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洪泽湖湿地纹理特征参数分析 被引量:13

Parameter analysis of image texture of wetland in the Hongze Lake
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摘要 应用纹理特征进行影像分类,关键在于纹理特征参数的确定。以洪泽湖湿地典型地区为研究对象,选择灰度共生矩阵进行纹理特征计算,探讨灰度共生矩阵窗口尺寸、移动步长、方向和纹理特征统计量对淡水湖泊湿地的区分能力;然后,利用纹理特征和地物光谱特征,结合决策树方法对研究区湿地及其他主要地类进行分类,并通过混淆矩阵进行精度评价。结果表明:研究区湿地分类中纹理特征的最佳窗口大小为3像元×3像元,方向为90°,步长为1个像元,纹理特征统计量组合为均值、熵和相关度;分类精度为83.24%,Kappa为0.788,其结果验证了纹理特征参数选择的科学性和合理性。 The determination of parameters for texture analysis is crucial to remote sensing image classification. In this paper, the Hongze Lake wetlands were taken as the study area and the texture was calculated based on gray level co-occurrence matrix. The effect of the window size, moving step and direction in computing texture upon the separability of freshwater lake wetlands was discussed. The classification of wetlands was carried out based on decision tree classification by using texture and spectral features. The classification accuracy was assessed based on error matrix. It is shown that the parameters of 3 pixel × 3 pixel in the direction of 90° are the optimal ones. Mean, entropy, correlation are used for the classification of wetlands in the study area. The classification accuracy is 83 . 24% with Kappa of 0 . 788 . The results show that the effect of texture parameters upon the classification of freshwater lake wetlands is significant.
出处 《国土资源遥感》 CSCD 北大核心 2015年第1期75-80,共6页 Remote Sensing for Land & Resources
基金 中国科学院战略性先导科技专项项目(编号:XDA05050106) 生态十年专项项目(编号:STSN-01-05)共同资助
关键词 洪泽湖湿地 纹理特征 窗口尺寸 移动步长和方向 灰度共生矩阵 GRAY level CO-OCCURRENCE matrix(GLCM) Hongze Lake wetlands textural characteristics window size moving step and direction
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