| 基于BPNN算法的三门峡库区土地利用分类研究 |
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| 引用本文： | 易伟雄,王世岩,毛战坡,杨素珍,王亮. 基于BPNN算法的三门峡库区土地利用分类研究[J]. 人民黄河, 2012, 0(8): 96-98 |
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| 作者姓名： | 易伟雄 王世岩 毛战坡 杨素珍 王亮 |
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| 作者单位： | 中国地质大学水资源与环境学院;中国水利水电科学研究院 |
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| 基金项目： | 国家自然科学基金资助项目(50879093,51179207);中国水利水电科学研究院科研专项(1135) |
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| 摘 要： | 在主成分融合的基础上,利用BPNN算法对三门峡库区土地利用类型进行了分类研究,并对比分析了BPNN算法与MLC算法的分类效果。结果表明:BPNN算法的分类精确度总体上优于MLC算法,采用BPNN算法进行土地利用分类可以取得更好的分类效果;BPNN算法及MLC算法对水体及滩地的分类效果均较好,前者对于沼泽的分类效果要略好于后者,但BPNN算法及MLC算法对其他土地利用类型的分类精确度相比水体、滩地要低,并存在部分错分现象。
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| 关 键 词： | BP神经网络 MLC算法 主成分融合 土地利用分类 三门峡库区 |
Classification of Land Use Based on BP Algorithm in Sanmenxia Reservoir Area |
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| YI Wei-xiong,WANG Shi-yan,MAO Zhan-po,YANG Su-zhen,WANG Liang. Classification of Land Use Based on BP Algorithm in Sanmenxia Reservoir Area[J]. Yellow River, 2012, 0(8): 96-98 |
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| Authors: | YI Wei-xiong WANG Shi-yan MAO Zhan-po YANG Su-zhen WANG Liang |
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| Affiliation: | 1.School of Water Resources and Environment,China University of Geosciences,Beijing 100083,China; 2.China Institute of Water Resources and Hydropower Research,Beijing 100038,China) |
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| Abstract: | On the basis of principal component fusion,the land use classification of Sanmenxia Reservoir area was studied by BPNN algorithm.The results show that the classification based on BPNN algorithm is better than that of MLC classification algorithm in accuracy,the better classification results will be gained by the former.Classification precision of water and beach are relatively higher for both BPNN and MLC,however,BPNN can extract marsh information from image more correctly than that of MLC.Classification precision of other land-use types are lower than that of water and beach for both two classification algorithms,and mistakenly classified between different land-use types is also found in this two methods. |
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| Keywords: | BP Neural Net MLC algorithm principal component fusion land use classification Sanmenxia Reservoir |
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