基于野外实测光谱的玄武岩地球化学成分反演
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摘要
岩石地球化学成分对岩石分类、成因及演化研究有重要地质意义。利用遥感手段反演岩石地球化学成分是一个较新的课题,也是遥感相关应用研究的难点。以甘肃省柳园镇南部二叠纪玄武岩带为研究目标,在进行系统采样、光谱分析、地球化学测试的基础上,采用偏最小二乘回归(partial least squares regression,PLSR)对拥有2 150个波段的实测波谱数据及相应的6种主量矿物数据进行反演建模。首先选择有效的预处理方法对目标数据集进行优化,再利用k折交叉检验方法获得最小均方根误差下的最适主成分个数。运算结果表明,PLSR模型具有较好的稳定性和精度,在利用遥感数据进行岩石地球化学成分反演方面有很好的应用前景。
Geochemical compositions have significant implications for rock classification,identification of the petrogenesis and evolution of the rocks. The utilization of remote sensing method to estimate the geochemical compositions of the rocks is a new subject,and is also a difficult point in remote sensing related researches due to its relatively immature applications. In this study,he Permian basalts were chosen as the study object. Based on systematical sampling,spectral analysis and geochemical test,the authors constructed a mathematical model between field measured spectra data( 2 150 bands) and available data of six representative major elements by using partial least squares regression( PLSR). It is essential to initially choose proper preprocessing method to optimize the spectra data,and then search for the optimal number of principal components with minimum root- mean-square error through k- fold cross- validation. The results show that the PLSR model yields higher stability and precision,and plays a significant role in applications of geochemical composition inversion using remote sensing data.
Geochemical compositions have significant implications for rock classification,identification of the petrogenesis and evolution of the rocks. The utilization of remote sensing method to estimate the geochemical compositions of the rocks is a new subject,and is also a difficult point in remote sensing related researches due to its relatively immature applications. In this study,he Permian basalts were chosen as the study object. Based on systematical sampling,spectral analysis and geochemical test,the authors constructed a mathematical model between field measured spectra data( 2 150 bands) and available data of six representative major elements by using partial least squares regression( PLSR). It is essential to initially choose proper preprocessing method to optimize the spectra data,and then search for the optimal number of principal components with minimum root- mean-square error through k- fold cross- validation. The results show that the PLSR model yields higher stability and precision,and plays a significant role in applications of geochemical composition inversion using remote sensing data.
引文
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[16]褚小立,袁洪福,陆婉珍.近红外分析中光谱预处理及波长选择方法进展与应用[J].化学进展,2004,16(4):528-542.Chu X L,Yuan H F,Lu W Z.Progress and application of spectral data pretreatment and wavelength selection methods in NIR analytical technique[J].Progress in Chemistry,2004,16(4):528-542.
[17]黎文兵,药林桃,刘木华,等.光谱预处理对LIBS检测脐橙中Cu的偏最小二乘定量模型影响[J].光谱学与光谱分析,2015,35(5):1392-1397.Li W B,Yao L T,Liu M H,et al.Influence of spectral pre-processing on PLS quantitative model of detecting Cu in navel orange by LIBS[J].Spectroscopy and Spectral Analysis,2015,35(5):1392-1397.
[2]Song L,Jian J,Tan D J,et al.Estimate of heavy metals in soil and streams using combined geochemistry and field spectroscopy in Wan-sheng mining area,Chongqing,China[J].International Journal of Applied Earth Observation and Geoinformation,2015,34:1-9.
[3]Lucey P G,Blewett D T,Jolliff B L.Lunar iron and titanium abundance algorithms based on final processing of Clementine ultraviolet-visible images[J].Journal of Geophysical Research,2000,105(E8):20297-20305.
[4]Le Mouélic S,Lucey P G,Langevin Y,et al.Calculating iron contents of lunar highland materials surrounding Tycho crater from integrated Clementine UV-visible and near-infrared data[J].Journal of Geophysical Research,2002,107(E10):5074.
[5]Greenhagen B T,Lucey P G,Wyatt M B,et al.Global silicate mineralogy of the Moon from the Diviner lunar radiometer[J].Science,2010,329(5998):1507-1509.
[6]Yan B K,Xiong S Q,Wu Y Z,et al.Mapping lunar global chemical composition from Chang’E-1 IIM data[J].Planetary and Space Science,2012,67(1):119-129.
[7]闫柏琨,刘圣伟,王润生,等.热红外遥感定量反演地表岩石的Si O2含量[J].地质通报,2006,25(5):639-643.Yan B K,Liu S W,Wang R S,et al.Quantitative inversion of the Si O2content in surface rocks using thermal infrared remote sensing[J].Geological Bulletin of China,2006,25(5):639-643.
[8]王俊虎,张杰林,张静波.基于ASTER热红外数据的Si O2含量反演在某矿田信息提取中的应用[J].铀矿地质,2010,26(5):306-312.Wang J H,Zhang J L,Zhang J B.Si O2content retrieving based on ASTER thermal data and its application in substracting metallogenic factor of a uranium deposit[J].Uranium Geology,2010,26(5):306-312.
[9]杨杭,张立福,黄照强,等.基于热红外发射光谱的岩石Si O2定量反演模型研究[J].光谱学与光谱分析,2012,32(6):1611-1615.Yang H,Zhang L F,Huang Z Q,et al.Quantitative inversion of rock Si O2content based on thermal infrared emissivity spectrum[J].Spectroscopy and Spectral Analysis,2012,32(6):1611-1615.
[10]莫宣学.岩浆与岩浆岩:地球深部"探针"与演化记录[J].自然杂志,2011,33(5):255-259.Mo X X.Magma and magmatic/igneous rocks:A lithoprobe into the deep earth and records of the Earth’s evolution[J].Chinese Journal of Nature,2011,33(5):255-259.
[11]莫宣学,赵志丹,邓晋福,等.印度-亚洲大陆主碰撞过程的火山作用响应[J].地学前缘,2003,10(3):135-148.Mo X X,Zhao Z D,Deng J F,et al.Response of volcanism to the India-Asia collision[J].Earth Science Frontiers,2003,10(3):135-148.
[12]赵泽辉,郭召杰,韩宝福,等.新疆东部―甘肃北山地区二叠纪玄武岩对比研究及其构造意义[J].岩石学报,2006,22(5):1279-1293.Zhao Z H,Guo Z J,Han B F,et al.Comparative study on Permian basalts from eastern Xinjiang-Beishan area of Gansu Province and its tectonic implications[J].Acta Petrologica Sinica,2006,22(5):1279-1293.
[13]Wold S,Albano C,Dunn III W J,et al.Pattern recognition:Finding and using regularities in multivariate data[C]//Proceedings of Food Research and Data Analysis.London,UK:Applied Science Pub,1983:146-189.
[14]陈洁梅,肖青青,潘涛,等.NIR光谱结合稳定等效MW-PLS方法用于高脂血症指标分析[J].光谱学与光谱分析,2014,34(10):2827-2832.Chen J M,Xiao Q Q,Pan T,et al.NIR spectroscopy combined with stability and equivalence MW-PLS method applied to analysis of hyperlipidemia indexes[J].Spectroscopy and Spectral Analysis,2014,34(10):2827-2832.
[15]李耀翔,汪洪涛,耿志伟,等.基于NIR及PLS-PCR-SVR预测森林土壤有机碳含量[J].安徽农业科学,2014,42(15):4702-4706,4742.Li Y X,Wang H T,Geng Z W,et al.Prediction of forest soil carbon content based on the near infrared spectroscopy and PLS-PCRSVR[J].Journal of Anhui Agricultural Sciences,2014,42(15):4702-4706,4742.
[16]褚小立,袁洪福,陆婉珍.近红外分析中光谱预处理及波长选择方法进展与应用[J].化学进展,2004,16(4):528-542.Chu X L,Yuan H F,Lu W Z.Progress and application of spectral data pretreatment and wavelength selection methods in NIR analytical technique[J].Progress in Chemistry,2004,16(4):528-542.
[17]黎文兵,药林桃,刘木华,等.光谱预处理对LIBS检测脐橙中Cu的偏最小二乘定量模型影响[J].光谱学与光谱分析,2015,35(5):1392-1397.Li W B,Yao L T,Liu M H,et al.Influence of spectral pre-processing on PLS quantitative model of detecting Cu in navel orange by LIBS[J].Spectroscopy and Spectral Analysis,2015,35(5):1392-1397.