Title
Comparison of the Lunar Models Using the Hyper-Spectral Imager Observations in Lijiang, China.
Abstract
A lunar observation campaign was conducted using a hyper-spectral imaging spectrometer in Lijiang, China from December 2015 to February 2016. The lunar hyper-spectral images in the visible to near-infrared region (VNIR) have been obtained in different lunar phases with absolute scale established by the National Institute of Metrology (NIM), China using the lamp-plate calibration system. At the same time, the aerosol optical depth (AOD) is measured regularly by a lidar and a lunar CE318U for atmospheric characterization to provide nightly atmosphere extinction correction of lunar observations. This paper addressed the complicated data processing procedure in detail from raw images of the spectrometer into the spectral lunar irradiance in different lunar phases. The result of measurement shows that the imaging spectrometer can provide lunar irradiance with uncertainties less than 3.30% except for absorption bands. Except for strong atmosphere absorption region, the mean spectral irradiance difference between the measured irradiance and the ROLO (Robotic Lunar Observatory) model is 8.6 +/- 2% over the course of the lunar observation mission. The ROLO model performs more reliable to clarify absolute and relative accuracy of lunar irradiance than that of the MT2009 model in different Sun-Moon-Earth geometry. The spectral ratio analysis of lunar irradiance shows that band-to-band variability in the ROLO model is consistent within 2%, and the consistency of the models in the lunar phase and spectrum is well analyzed and evaluated from phase dependence and phase reddening analysis respectively.
Year
DOI
Venue
2020
10.3390/rs12111878
REMOTE SENSING
Keywords
DocType
Volume
radiometric calibration,lunar irradiance model,uncertainty
Journal
12
Issue
Citations 
PageRank 
11
0
0.34
References 
Authors
0
10
Name
Order
Citations
PageRank
Yang Wang100.34
Xiuqing Hu2348.87
Lin Chen300.68
Yu Huang400.34
Zhanfeng Li500.34
Shurong Wang600.34
Peng Zhang702.37
Ronghua Wu801.01
Lu Zhang900.68
Wei Wang1000.34