scholarly journals Estimation of Noise in the In Situ Hyperspectral Data Acquired by Chang’E-4 and Its Effects on Spectral Analysis of Regolith

2020 ◽  
Vol 12 (10) ◽  
pp. 1603
Author(s):  
Honglei Lin ◽  
Yangting Lin ◽  
Yong Wei ◽  
Rui Xu ◽  
Yang Liu ◽  
...  
Keyword(s):  
Spectral Analysis ◽  
Lunar Surface ◽  
Near Infrared ◽  
Infrared Imaging ◽  
Hyperspectral Data ◽  
Repeated Measurements ◽  
Imaging Spectrometer ◽  
Low Snr ◽  
Spectral Interpretation ◽  
Geologic Interpretation

The Chang’E-4 (CE-4) spacecraft landed successfully on the far side of the Moon on 3 January 2019, and the rover Yutu-2 has explored the lunar surface since then. The visible and near-infrared imaging spectrometer (VNIS) onboard the rover has acquired numerous spectra, providing unprecedented insight into the composition of the lunar surface. However, the noise in these spectral data and its effects on spectral interpretation are not yet assessed. Here we analyzed repeated measurements over the same area at the lunar surface to estimate the signal–noise ratio (SNR) of the VNIS spectra. Using the results, we assessed the effects of noise on the estimation of band centers, band depths, FeO content, optical maturity (OMAT), mineral abundances, and submicroscopic metallic iron (SMFe). The data observed at solar altitudes <20° exhibit low SNR (25 dB), whereas the data acquired at 20°–35° exhibit higher SNR (35–37 dB). We found differences in band centers due to noise to be ~6.2 and up to 28.6 nm for 1 and 2 μm absorption, respectively. We also found that mineral abundances derived using the Hapke model are affected by noise, with maximum standard deviations of 6.3%, 2.4%, and 7.0% for plagioclase, pyroxene, and olivine, respectively. Our results suggest that noise has significant impacts on the CE-4 spectra, which should be considered in the spectral analysis and geologic interpretation of lunar exploration data.

scholarly journals Effect of Lunar Complex Illumination on In Situ Measurements Obtained Using Visible and Near-Infrared Imaging Spectrometer of Chang’E-4

2021 ◽  
Vol 13 (12) ◽  
pp. 2359
Author(s):  
Jiafei Xu ◽  
Meizhu Wang ◽  
Rong Wang ◽  
Qi Feng ◽  
Honglei Lin ◽  
...  
Keyword(s):  
Lunar Surface ◽  
Near Infrared ◽  
Infrared Imaging ◽  
Specular Reflection ◽  
In Situ Measurements ◽  
The Moon ◽  
Spectral Measurements ◽  
Near Infrared Imaging ◽  
Imaging Spectrometer

In-situ measurements of the spectral information on the lunar surface are of significance to study the geological evolution of the Moon. China’s Chang’E-4 (CE-4) Yutu-2 rover has conducted several in-situ spectral explorations on the Moon. The visible and near-infrared imaging spectrometer (VNIS) onboard the rover has acquired a series of in-situ spectra of the regolith at the landing site. In general, the mineralogical research of the lunar surface relies on the accuracy of the in-situ data. However, the spectral measurements of the Yutu-2 rover may be affected by shadows and stray illumination. In this study, we analyzed 106 CE-4 VNIS spectra acquired in the first 24 lunar days of the mission and noted that six of these spectra were affected by the shadows of the rover. Therefore, a method was established to correct the effects of the rover shadow on the spectral measurements. After shadow correction, the FeO content in the affected area is corrected to 14.46 wt.%, which was similar to the result calculated in the normal regolith. Furthermore, according to the visible images, certain areas of the explored sites were noted to be unusually bright. Considering the reflectance, geometric information, and shining patterns of the multi-layer insulation (MLI), we examined the influence of the specular reflection of the MLI on the bright spot regionsd , and found that the five sets of data were likely not affected by the specular reflection of the MLI. The results indicated that the complex illumination considerably influences the in situ spectral data. This study can provide a basis to analyze the VNIS scientific data and help enhance the accuracy of interpretation of the composition at CE-4 landing sites.

scholarly journals Applications of AOTF Spectrometers in In Situ Lunar Measurements

Materials ◽  
2021 ◽  
Vol 14 (13) ◽  
pp. 3454
Author(s):  
Jinning Li ◽  
Yuhua Gui ◽  
Rui Xu ◽  
Zehong Zhang ◽  
Wei Liu ◽  
...  
Keyword(s):  
Lunar Surface ◽  
Near Infrared ◽  
Infrared Imaging ◽  
In Situ Measurement ◽  
Low Light ◽  
Imaging Spectrometer ◽  
Electrical Modulation ◽  
Temperature Ranges ◽  
Temperature Adaptability

Spectrometers based on acousto-optic tunable filters (AOTFs) have several advantages, such as stable temperature adaptability, no moving parts, and wavelength selection through electrical modulation, compared with the traditional grating and Fourier transform spectrometers. Therefore, AOTF spectrometers can realize stable in situ measurement on the lunar surface under wide temperature ranges and low light environments. AOTF imaging spectrometers were first employed for in situ measurement of the lunar surface in the Chinese Chang’e project. The visible and near-infrared imaging spectrometer and the lunar mineralogical spectrometer have been successfully deployed on board the Chang’e-3/4 and Chang’e-5 missions. In this review, we investigate the performance indicators, structural design, selected AOTF performance parameters, data acquisition of the three lunar in situ spectral instruments used in the Chang’e missions. In addition, we also show the scientific achievement of lunar technology based on in situ spectral data.

scholarly journals Continuing the MODIS Dark Target Aerosol Time Series with VIIRS

2020 ◽  
Vol 12 (2) ◽  
pp. 308 ◽  
Author(s):  
Virginia Sawyer ◽  
Robert C. Levy ◽  
Shana Mattoo ◽  
Geoff Cureton ◽  
Yingxi Shi ◽  
...  
Keyword(s):  
Near Infrared ◽  
Infrared Imaging ◽  
Retrieval Algorithm ◽  
Spatial And Temporal Variability ◽  
Imaging Spectrometer ◽  
Standard Data ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Infrared Wavelengths ◽  
Good Agreement

For reflected sunlight observed from space at visible and near-infrared wavelengths, particles suspended in Earth’s atmosphere provide contrast with vegetation or dark water at the surface. This is the physical motivation for the Dark Target (DT) aerosol retrieval algorithm developed for the Moderate Resolution Imaging Spectrometer (MODIS). To extend the data record of aerosol optical depth (AOD) beyond the expected 20-year lifespan of the MODIS sensors, DT must be adapted for other sensors. A version of the DT AOD retrieval for the Visible Infrared Imaging Radiometer Suite (VIIRS) on the Suomi-National Polar-Orbiting Partnership (SNPP) is now mature enough to be released as a standard data product, and includes some upgraded features from the MODIS version. Differences between MODIS Aqua and VIIRS SNPP lead to some inevitable disagreement between their respective AOD measurements, but the offset between the VIIRS SNPP and MODIS Aqua records is smaller than the offset between those of MODIS Aqua and MODIS Terra. The VIIRS SNPP retrieval shows good agreement with ground-based measurements. For most purposes, DT for VIIRS SNPP is consistent enough and in close enough agreement with MODIS to continue the record of satellite AOD. The reasons for the offset from MODIS Aqua, and its spatial and temporal variability, are investigated in this study.

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

2020 ◽  
Vol 12 (19) ◽  
pp. 3211
Author(s):  
Xiaobin Qi ◽  
Zongcheng Ling ◽  
Jiang Zhang ◽  
Jian Chen ◽  
Haijun Cao ◽  
...  
Keyword(s):  
Near Infrared ◽  
Infrared Imaging ◽  
Landing Site ◽  
Near Infrared Imaging ◽  
Imaging Spectrometer ◽  
Quantitative Mineralogy ◽  
Infrared Spectral ◽  
Phase Functions ◽  
Phase Angles

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.

scholarly journals HYDRA2: A Multispectral Data Analysis Toolkit for Sensors on Suomi-NPP and Other Current Satellite Platforms

2016 ◽  
Vol 97 (7) ◽  
pp. 1283-1294
Author(s):  
Tom Rink ◽  
W. Paul Menzel ◽  
Liam Gumley ◽  
Kathy Strabala
Keyword(s):  
Cross Sections ◽  
Near Infrared ◽  
Infrared Imaging ◽  
Hyperspectral Data ◽  
Advanced Technology ◽  
Multispectral Data ◽  
Brightness Temperatures ◽  
Sensing Applications ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Multispectral Analysis

Abstract The Hyperspectral Data Viewer for Development of Research Applications, version 2 (HYDRA2), is a freeware-based multispectral analysis toolkit for satellite data that assists scientists in research and development, as well as education and training of remote sensing applications. HYDRA2 users can explore and visualize relationships between sensor measurements (brightness temperatures for infrared and reflectances for visible/near-infrared wavelengths) using spectral diagrams, cross sections, scatterplots, multiband combinations, and color enhancements on a pixel-by-pixel basis. HYDRA2 can be used with direct broadcast and archived data from sensors on board the National Oceanic and Atmospheric Administration (NOAA)/National Aeronautics and Space Administration (NASA) Suomi–National Polar-Orbiting Partnership (Suomi-NPP), NASA Aqua/Terra, European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) Meteorological Operational (MetOp), and Chinese Fengyun-3 platforms. This paper describes HYDRA2 and presents some examples using data retrievals from the Suomi-NPP Visible Infrared Imaging Radiometer Suite (VIIRS), Cross-Track Infrared Sounder (CrIS), Advanced Technology Microwave Sounder (ATMS), and Terra/Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) instruments.

scholarly journals CLASSIFICATION OF HYPERSPECTRAL DATA BASED ON GUIDED FILTERING AND RANDOM FOREST

2017 ◽  
Vol XLII-2/W7 ◽  
pp. 821-824
Author(s):  
H. Ma ◽  
W. Feng ◽  
X. Cao ◽  
L. Wang
Keyword(s):  
Random Forest ◽  
Infrared Imaging ◽  
Image Filtering ◽  
Hyperspectral Data ◽  
Spectral Information ◽  
Data Set ◽  
Imaging Spectrometer ◽  
Guided Image Filter ◽  
Spectral Bands ◽  
Guided Image Filtering

Hyperspectral images usually consist of more than one hundred spectral bands, which have potentials to provide rich spatial and spectral information. However, the application of hyperspectral data is still challengeable due to “the curse of dimensionality”. In this context, many techniques, which aim to make full use of both the spatial and spectral information, are investigated. In order to preserve the geometrical information, meanwhile, with less spectral bands, we propose a novel method, which combines principal components analysis (PCA), guided image filtering and the random forest classifier (RF). In detail, PCA is firstly employed to reduce the dimension of spectral bands. Secondly, the guided image filtering technique is introduced to smooth land object, meanwhile preserving the edge of objects. Finally, the features are fed into RF classifier. To illustrate the effectiveness of the method, we carry out experiments over the popular Indian Pines data set, which is collected by Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) sensor. By comparing the proposed method with the method of only using PCA or guided image filter, we find that effect of the proposed method is better.

Sign in / Sign up

Export Citation Format

Share Document