| 基于BP神经网络模型的太湖悬浮物浓度遥感定量提取研究 |
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| 引用本文： | 吕恒,李新国,曹凯. 基于BP神经网络模型的太湖悬浮物浓度遥感定量提取研究[J]. 武汉大学学报(信息科学版), 2006, 31(8): 683-687 |
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| 作者姓名： | 吕恒 李新国 曹凯 |
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| 作者单位： | [1]中国科学院南京地理与湖泊研究所,南京市北京东路73号210008 [2]中国科学院研究生院,北京市玉泉路甲19号100039 [3]南京大学城市与资源学系,南京市汉口路22号210008 |
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| 摘 要： | 构建了含有一个隐含层的两层BP神经网络反演模型，以TM数据的前4个波段的反射率作为输入，以悬浮物浓度值作为输出，成功反演了太湖水体的悬浮物浓度。
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| 关 键 词： | BP神经网络模型 悬浮物浓度 太湖 定量反演 |
| 文章编号： | 1671-8860(2006)08-0683-04 |
| 修稿时间： | 2006-04-18 |
Quantitative Retrieval of Suspended Solid Concentration in Lake Taihu Based on BP Neural Net |
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| Abstract: | A two-layer BP neural net model is constructed with four input nodes of TM1,2,3,4 band reflectances,and one output node of suspended solid concentration(SSC) to retrieve SSC of Lake Taihu.The results demonstrated that BP neural net is very fit to quantitatively retrieve water quality of case II water with complex optic characteristic,and has much higher accuracy than the common linear model.A test was made and the results suggest that 13 had relative error(RE)RE of less than 30%,accounting for 81.25% of the total samples. |
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| Keywords: | BP neural net suspended solid concentration Lake Taihu quantitative retrieval |
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