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Article

Photometric Normalization of Chang’e-4 Visible and Near-Infrared Imaging Spectrometer Datasets: A Combined Study of In-Situ and Laboratory Spectral Measurements

1
Shandong Key Laboratory of Optical Astronomy and Solar-Terrestrial Environment, School of Space Science and Physics, Institute of Space Sciences, Shandong University, Weihai 264209, China
2
CAS Center for Excellence in Comparative Planetology, Chinese Academy of Sciences, Hefei 230026, China
3
Key Laboratory of Space Active Opto-Electronics Technology, Shanghai Institute of Technical Physics, Chinese Academy of Sciences, Shanghai 200083, China
4
Institute of Geochemistry, Chinese Academy of Sciences, Guiyang 550002, China
5
State Key Laboratory of Space Weather, National Space Science Center, Chinese Academy of Sciences, Beijing 100190, China
*
Author to whom correspondence should be addressed.
Remote Sens. 2020, 12(19), 3211; https://doi.org/10.3390/rs12193211
Received: 30 August 2020 / Revised: 23 September 2020 / Accepted: 29 September 2020 / Published: 1 October 2020
(This article belongs to the Special Issue Lunar Remote Sensing and Applications)
Until 29 May 2020, the Visible and Near-Infrared Imaging Spectrometer (VNIS) onboard the Yutu-2 Rover of the Chang’e-4 (CE-4) has acquired 96 high-resolution surface in-situ imaging spectra. These spectra were acquired under different illumination conditions, thus photometric normalization should be conducted to correct the introduced albedo differences before deriving the quantitative mineralogy for accurate geologic interpretations. In this study, a Lommel–Seeliger (LS) model and Hapke radiative transfer (Hapke) model were used and empirical phase functions of the LS model were derived. The values of these derived phase functions exhibit declining trends with the increase in phase angles and the opposition effect and phase reddening effect were observed. Then, we discovered from in-situ and laboratory measurements that the shadows caused by surface roughness have significant impacts on reflectance spectra and proper corrections were introduced. The validations of different phase functions showed that the maximum discrepancy at 1500 nm of spectra corrected by the LS model was less (~3.7%) than that by the Hapke model (~7.4%). This is the first time that empirical phase functions have been derived for a wavelength from 450 to 2395 nm using in-situ visible and near-infrared spectral datasets. Generally, photometrically normalized spectra exhibit smaller spectral slopes, lower FeO contents and larger optical maturity parameter (OMAT) than spectra without correction. In addition, the band centers of the 1 and 2 μm absorption features of spectra after photometric normalization exhibit a more concentrated distribution, indicating the compositional homogeneity of soils at the CE-4 landing site. View Full-Text
Keywords: Chang’e-4; visible and near-infrared imaging spectrometer; lunar soils; photometric correction; phase function; surface roughness Chang’e-4; visible and near-infrared imaging spectrometer; lunar soils; photometric correction; phase function; surface roughness
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MDPI and ACS Style

Qi, X.; Ling, Z.; Zhang, J.; Chen, J.; Cao, H.; Liu, C.; Qiao, L.; Fu, X.; He, Z.; Xu, R.; Liu, J.; Zou, Y. Photometric Normalization of Chang’e-4 Visible and Near-Infrared Imaging Spectrometer Datasets: A Combined Study of In-Situ and Laboratory Spectral Measurements. Remote Sens. 2020, 12, 3211. https://doi.org/10.3390/rs12193211

AMA Style

Qi X, Ling Z, Zhang J, Chen J, Cao H, Liu C, Qiao L, Fu X, He Z, Xu R, Liu J, Zou Y. Photometric Normalization of Chang’e-4 Visible and Near-Infrared Imaging Spectrometer Datasets: A Combined Study of In-Situ and Laboratory Spectral Measurements. Remote Sensing. 2020; 12(19):3211. https://doi.org/10.3390/rs12193211

Chicago/Turabian Style

Qi, Xiaobin, Zongcheng Ling, Jiang Zhang, Jian Chen, Haijun Cao, Changqing Liu, Le Qiao, Xiaohui Fu, Zhiping He, Rui Xu, Jianzhong Liu, and Yongliao Zou. 2020. "Photometric Normalization of Chang’e-4 Visible and Near-Infrared Imaging Spectrometer Datasets: A Combined Study of In-Situ and Laboratory Spectral Measurements" Remote Sensing 12, no. 19: 3211. https://doi.org/10.3390/rs12193211

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