| Classification of CBERS-2 Imagery with Fuzzy ARTMAP Classifier |
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| 作者姓名： | LUO Chengfeng LIU Zhengjun YAN Qin |
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| 作者单位： | LUO Chengfeng LIU Zhengjun YAN Qin LUO Chengfeng，Institute of Photogrammetry and Remote Sensing. Chinese Academy of Surveying and Mapping，16 Beitaiping Road，Beijing 100039，China. |
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| 基金项目： | Supported by the National Social Development Research Program of China (No.2004DE100625). |
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| 摘 要： | A fuzzy ARTMAP classifier is adopted for a classification experiment of CBERS-2 imagery. The fundamental theory and processing about the algorithm are first introduced, followed with a land-use classification experiment in Shihezi County on CBERS-2 high resolution imagery. Three classifiers are compared: maximum likelihood classifier (MLC), error back propagation (BP) classifier, and fuzzy ARTMAP classifier. The comparison shows comparably better results for the fuzzy ARTMAP classifier, with overall classification accuracy of 9.9% and 4.6% higher than that of MLC and BP. The results also prove that the fuzzy ARTMAP classifier has better discernment in identifying bare soil on CBERS-2 imagery.
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| 关 键 词： | 模糊ARTMAP分类器 CBERS-2图象 分类实验 土地利用 |
| 文章编号： | 1009-5020（2007）02-124-04 |
| 修稿时间： | 2007-03-23 |
Classification of CBERS-2 imagery with fuzzy ARTMAP classifier |
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| LUO Chengfeng LIU Zhengjun YAN Qin.Classification of CBERS-2 Imagery with Fuzzy ARTMAP Classifier[J].Geo-Spatial Information Science,2007,10(2):124-127. |
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| Authors: | Luo Chengfeng Liu Zhengjun Yan Qin |
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| Institution: | (1) Institute of Photogrammetry and Remote Sensing, Chinese Academy of Surveying and Mapping, 16 Beitaiping Road, Beijing, 100039, China |
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| Abstract: | A fuzzy ARTMAP classifier is adopted for a classification experiment of CBERS-2 imagery. The fundamental theory and processing about the algorithm are first introduced, followed with a land-use classification experiment in Shihezi County on CBERS-2 high resolution imagery. Three classifiers are compared: maximum likelihood classifier (MLC), error back propagation (BP) classifier, and fuzzy ARTMAP classifier. The comparison shows comparably better results for the fuzzy ARTMAP classifier, with overall classification accuracy of 9.9% and 4.6% higher than that of MLC and BP. The results also prove that the fuzzy ARTMAP classifier has better discernment in identifying bare soil on CBERS-2 imagery. |
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| Keywords: | fuzzy ARTMAP CBERS-2 imagery classification |
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