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Correlation analysis and partial least square modeling to quantify typical minerals with Chang'E-3 visible and near-infrared imaging spectrometer's ground validation data
作者姓名:LIU Bin  LIU Jianzhong  ZHANG Guangliang  LING Zongcheng  ZHANG Jiang  HE Zhiping  YANG Benyong  ZOU Yongliao
作者单位:[1]National Astronomical Observatories', Chinese Academy ofSeienee, Beijing 100012, China [2]Graduate University of Chinese Academy of Sciences, Beijing 100049, China [3]School of Space Science and Physics, Shandong University, Weihai 264209, China [4]Shanghai Institute of Technical Physics, Chinese Academy of Science, Shanghai 200083, China [5]Anhui Institute of Optics and Fine Mechanics', Chinese Academy of Science, Anhui 230031, China
基金项目:Acknowledgements This study was financially supported by the Chang'E program of China (NO.TY3Q20110029), Knowledge Innovation Pro- gram of the Chinese Academy of Sciences (Grant No.KGCX2-EW-402) and National Natural Science Foundation of China (Nos. 11003012 and U 1231103).
摘    要:In 2013, Chang'E-3 program will develop lunar mineral resources in-situ detection. A Visible and Near-infrared Imaging Spectrometer (VNIS) has been selected as one payload of CE-3 lunar rover to achieve this goal. It is critical and urgent to evaluate VNIS' spectrum data quality and validate quantification methods for mineral composition before its launch. Ground validation experiment of VNIS was carried out to complete the two goals, by simulating CE-3 lunar rover's detection environment on lunar surface in the laboratory. Based on the hyperspectral reflectance data derived, Correlation Analysis and Partial Least Square (CA-PLS) algorithm is applied to predict abundance of four lunar typical minerals (pyroxene, plagioclase, ilmenite and olivine) in their mixture. We firstly selected a set of VNIS' spectral parameters which highly correlated with minerals' abundance by correlation analysis (CA), and then stepwise regression method was used to find out spectral parameters which make the largest contri- butions to the mineral contents. At last, functions were derived to link minerals' abundance and spectral parameters by partial least square (PLS) algorithm. Not considering the effect of maturity, agglutinate and Fe~, we found that there are wonderful correlations between these four minerals and VNIS' spectral parameters, e.g. the abundance of pyroxene correlates positively with the mixture's absorption depth, the value of absorption depth added as the in- creasing of pyroxene's abundance. But the abundance of plagioclase correlates negatively with the spectral parame- ters of band ratio, the value of band ratio would decrease when the abundance of plagioclase increased. Similar to plagioclase, the abundance of ilmenite and olivine has a negative correlation with the mixture's reflectance data, if the abundance of ilmenite or olivine increase, the reflectance values of the mixture will decrease. Through model validation, better estimates of pyroxene, plagioclase and ilmenite's abundances are given. It is concluded that VNIS has the capability to be applied on lunar minerals' identification, and CA-PLS algorithm has the potential to be used on lunar surface's in-situ detection for minerals' abundance prediction.

关 键 词:红外成像光谱仪  偏最小二乘  矿物成分  地面验证  相关分析  模型验证  可见光  高光谱反射率

Correlation analysis and partial least square modeling to quantify typical minerals with Chang’E-3 visible and near-infrared imaging spectrometer’s ground validation data
LIU Bin,LIU Jianzhong,ZHANG Guangliang,LING Zongcheng,ZHANG Jiang,HE Zhiping,YANG Benyong,ZOU Yongliao.Correlation analysis and partial least square modeling to quantify typical minerals with Chang’E-3 visible and near-infrared imaging spectrometer’s ground validation data[J].Chinese Journal of Geochemistry,2014,33(1):86-94.
Authors:Bin Liu  Jianzhong Liu  Guangliang Zhang  Zongcheng Ling  Jiang Zhang  Zhiping He  Benyong Yang  Yongliao Zou
Institution:1. National Astronomical Observatories, Chinese Academy of Science, Beijing, 100012, China
2. Graduate University of Chinese Academy of Sciences, Beijing, 100049, China
3. School of Space Science and Physics, Shandong University, Weihai, 264209, China
4. Shanghai Institute of Technical Physics, Chinese Academy of Science, Shanghai, 200083, China
5. Anhui Institute of Optics and Fine Mechanics, Chinese Academy of Science, Anhui, 230031, China
Abstract:In 2013, Chang’E-3 program will develop lunar mineral resources in-situ detection. A Visible and Near-infrared Imaging Spectrometer (VNIS) has been selected as one payload of CE-3 lunar rover to achieve this goal. It is critical and urgent to evaluate VNIS’ spectrum data quality and validate quantification methods for mineral composition before its launch. Ground validation experiment of VNIS was carried out to complete the two goals, by simulating CE-3 lunar rover’s detection environment on lunar surface in the laboratory. Based on the hyperspectral reflectance data derived, Correlation Analysis and Partial Least Square (CA-PLS) algorithm is applied to predict abundance of four lunar typical minerals (pyroxene, plagioclase, ilmenite and olivine) in their mixture. We firstly selected a set of VNIS’ spectral parameters which highly correlated with minerals’ abundance by correlation analysis (CA), and then stepwise regression method was used to find out spectral parameters which make the largest contributions to the mineral contents. At last, functions were derived to link minerals’ abundance and spectral parameters by partial least square (PLS) algorithm. Not considering the effect of maturity, agglutinate and Fe0, we found that there are wonderful correlations between these four minerals and VNIS’ spectral parameters, e.g. the abundance of pyroxene correlates positively with the mixture’s absorption depth, the value of absorption depth added as the increasing of pyroxene’s abundance. But the abundance of plagioclase correlates negatively with the spectral parameters of band ratio, the value of band ratio would decrease when the abundance of plagioclase increased. Similar to plagioclase, the abundance of ilmenite and olivine has a negative correlation with the mixture’s reflectance data, if the abundance of ilmenite or olivine increase, the reflectance values of the mixture will decrease. Through model validation, better estimates of pyroxene, plagioclase and ilmenite’s abundances are given. It is concluded that VNIS has the capability to be applied on lunar minerals’ identification, and CA-PLS algorithm has the potential to be used on lunar surface’s in-situ detection for minerals’ abundance prediction.
Keywords:Lunar surface  Chang'E-3  VNIS  partial least square (PLS)
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