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. ...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.展开更多
1 Introduction Lunar mare basalts represent the products of partial remelting of deep mantle sources and provide windows into the compositions of lunar interior.Nine Apollo andLuna missions returned large amounts of m...1 Introduction Lunar mare basalts represent the products of partial remelting of deep mantle sources and provide windows into the compositions of lunar interior.Nine Apollo andLuna missions returned large amounts of mare basaltic samples,while remote sensing suggests that sampled basalts may cover only a small number of the lunar basalt展开更多
The imaging interferometer(IIM)aboard the Chang’E-1 lunar orbiter is the first multispectral imaging spectrometer for Chinese lunar missions.Before science applications(e.g.,FeO and TiO2mapping)of the IIM raw data,th...The imaging interferometer(IIM)aboard the Chang’E-1 lunar orbiter is the first multispectral imaging spectrometer for Chinese lunar missions.Before science applications(e.g.,FeO and TiO2mapping)of the IIM raw data,the radiance variation due to changes in illumination and viewing geometry has to be removed from the radiometrically calibrated IIM Level 2A images.To achieve this,we fit the IIM Level 2A radiance data with a Lommel-Seeliger photometric model consisting of an exponential term and a fourth order polynomial in the phase function,without distinguishing between lunar maria and highlands.The exponential and the fourth order polynomial parameters are derived separately by fitting to two datasets divided at a solar phase angle threshold,avoiding a decrease in the phase function close to zero phase angle.Different phase angle thresholds result in coincident fitting curves between 20°and 75°,while large discrepancies occur at other phase angles.Then the derived photometric model is used to normalize the IIM Level 2A data to radiance values at an incidence and phase angle of 30°and emission angle of 0°.Our photometric model is validated by comparing two photometrically normalized IIM radiance spectra covering the same areas,showing a relative deviation consistent with the IIM preflight calibration.展开更多
Information about the variability,and spatial distribution of iron abundance is important to understand lunar geological history and for future resource utilization. In this paper we present a preliminary model to pro...Information about the variability,and spatial distribution of iron abundance is important to understand lunar geological history and for future resource utilization. In this paper we present a preliminary model to produce an iron abundance map using images taken by an Imaging Interferometer on board the satellite Chang'E-1. Compared with the Clementine UVVIS images,the images from the Chang'E-1 satellite also allowed for the extraction of FeO abundance distributions on the Moon. However,the prelimi-nary model results suggest an underestimation of ～2 wt.% for the FeO content of the mare region and an overestimation of ～3 wt.% for the highland region.展开更多
The distribution of titanium abundance on the lunar surface is important knowledge for lunar geologic studies and future resource utilization.In this paper,we develop a preliminary model based on"ground truths&qu...The distribution of titanium abundance on the lunar surface is important knowledge for lunar geologic studies and future resource utilization.In this paper,we develop a preliminary model based on"ground truths"from Apollo and Luna sample-return sites to produce a titanium abundance map from Chang’E-1 Imaging Interferometer(IIM) images.The derived TiO2 abundances are validated with Clementine UVVIS results in several regions,including lunar highlands neighboring the Apollo 16 landing site,and high-Ti and low-Ti maria near the standard site of Mare Serenitatis(MS2) .The validation results show that TiO2 abundances modeled with Chang’E-1 IIM data are overestimated for highlands(～0.7 wt.%) and low-Ti maria(～1.5 wt.%) and underestimated for high-Ti maria(～0.8 wt.%).展开更多
Lunar absolute reflectance, which describes the fraction of solar radiation reflected by the Moon, is fundamental for the Chang'E-1 Imaging Interferometer(IIM) to map lunar mineralogical and elemental distribution...Lunar absolute reflectance, which describes the fraction of solar radiation reflected by the Moon, is fundamental for the Chang'E-1 Imaging Interferometer(IIM) to map lunar mineralogical and elemental distributions. Recent observations made by the Spectral Irradiance Monitor(SIM) onboard the Solar Radiation and Climate Experiment(SORCE) spacecraft indicate that temporal variation in the solar radiation might have non-negligible influence on reflectance calculation, and the SIM measurements are different from the two previously used solar irradiances, i.e., ATLAS3 and Newkur. To provide reliable science results, we examined solar irradiance variability with the SIM daily observations, derived lunar absolute reflectances from the IIM 2A radiance with the SIM, ATLAS3 and Newkur data, and compared them with the Chandrayaan-1 Moon Mineralogy Mapper(M3), the Robotic Lunar Observatory(ROLO) and the Kaguya Multispectral Imager(MI) results. The temporal variability of the SIM solar irradiance is 0.25%–1.1% in the IIM spectral range, and less than 0.2% during the IIM observations. Nevertheless, the differences between the SIM measurements and the ATLAS3 and Newkur data can respectively rise up to 8% and 5% at particular IIM bands, resulting in discrepancy between which might affect compositional mapping. The IIM absolute reflectance we derived for the Moon using the SIM data, except for the last two bands, is consistent with the ROLO and the MI observations, although it is lower.展开更多
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)
文摘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.
基金supported by the National Natural Science Foundation of China (41473065, 41373068)Natural Science Foundation of Shandong Province (JQ201511)Qilu Young Scholar (TANG SCHOLAR) Program of Shandong University,Weihai (2015WHWLJH14)
文摘1 Introduction Lunar mare basalts represent the products of partial remelting of deep mantle sources and provide windows into the compositions of lunar interior.Nine Apollo andLuna missions returned large amounts of mare basaltic samples,while remote sensing suggests that sampled basalts may cover only a small number of the lunar basalt
基金supported by the National Natural Science Foundation of China(11003012,41373068)the Natural Science Foundation of Shandong Province(ZR2011AQ001)+1 种基金Joint Funds of the National Natural Science Foundation of China and the Chinese Academy of Sciences(U1231103)Independent Innovation Foundation of Shandong University(2013ZRQP004)
文摘The imaging interferometer(IIM)aboard the Chang’E-1 lunar orbiter is the first multispectral imaging spectrometer for Chinese lunar missions.Before science applications(e.g.,FeO and TiO2mapping)of the IIM raw data,the radiance variation due to changes in illumination and viewing geometry has to be removed from the radiometrically calibrated IIM Level 2A images.To achieve this,we fit the IIM Level 2A radiance data with a Lommel-Seeliger photometric model consisting of an exponential term and a fourth order polynomial in the phase function,without distinguishing between lunar maria and highlands.The exponential and the fourth order polynomial parameters are derived separately by fitting to two datasets divided at a solar phase angle threshold,avoiding a decrease in the phase function close to zero phase angle.Different phase angle thresholds result in coincident fitting curves between 20°and 75°,while large discrepancies occur at other phase angles.Then the derived photometric model is used to normalize the IIM Level 2A data to radiance values at an incidence and phase angle of 30°and emission angle of 0°.Our photometric model is validated by comparing two photometrically normalized IIM radiance spectra covering the same areas,showing a relative deviation consistent with the IIM preflight calibration.
基金supported by the National High-Tech Research and Development Program of China (2008AA12A212/211/213)China Postdoctoral Science Foundation (20090450580)+1 种基金the National Natural Science Foundation of China (11003012)the Young Researcher Grant of the National Astronomical Observatories,Chinese Academy of Sciences
文摘Information about the variability,and spatial distribution of iron abundance is important to understand lunar geological history and for future resource utilization. In this paper we present a preliminary model to produce an iron abundance map using images taken by an Imaging Interferometer on board the satellite Chang'E-1. Compared with the Clementine UVVIS images,the images from the Chang'E-1 satellite also allowed for the extraction of FeO abundance distributions on the Moon. However,the prelimi-nary model results suggest an underestimation of ～2 wt.% for the FeO content of the mare region and an overestimation of ～3 wt.% for the highland region.
基金supported by the National High-Tech Research and Development Program of China(2008AA12A212/211/213,2009AA122201, 2010AA122203)China Postdoctoral Science Foundation(20090450580)National Natural Science Foundation of China(11003012)
文摘The distribution of titanium abundance on the lunar surface is important knowledge for lunar geologic studies and future resource utilization.In this paper,we develop a preliminary model based on"ground truths"from Apollo and Luna sample-return sites to produce a titanium abundance map from Chang’E-1 Imaging Interferometer(IIM) images.The derived TiO2 abundances are validated with Clementine UVVIS results in several regions,including lunar highlands neighboring the Apollo 16 landing site,and high-Ti and low-Ti maria near the standard site of Mare Serenitatis(MS2) .The validation results show that TiO2 abundances modeled with Chang’E-1 IIM data are overestimated for highlands(～0.7 wt.%) and low-Ti maria(～1.5 wt.%) and underestimated for high-Ti maria(～0.8 wt.%).
基金supported by the National Natural Science Foundation of China(Grant Nos.11003012,41373068,41473065 and U1231103)
文摘Lunar absolute reflectance, which describes the fraction of solar radiation reflected by the Moon, is fundamental for the Chang'E-1 Imaging Interferometer(IIM) to map lunar mineralogical and elemental distributions. Recent observations made by the Spectral Irradiance Monitor(SIM) onboard the Solar Radiation and Climate Experiment(SORCE) spacecraft indicate that temporal variation in the solar radiation might have non-negligible influence on reflectance calculation, and the SIM measurements are different from the two previously used solar irradiances, i.e., ATLAS3 and Newkur. To provide reliable science results, we examined solar irradiance variability with the SIM daily observations, derived lunar absolute reflectances from the IIM 2A radiance with the SIM, ATLAS3 and Newkur data, and compared them with the Chandrayaan-1 Moon Mineralogy Mapper(M3), the Robotic Lunar Observatory(ROLO) and the Kaguya Multispectral Imager(MI) results. The temporal variability of the SIM solar irradiance is 0.25%–1.1% in the IIM spectral range, and less than 0.2% during the IIM observations. Nevertheless, the differences between the SIM measurements and the ATLAS3 and Newkur data can respectively rise up to 8% and 5% at particular IIM bands, resulting in discrepancy between which might affect compositional mapping. The IIM absolute reflectance we derived for the Moon using the SIM data, except for the last two bands, is consistent with the ROLO and the MI observations, although it is lower.
