这种组合进行分类有助于提高分类精度。研究区分类结果表明:最大似然分类法总体精度比最小距离法约高6%,两种分类方法配合使用可综合提高分类精度。

关 键 词:松辽平原  黑土区  Aster数据  光谱特征  自动分类
文章编号:1004-5589(2007)03-0313-06
修稿时间:2006-11-28

Research on spectral characteristics of aster image in black soil area of Songliao Plain and their automatic classification
WANG Geng-ming,JIANG Qi-gang,LI Yuan-hua,ZHANG Hong-hong.Research on spectral characteristics of aster image in black soil area of Songliao Plain and their automatic classification[J].World Geology,2007,26(3):313-318.
Authors:WANG Geng-ming  JIANG Qi-gang  LI Yuan-hua  ZHANG Hong-hong
Institution:College of Geoexploration Science and Technology, Jilin University, Changchun 130026, China
Abstract:In order to study the black soil degradation in Songliao Plain, the authors chose the optimal wave band based on the spectral characteristics of Aster image, and realized the computerized automatic classification by means of man-machlne interactive processing. The results show that visible/near-IR band 3N, 2, 1 of Aster image are best for the combination of wave bands through comparing pseudo color composite of multiple bands, which is the best wave band combination in improving the classified accuracy. The consequence of classification shows that the classified effect of maximum likelihood method is much better than minimum distance method; the mutual use of the two methods can greatly improve the classified accuracy.
Keywords:Songliao Plain  black soil area  Aster image  spectral characteristics  automatic classification
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