| 基于C4.5算法的遥感影像分类 |
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| 引用本文： | 夏双,阮仁宗,佘远见,颜梅春,张砾.基于C4.5算法的遥感影像分类[J].地理空间信息,2012,10(4):89-91,94. |
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| 作者姓名： | 夏双 阮仁宗 佘远见 颜梅春 张砾 |
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| 作者单位： | 河海大学地球科学与工程学院,江苏南京,210098 |
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| 基金项目： | 江苏省自然科学基金资助项目（BK2008360）; 江苏省博士后基金; 河海大学人才引进基金; 中央高校基本科研业务费专项资金项目（2009B12714、2009B11714） |
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| 摘 要： | 随着城市化进程的加快,湿地对整个生态系统的可持续发展具有重要的意义。以洪泽湖湿地为研究区,集合TM影像的光谱信息和纹理信息构建空间数据库,获取训练样本,并从训练样本集中获取分类规则;然后利用C4.5算法构建决策树,并基于知识规则推理得到遥感影像分类结果;最后将分类结果与传统的最大似然法进行比较分析。实验表明,基于C4.5算法得到的分类结果的分类总精度为91.9701%,其分类总精度结果明显高于传统的最大似然法的80.0885%;同样,前者的分类结果的Kappa系数为0.900 3,也远远高于最大似然法的0.746 5。
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| 关 键 词： | 洪泽湖湿地 空间数据库 C4.5决策树算法 最大似然法 知识规则 |
Classification of Remote Sensing Image Based on C4.5 Algorithm |
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| Abstract: | With the accelerated process of urbanization, wetlands have been crucial to the sustainable development of the entire ecosystem. In this paper, Hongze Lake wetlands were selected as the study area. A collection of spectral information and texture information on TM imagery was used to build a spatial database. Training samples were sampled and classification rules were got from training samples. Then the C4.5 algorithm was used to build decision trees. Classification results of the remote sensing imagery based on knowledge rules. Finally, the C4.5 algorithm was compared with the traditional maximum likelihood method. The results show that the overall accuracy of the results of the C4.5 algorithm, which is 91.970 1%, is significantly higher than that of maximum likelihood method, which is 80.088 5%. The former Kappa coefficient, which is 0.900 3, is also much higher than that of the maximum likelihood method, which is 0.746 5. |
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| Keywords: | Hongze Lake Wetlands spatial database C4 5 Algorithm Maximum Likelihood Method knowledge rules |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
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