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消除水分因素影响的野外原状土壤盐分高光谱建模估测
引用本文:陈红艳,赵庚星,李玉环,李 华,盖岳峰. 消除水分因素影响的野外原状土壤盐分高光谱建模估测[J]. 农业工程学报, 2018, 34(12): 119-125
作者姓名:陈红艳  赵庚星  李玉环  李 华  盖岳峰
作者单位:土肥资源高效利用国家工程实验室/山东农业大学资源与环境学院;山东菏泽水利工程总公司;山东颐通土地房地产评估测绘有限公司
基金项目:国家自然科学基金项目(41401239,41671346);国家科技支撑计划(2015BAD23B02);山东农业大学"双一流"奖补资金资助(SYL2017XTTD02);山东省重点研发计划(2017CXGC0306)
摘    要:土壤水分被确定为土壤属性(有机碳、盐分等)光谱预测准确性下降的一个主要原因,该文通过两种方法的对比旨在探索去除土壤水分影响、提高盐分高光谱定量估测精度的方法和技术路线。首先以山东省东营市垦利区为研究区,采用地物光谱仪测定了96个样本的野外原状土和室内风干土光谱,并进行一阶导数变换;接着,对比分析盐分光谱特征及水分的影响;然后分别采用外部参数正交化(external parameter orthogonalization,EPO)和非负矩阵分解(non-negative matrix factorizing,NMF)方法校正和融合野外原状土光谱,去除土壤水分因素的影响,形成野外原状土光谱的校正和融合光谱;最后基于野外原状土光谱、校正和融合光谱,分别采用多元逐步线性回归(multiple step linear regression,MSLR)和偏最小二乘回归(partial least squares regression,PLSR)构建土壤盐分含量的估测模型,并进行验证和比较,分析预测精度变化。结果显示:土壤水分对野外原状土光谱及盐分光谱特征影响较大,需要研究去除;EPO和NMF均可提高土壤盐分野外原位光谱估测精度,比较而言,NMF效果更为显著;EPO结合PLSR或NMF结合MSLR可作为去除水分影响的土壤盐分校准模型的技术路线。

关 键 词:土壤盐分  土壤水分  光谱分析  外部参数正交化  非负矩阵分解
收稿时间:2018-03-25
修稿时间:2018-05-03

Modeling and estimation of field undisturbed soil salt based on hyperspectra under removal of moisture factor
Chen Hongyan,Zhao Gengxing,Li Yuhuan,Li Hua and Gai Yuefeng. Modeling and estimation of field undisturbed soil salt based on hyperspectra under removal of moisture factor[J]. Transactions of the Chinese Society of Agricultural Engineering, 2018, 34(12): 119-125
Authors:Chen Hongyan  Zhao Gengxing  Li Yuhuan  Li Hua  Gai Yuefeng
Affiliation:1. National Engineering Laboratory for Efficient Utilization of Soil and Fertilizer Resources, College of Resources and Environment, Shandong Agricultural University, Taian 271018, China;,1. National Engineering Laboratory for Efficient Utilization of Soil and Fertilizer Resources, College of Resources and Environment, Shandong Agricultural University, Taian 271018, China;,1. National Engineering Laboratory for Efficient Utilization of Soil and Fertilizer Resources, College of Resources and Environment, Shandong Agricultural University, Taian 271018, China;,2. Shandong Heze Hydraulic Engineering Corporation, Heze 274000, China; and 3. Shandong Yitong Real Estate Appraisal and Mapping Co., LTD, Jinan 250000, China
Abstract:Abstract: Soil moisture is one of the main reasons for the decline of predictive accuracy of soil attributes (organic carbon, salt, etc.) in using spectrum analysis method. By comparing the two methods of external parameter orthogonization (EPO) and non-negative matrix factorization (NMF), the purpose of this article is to explore a method and technology route of removing the effect of soil moisture (SM) and improving the estimation precision of soil salt content (SSC) based on hyperspectra. Firstly, we used Kenli district of Dongying city in Shandong province as the research area, and took 96 soil samples in the fields. The samples'' hyperspectra in situ and indoor after air-dry were measured respectively by spectra radiometer, and then transformed to the first deviation. The content of soil salinity and moisture were measured in laboratory. Then, the spectral characteristics of soil salt content and the effect of soil moisture on it were analyzed by comparison. Next, the external parameter orthogonization and non-negative matrix factorization were respectively used to correct and fuse the soil spectra in situ (Situ-spectra), and to remove the SM effect, and form the EPO correction spectra (EPO-spectra) and the NMF fusion spectra (NMF-spectra) of the Situ-spectra. Finally the estimation models of SSC were built respectively by the multiple step linear regression (MSLR) and the partial least squares regression (PLSR) based on the Situ-spectra, EPO-spectra and NMF-spectra, and were verified and compared to analyze the change of the SSC prediction precision. The results indicated that the soil salt content was high the soil salt content gradient was obvious, and the dispersion degree of soil salt content was high. However the soil moisture content was about 30 times of the soil salt content in the study area. The correlation between soil salinity and spectra is better at the band ranges of 1440-1660 nm, 1830-1860 nm, 1960-2110 nm. The soil moisture had great effect on the Situ-spectra and soil salt content spectral characteristics. Therefore, it is necessary to remove soil moisture impact. The EPO method can reduce the correlation between spectra and soil moisture in most spectral regions, and at the same time weaken the correlation between spectra and soil salinity in local bands. In comparison, the NMF method can effectively reduce the correlation between spectra and soil moisture, and increase the correlation between spectra and soil salinity. Both the EPO and NMF can improve the accuracy of the soil salt content estimation based on Situ-spectra. After adoption of EPO, the validation coefficient of determination (R2) increased between 0.08 and 0.09, and the relative prediction deviation (RPD) increased between 0.08 and 0.69%. At the same time, after adoption of NMF, the validation R2 increased between 0.27 and 0.38 and reached above 0.80, the RPD increased between 1.04 and 1.06, and reached above of 2.37. Thus the result of NMF was more significant than that of EPO for the removal of the SM effect. The method of EPO combined with PLSR or NMF combined with MSLR can be used as the technical route of removing the soil moisture effect and building soil salt content calibration model. The results can effectively promote the quantitative remote sensing extraction and real-time, in-situ monitoring of the saline soil information.
Keywords:soil salt   soil moisture   spetrum analysis   external parameter orthogonalization   non-negative matrix factorizing
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