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糧食主產區(qū)耕地土壤重金屬高光譜綜合反演模型
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國土資源部公益性行業(yè)科研專項(201411022-2)


Hybrid Inversion Model of Heavy Metals with Hyperspectral Reflectance in Cultivated Soils of Main Grain Producing Areas
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    摘要:

    糧食主產區(qū)的耕地土壤重金屬污染已成為影響糧食安全和人居環(huán)境安全的突出問題。高光譜遙感技術為快速高效獲取土壤重金屬含量提供了新的途徑,也為土壤總金屬污染的監(jiān)測和防治提供了技術保障。以河南省糧食主產區(qū)新鄭市為研究對象,共采集191個耕地土壤樣品,利用Rank-KS法劃分為144個建模集樣本和47個驗證集樣本;在室內利用ASD FieldSpec 3型地物光譜儀獲取土壤高光譜數(shù)據(jù),對耕地土壤樣品在400~2400nm的光譜反射率與Cr、Cd、Zn、Cu、Pb 5種重金屬元素進行相關性分析,篩選出5種重金屬均通過P=0.01顯著性檢驗的共用高光譜特征波段作為反演模型的自變量;采用基于OLS的固定影響變系數(shù)面板數(shù)據(jù)模型,對新鄭市144個建模集樣本的5種土壤重金屬面板數(shù)據(jù)構建高光譜綜合反演模型。結果表明:面板數(shù)據(jù)模型整體顯著,擬合優(yōu)度較高(R2=0.9937,F(xiàn)統(tǒng)計量為1365.94)。模型精度檢驗Cu的相對分析誤差為2.046,Pb的相對分析誤差為3.432,都具有較好的預測精度;Cr、Cd、Zn的相對分析誤差在1.4~1.8之間,具有一般的定量預測能力。面板數(shù)據(jù)模型通過一次建模綜合反演多種土壤重金屬,計算簡便、速度快,可以用于新鄭市耕地土壤重金屬的高光譜快速監(jiān)測。

    Abstract:

    The heavy metals pollution in cultivated soils of main grain producing areas has become a prominent problem affecting the safety of food and living environment. The hyperspectral remote sensing technology as the frontier technology in the field of remote sensing technology, provides a new approach to access to soil heavy metal data quickly and accurately, and also provides the technical support for monitoring and predicting. Taking Xinzheng City of main grain producing areas in Henan Province as the research object, the 191 cultivated soil samples collected were divided into 144 calibration set and 47 validation set by Rank-KS method. The hyperspectral reflectance of soil samples was measured by using ASD FieldSpec 3 spectrometer in laboratory experiments. The correlation analyses between row spectral reflectance in 400~2400nm and the content of heavy metals Cr, Cd, Zn, Cu, Pb were done, and the correlation coefficient by F significance test (P=0.01) was selected which could be used to extract sensitive hyperspectral feature wavebands reflectance common to the above heavy metals as the independent variables of model. The hyperspectral inversion model was built by panel data model of fixed effect variable coefficient based on the ordinary least squares estimation method (OLS), which was about the panel data of heavy metals Cr, Cd, Zn, Cu, Pb of 144 samples in Xinzheng. The results show that the panel data model is overall significant, with high goodness of fit (R2=0.9937, F=1365.94). The result of precision test indicated that models for Cu and Pb performed well in modeling and predicting with a good ability of quantificational prediction, with relative percent deviation (RPD) values of 2.046 and 3.432 separately;Cr,Cd,Zn could perform generally in modeling and predicting with a good ability of quantificational prediction, with RPD values range of 1.4~1.8. The panel data model can be used to calculate various heavy metals at the same time and rapidly monitor soil heavy metals with hyperspectral reflectance in Xinzheng, with simple and fast calculation.

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張秋霞,張合兵,張會娟,王新生,劉文鍇.糧食主產區(qū)耕地土壤重金屬高光譜綜合反演模型[J].農業(yè)機械學報,2017,48(3):148-155. ZHANG Qiuxia, ZHANG Hebing, ZHANG Huijuan, WANG Xinsheng, LIU Wenkai. Hybrid Inversion Model of Heavy Metals with Hyperspectral Reflectance in Cultivated Soils of Main Grain Producing Areas[J]. Transactions of the Chinese Society for Agricultural Machinery,2017,48(3):148-155.

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  • 收稿日期:2016-12-11
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  • 在線發(fā)布日期: 2017-03-10
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