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基于高光谱成像技术的土壤水分机理研究及模型建立
引用本文:吴龙国,王松磊,何建国,KAZUHIRO Nakano.基于高光谱成像技术的土壤水分机理研究及模型建立[J].发光学报,2017,38(10):1366-1376.
作者姓名:吴龙国  王松磊  何建国  KAZUHIRO Nakano
作者单位:1. 宁夏大学 土木水利工程学院, 宁夏 银川 750021; 2. 宁夏大学 农学院, 宁夏 银川 750021; 3. Graduate School of Science and Technology in Niigata University, Niigata 950-2181, Japan
基金项目:国家自然科学基金,2011年度宁夏回族自治区科技攻关计划,国家科技支撑计划(2012BAF07B06)资助项目Supported by National Natural Science Foundation of China,Science and Technology Research Plan of Ningxia Hui Autonomous Region,National Science and Technology Support Program
摘    要:为了研究宁夏地区土壤的水分迁移机理以及对土壤水分快速无损检测,利用高光谱成像(光谱范围900~1 700 nm)技术对土壤的含水率进行了研究。通过高光谱成像系统采集了208个土样,比较了不同天数下土壤含水率与光谱的变化、不同质量含水量光谱的差异。对采集到的土样进行PLSR模型建立,对比分析不同光谱预处理方法、不同方法提取特征波长(UVE、CARS、β系数、SPA)、不同建模方法(MLR、PCR、PLSR)建立的模型,优选出最佳模型。结果表明:在一定的土壤含水量范围内,光谱曲线的反射率与土壤含水率成反比;当增大到超过田间持水率时,光谱曲线的反射率与土壤含水率成正比。对比分析了不同预处理方法,优选出单位向量归一化预处理方法。对比不同的模型,优选出SPA提取的特征波长的MLR模型。最优的特征波长为987,1 386,1 466,1 568,1 636,1 645 nm,最优模型的预测相关系数Rp=0.984,预测均方根误差RMSEP为0.631。因此,今后可采用不同波段对土壤含水率进行定量分析。

关 键 词:高光谱成像  土壤  水分含量  无损检测
收稿时间:2017-06-12

Soil Moisture Mechanism and Establishment of Model Based on Hyperspectral Imaging Technique
WU Long-guo,WANG Song-lei,HE Jian-guo,KAZUHIRO Nakano.Soil Moisture Mechanism and Establishment of Model Based on Hyperspectral Imaging Technique[J].Chinese Journal of Luminescence,2017,38(10):1366-1376.
Authors:WU Long-guo  WANG Song-lei  HE Jian-guo  KAZUHIRO Nakano
Institution:1. Institute of Civil and Hydraulic Engineering, Ningxia University, Yinchuan 750021, China; 2. School of Agriculture, Ningxia University, Yinchuan 750021, China; 3. Graduate School of Science and Technology in Niigata University, Niigata 950-2181, Japan
Abstract:By using the near-infrared ( spectral range of 900 -1700 nm ) hyperspectral imaging technique, the soil moisture movement mechanism and non-destructive determination of the moisture content of soil in Ningxia Hui Autonomous Region were studied. A total of 208 soil samples were collected by hyperspectral imaging system. The differences among soil water content, spectral chan-ges, and spectra of different water contents were compared. The best model was chosen by different spectral pretreatment manners, different extraction manners of the characteristic wavelengths( UVE, CARS,β coefficient, SPA) , and different building model manners( MLR, PCR, PLSR) . The re-sults show that the changes of spectra are inversely proportional to the changes of soil water content within the moisture limits. When the moisture content of soil is beyond the field water holding capac-ity, the changes of spectra are directly proportional to the changes of soil water content. The unit vector normalized preprocessing method is optimized. The best model is MLR method based on the characteristic wavelength of SPA extraction. The optimal characteristic wavelengths are 987, 1386, 1466, 1568, 1636, 1645 nm, and the value of optimal correlation coefficient and RMSE are 0. 984 and 0. 631, respectively. Therefore, the soil moisture content can be quantitatively analyzed using different wavelengths.
Keywords:hyperspectral imaging  soil  moisture content  non-destruction
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