机构地区:[1]National Astronomical Observatories,Chinese Academy of Science [2]Graduate University of Chinese Academy of Sciences [3]School of Space Science and Physics,Shandong University [4]Shanghai Institute of Technical Physics,Chinese Academy of Science [5]Anhui Institute of Optics and Fine Mechanics,Chinese Academy of Science
出 处:《Chinese Journal Of Geochemistry》2014年第1期86-94,共9页中国地球化学学报
基 金:financially supported by the Chang’E program of China (NO.TY3Q20110029);Knowledge Innovation Program of the Chinese Academy of Sciences (Grant No.KGCX2-EW-402);National Natural Science Foundation of China (Nos.11003012 and U1231103)
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 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 hIn 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�
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