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耦合小波变换和偏最小二乘的悬浮物浓度和浊度高光谱建模方法
引用本文:曹引,冶运涛,赵红莉,石玉波,蒋云钟. 耦合小波变换和偏最小二乘的悬浮物浓度和浊度高光谱建模方法[J]. 中国水利水电科学研究院学报, 2015, 0(3): 233-239
作者姓名:曹引  冶运涛  赵红莉  石玉波  蒋云钟
作者单位:东华大学环境科学与工程学院, 上海201620;中国水利水电科学研究院水资源研究所, 北京100038;中国水利水电科学研究院水资源研究所, 北京100038;中国水利水电科学研究院水资源研究所, 北京100038;水利部水资源司, 北京100053;中国水利水电科学研究院水资源研究所, 北京100038
基金项目:“十二五”国家科技支撑计划课题(2013BAB05B01);高分辨率对地观测系统重大专项(08-Y30B07-9001-13/15-01);国家自然科学基金项目(51309254,51209223);中国水利水电科学研究院科研专项(资基本科研1401)
摘    要:针对高光谱曲线中可能存在噪声以及传统半经验方法不能有效利用全部光谱信息的问题,提出了耦合Haar小波变换和偏最小二乘的水质遥感高光谱建模方法(Haar WT-PLS)。利用该方法,对在南四湖获取的实测高光谱数据经分解尺度为3的Haar小波变换后,将原始光谱数据压缩到47个特征变量;随后利用小波变换重构的光谱数据建立了悬浮物浓度和浊度的Haar WT-PLS反演模型,并进行了验证。结果表明:Haar WT-PLS反演悬浮物浓度和浊度精度较高,验证样本的均方根误差分别为25.05 mg/L和20.10NTU,平均相对误差分别为20.36%和13.88%。通过和单波段模型、一阶微分模型和波段比值模型进行精度对比分析,本文建立的Haar WT-PLS模型反演悬浮物浓度和浊度具有较高的精度和更好的稳定性。

关 键 词:小波变换  偏最小二乘法  高光谱  悬浮物  浊度  南四湖
收稿时间:2015-01-20

Hyperspectral modeling method of suspended solid concentration and turbidity based on the coupling of Haar wavelet transform and partial least squares
CAO Yin,YE Yuntao,ZHAO Hongli,SHI Yubo and JIANG Yunzhong. Hyperspectral modeling method of suspended solid concentration and turbidity based on the coupling of Haar wavelet transform and partial least squares[J]. Journal of China Institute of Water Resources and Hydropower Research, 2015, 0(3): 233-239
Authors:CAO Yin  YE Yuntao  ZHAO Hongli  SHI Yubo  JIANG Yunzhong
Affiliation:School of Environmental Science and Engineering, Donghua University, Shanghai 201620, China;Department of Water Resources, China Institute of Water Resources and Hydropower Research, Beijing 100038, China;Department of Water Resources, China Institute of Water Resources and Hydropower Research, Beijing 100038, China;Department of Water Resources, China Institute of Water Resources and Hydropower Research, Beijing 100038, China;Department of Water Resources Management, Ministry of Water Resources, Beijing 100053, China;Department of Water Resources, China Institute of Water Resources and Hydropower Research, Beijing 100038, China
Abstract:Aiming at the noise in hyperspectral curve and the problems that traditional semi-empirical meth-ods cannot effectively use all effective spectral information,hyperspectral modeling method of suspended sol-id concentration and turbidity based on the coupling of Haar wavelet transform and partial least squares (Haar wavelet transform) is proposed. Firstly, the original spectral data of Nansi Lake on July 22 to 23, 2014 are compressed to 47 feature variables using wavelet transform with the wavelet function Haar and de-compose scale 3. Secondly, according to the reconstruction data of spectra using wavelet transform, Haar WT-PLS inversion models of suspended solid concentration and turbidity are established and verified. The results show that inversion of suspended solid concentration and turbidity using Haar WT-PLS has higher accuracy and the root mean square errors of validation samples are 25.05 mg/L and 20.10 NTU, respective-ly. The average relative errors are 20.36 % and 13.88 %,respectively. Through the analysis and comparison of single band model, the first derivative model, band ratio models and Haar WT-PLS model, Haar WT-PLS model proposed in the paper has higher accuracy and stability to retrieve suspended solid concen-tration and turbidity.
Keywords:wavelet transform  partial least squares  hyperspectral  suspended solid  turbidity  Nansi Lake
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