| 基于BP神经网络的森林植被遥感分类研究 |
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| 引用本文： | 刘旭升,张晓丽.基于BP神经网络的森林植被遥感分类研究[J].林业资源管理,2005(1):51-54. |
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| 作者姓名： | 刘旭升 张晓丽 |
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| 作者单位： | 1. 国家林业局规划院,北京,100714
2. 北京林业大学资源与环境学院,北京,100083 |
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| 基金项目： | 北京林业大学校科研和教改项目 |
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| 摘 要： | 如何解决多类别图像的识别并满足一定的精度,是遥感图像研究中的一个关键问题,具有十分重要的意义。本文使用Landsat7ETM+遥感数据和森林资源分布图等地理辅助数据,用BP神经网络方法对森林植被进行了分类,并与最大似然法的分类结果进行精度比较分析。结果表明地理辅助数据参与的BP神经网络用于森林植被遥感图像分类其效果是较好的,是一种有效的图像分类方法。
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| 关 键 词： | 遥感 分类 森林 植被 BP人工神经网络 |
| 文章编号： | 1002-6622(2005)01-0051-04 |
Remote Sensing Classification of Forest Vegetation Based on Artificial Neural Network |
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| LIU Xusheng,ZHANG Xiaoli.Remote Sensing Classification of Forest Vegetation Based on Artificial Neural Network[J].Forest Resources Management,2005(1):51-54. |
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| Authors: | LIU Xusheng ZHANG Xiaoli |
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| Institution: | LIU Xusheng~1,ZHANG Xiaoli~2 |
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| Abstract: | It is a key issue of remote sensing image research to resolve the problem of multi-type images identification and meet the accuracy demand, and it has important significance for classification of forest vegetation, Landsat7ETM+ data, forest resource distribution map and other geographical assistance data,and also BP neural network. Its classification accuracy is improved compared to Maximum likelihood classifier.The results show the classification method combined with BP neural network and geographical assistance data is an effective approach. |
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| Keywords: | remote sensing classification forest vegetation BP artificial neural network |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
