| 基于TM数据和ANN的河流水质参数监测研究 |
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| 引用本文： | 王孝武,孙水裕.基于TM数据和ANN的河流水质参数监测研究[J].环境工程学报,2009,3(8):1532-1536. |
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| 作者姓名： | 王孝武 孙水裕 |
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| 作者单位： | 广东工业大学环境科学与工程学院,广州,510090 |
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| 摘 要： | 以珠江水系广州河段为研究对象，联合使用遥感（RS）和人工神经网络（ANN）技术对珠江水质进行分析监测。这种技术主要是利用GIS对RS图像进行地理定位，然后利用RS专用软件提取定位点的RS数据，最后通过建立前馈误差反传人工神经网络（BP网络），确定TM数据前5个波段在定位点的反射率与水质3个主要参数的映射关系，即建立RS数据与水质的映射模型。经过检验，该技术监测误差小于16%，基本能满足当前实际需要。
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| 关 键 词： | RSGISTMANN珠江水系水质监测 |
Study on monitoring of river water quality based on TM and ANN |
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| Wang Xiaowu and Sun Shuiyu.Study on monitoring of river water quality based on TM and ANN[J].Techniques and Equipment for Environmental Pollution Control,2009,3(8):1532-1536. |
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| Authors: | Wang Xiaowu and Sun Shuiyu |
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| Institution: | Faculty of Environmental Science and Engineering, Guangdong University of Technology, Guangzhou 510090,China and Faculty of Environmental Science and Engineering, Guangdong University of Technology, Guangzhou 510090,China |
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| Abstract: | In this study, remote sensing (RS) and artificial neural networks (ANN) are combined to monitor the Pearl River in Guangzhou City. This combination is regarded as a new technology for water quality. In the application of the new measurement technology, firstly, geography location is received by GIS and RS pictures. Secondly, RS data of location is gained by exclusive RS software. Finally, BP network is built up, so the relation between echo rate of five frontal bands of TM data is found. The error of forecast by the new technology is less than 16% and so the new technology can meet practical needs. |
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| Keywords: | RS GIS TM ANN RS GIS TM ANN the Pearl River water monitoring |
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