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Advances in Exploring the Moon, Mars, and Asteroids Using Spacecraft Remote Sensing and Other Toolkits

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Satellite Missions for Earth and Planetary Exploration".

Deadline for manuscript submissions: closed (31 May 2023) | Viewed by 30514

Special Issue Editors

Prof. Dr. Shengbo Chen

E-Mail Website
Guest Editor
College of Geo-Exploration Science and Technology, Jilin University, Changchun 130026, China
Interests: remote sensing; planetary geology; lunar and Martian geology; geological remote sensing
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Lin Li

E-Mail Website
Guest Editor
Department of Earth Sciences, Indiana University-Purdue University Indianapolis, Indianapolis, IN 46202, USA
Interests: remote sensing; lunar and planetary geology; environmental sciences; data processing; radiative transfer models
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Yuanzhi Zhang

E-Mail Website
Guest Editor
Key Lab of Lunar Science and Deep-Exploration, Chinese Academy of Sciences, Beijing 100101, China
Interests: remote sensing; lunar and planetary science; Mars and Venus geology; environmental remote sensing; image processing
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Remote sensing plays critical roles in exploring different planetary bodies including the Moon, Mars, and asteroids. Remotely sensed optical images consist primarily of multi- and hyper-spectral datasets in the visible-near-infrared (VNIR) and shortwave infrared (SWIR) regions that are sensitive to the mineralogical composition on the Moon, Mars, Mercury, and asteroids because of spectrally diagnostic absorption features of major minerals (e.g., olivine, clinopyroxene, orthopyroxene, ilmenite, and plagioclase), different glasses, or molecular waters on the Moon, Mars, or some asteroids. On the other hand, thermal infrared (TIR) and passive microwave data are definitely necessary for mapping substrate physical properties (i.e., temperature, regolith’s size, and thickness and layering) and chemical compositions, which are critical for understanding surface and subsurface geology of airless or atmosphere-enveloped planetary bodies. Moreover, geophysical methods including digital terrain models, gravity and magnetic anomalies, seismic waves, and heat flux are available for characterizing the interiors of planets and small bodies hidden from remote sensing.

This Special Issue invites manuscripts focusing on analysing returning samples, spacecraft remote sensing, and geophysical data acquired by the latest missions to the Moon, Mars or asteroids and highlighting their importance for investigation of the Moon, Mars, asteroids and related planetary bodies. The Special Issue also welcomes to manuscripts reporting research results from integration of various observations by photography, nuclear remote sensing, and geophysical exploration, which advance our current knowledge of comparative planetology and expand remote sensing application. The topics will include, but are not limited to, the following:

  • Spacecraft remote sensing by Chang’E-series missions or its integration with analysing returned samples for mapping lunar regolith, mineralogy, and lithology;
  • Spacecraft remote sensing by Chang’E-series missions or its integration with geophysical methods for mapping lunar geological units, tectonic features, volcanism, and interior;
  • Recent investigations (rover measurements, returning samples, remote sensing, and geophysics) from other missions on lunar regolith, rock units, tectonic features, volcanism, and interior;
  • Studies on identification/investigation of potentially geological active features on the Moon using data acquired by Chang’E-series and other lunar missions;
  • Recent investigations from Mars missions on Martian regolith and rock types, geological units, tectonic features, volcanism, and interior;
  • Spacecraft remote sensing by near future asteroid missions or its integration with geophysical methods for investigation of asteroid regolith and rock types, geological units, tectonic features, volcanism, and interior;
  • Remotely optical spectroscopy and image data analysis;
  • Remotely thermal sensing of physical and compositional properties;
  • Microwave remote sensing of surface and subsurface properties;
  • Radiative transfer models for sensing various planetary bodies and comparative planetology;
  • Methods for integrative analysis of geological, remote sensing and geophysical datasets.

Prof. Dr. Shengbo Chen
Prof. Dr. Lin Li
Prof. Dr. Yuanzhi Zhang
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Chang’E-series missions
  • recent lunar missions
  • lunar geophysics and geochemistry
  • recent Mars missions
  • near future asteroid missions
  • regolith, rocks, and geological units
  • surface geomorphology and tectonic structures
  • volcanism, interior, and thermal history

Related Special Issue

Published Papers (19 papers)

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14 pages, 842 KiB  
Communication
Probing Dust and Water in Martian Atmosphere with Far-Infrared Frequency Spacecraft Occultation
by Ananyo Bhattacharya, Cheng Li, Nilton O. Renno, Sushil K. Atreya and David Sweeney
Remote Sens. 2023, 15(18), 4574; https://doi.org/10.3390/rs15184574 - 17 Sep 2023
Viewed by 1041
Abstract
Airborne dust plays an active role in determining the thermal structure and chemical composition of the present-day atmosphere of Mars and possibly the planet’s climate evolution over time through radiative–convective and cloud microphysics processes. Thus, accurate measurements of the distribution and variability of [...] Read more.
Airborne dust plays an active role in determining the thermal structure and chemical composition of the present-day atmosphere of Mars and possibly the planet’s climate evolution over time through radiative–convective and cloud microphysics processes. Thus, accurate measurements of the distribution and variability of dust are required. Observations from the Mars Global Surveyor/Thermal Emission Spectrometer Mars Mars Reconnaissance Orbiter/Mars Climate Sounder and Mars Express/Fourier Transform Spectrometer and the Curiosity Rover have limited capability to measure dust. We show that spacecraft occultation of the Martian atmosphere at far-infrared frequencies between 1 and 10 THz can provide the needed global and temporal data on atmospheric dust by providing co-located measurements of temperature and dust opacity from the top of the atmosphere all the way down to the surface. In addition, spacecraft occultation by a small-satellite constellation could provide global measurements of the development of dust storms. Full article
(This article belongs to the Special Issue Advances in Exploring the Moon, Mars, and Asteroids Using Spacecraft Remote Sensing and Other Toolkits)
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23 pages, 6489 KiB  
Article
Mars Rover Penetrating Radar Modeling and Interpretation Considering Linear Frequency Modulation Source and Tilted Antenna
by Shichao Zhong, Yibo Wang, Yikang Zheng and Ling Chen
Remote Sens. 2023, 15(13), 3423; https://doi.org/10.3390/rs15133423 - 06 Jul 2023
Cited by 1 | Viewed by 1052
Abstract
Ground-penetrating radar (GPR) has been extensively utilized in deep-space exploration. However, GPR modeling commonly employs simplified antenna models and carrier-free impulse signals, resulting in reduced accuracy and interpretability. In this paper, we addressed these limitations by combining a tilted monopole antenna and linear [...] Read more.
Ground-penetrating radar (GPR) has been extensively utilized in deep-space exploration. However, GPR modeling commonly employs simplified antenna models and carrier-free impulse signals, resulting in reduced accuracy and interpretability. In this paper, we addressed these limitations by combining a tilted monopole antenna and linear frequency modulation continuous wave (LFMCW) to simulate real conditions. Additionally, a radiation-pattern-compensation back-propagation (RPC-BP) algorithm was developed to improve the illumination of the right-inclined structure. We first introduced the LFMCW used by the Mars Rover Penetrating Radar (RoPeR) onboard the Zhurong rover, where frequencies range from 15 to 95 MHz. Although the LFMCW signal improves radiation efficiency, it increases data processing complexity. Then, the radiation patterns and response of the tilted monopole antenna were analyzed, where the radiated signal amplitude varies with frequency. Finally, a series of numerical and laboratory experiments were conducted to interpret the real RoPeR data. The results indicate that hyperbolic echoes tilt in the opposite direction of the survey direction. This study demonstrates that forward modeling considering real transmit signals and complex antenna models can improve modeling accuracy and prevent misleading interpretations on deep-space exploration missions. Moreover, the migration process can improve imaging quality by considering radiation pattern compensation. Full article
(This article belongs to the Special Issue Advances in Exploring the Moon, Mars, and Asteroids Using Spacecraft Remote Sensing and Other Toolkits)
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25 pages, 3389 KiB  
Article
When Convolutional Neural Networks Meet Laser-Induced Breakdown Spectroscopy: End-to-End Quantitative Analysis Modeling of ChemCam Spectral Data for Major Elements Based on Ensemble Convolutional Neural Networks
by Yan Yu and Meibao Yao
Remote Sens. 2023, 15(13), 3422; https://doi.org/10.3390/rs15133422 - 06 Jul 2023
Cited by 7 | Viewed by 1656
Abstract
Modeling the quantitative relationship between target components and measured spectral information is an essential part of laser-induced breakdown spectroscopy (LIBS) analysis. However, many traditional multivariate analysis algorithms must reduce the spectral dimension or extract the characteristic spectral lines in advance, which may result [...] Read more.
Modeling the quantitative relationship between target components and measured spectral information is an essential part of laser-induced breakdown spectroscopy (LIBS) analysis. However, many traditional multivariate analysis algorithms must reduce the spectral dimension or extract the characteristic spectral lines in advance, which may result in information loss and reduced accuracy. Indeed, improving the precision and interpretability of LIBS quantitative analysis is a critical challenge in Mars exploration. To solve this problem, this paper proposes an end-to-end lightweight quantitative modeling framework based on ensemble convolutional neural networks (ECNNs). This method eliminates the need for dimensionality reduction of the raw spectrum along with other pre-processing operations. We used the ChemCam calibration dataset as an example to verify the effectiveness of the proposed approach. Compared with partial least squares regression (a linear method) and extreme learning machine (a nonlinear method), our proposed method resulted in a lower root-mean-square error for major element prediction (54% and 73% lower, respectively) and was more stable. We also delved into the internal learning mechanism of the deep CNN model to understand how it hierarchically extracts spectral information features. The experimental results demonstrate that the easy-to-use ECNN-based regression model achieves excellent prediction performance while maintaining interpretability. Full article
(This article belongs to the Special Issue Advances in Exploring the Moon, Mars, and Asteroids Using Spacecraft Remote Sensing and Other Toolkits)
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27 pages, 13888 KiB  
Article
A New Blind Selection Approach for Lunar Landing Zones Based on Engineering Constraints Using Sliding Window
by Hengxi Liu, Yongzhi Wang, Shibo Wen, Jianzhong Liu, Jiaxiang Wang, Yaqin Cao, Zhiguo Meng and Yuanzhi Zhang
Remote Sens. 2023, 15(12), 3184; https://doi.org/10.3390/rs15123184 - 19 Jun 2023
Viewed by 1227
Abstract
Deep space exploration has risen in interest among scientists in recent years, with soft landings being one of the most straightforward ways to acquire knowledge about the Moon. In general, landing mission success depends on the selection of landing zones, and there are [...] Read more.
Deep space exploration has risen in interest among scientists in recent years, with soft landings being one of the most straightforward ways to acquire knowledge about the Moon. In general, landing mission success depends on the selection of landing zones, and there are currently few effective quantitative models that can be used to select suitable landing zones. When automatic landing zones are selected, the grid method used for data partitioning tends to miss potentially suitable landing sites between grids. Therefore, this study proposes a new engineering-constrained approach for landing zone selection using LRO LOLA-based slope data as original data based on the sliding window method, which solves the spatial omission problem of the grid method. Using the threshold ratio, mean, coefficient of variation, Moran’s I, and overall rating, this method quantifies the suitability of each sliding window. The k-means clustering algorithm is adopted to determine the suitability threshold for the overall rating. The results show that 20 of 22 lunar soft landing sites are suitable for landing. Additionally, 43 of 50 landing sites preselected by the experts (suitable landing sites considering a combination of conditions) are suitable for landing, accounting for 90.9% and 86% of the total number, respectively, for a window size of 0.5° × 0.5°. Among them, there are four soft landing sites: Surveyor 3, 6, 7, and Apollo 15, which are not suitable for landing in the evaluation results of the grid method. However, they are suitable for landing in the overall evaluation results of the sliding window method, which significantly reduces the spatial omission problem of the grid method. In addition, four candidate landing regions, including Aristarchus Crater, Marius Hills, Moscoviense Basin, and Orientale Basin, were evaluated for landing suitability using the sliding window method. The suitability of the landing area within the candidate range of small window sizes was 0.90, 0.97, 0.49, and 0.55. This indicates the capacity of the method to analyze an arbitrary range during blind landing zone selection. The results can quantify the slope suitability of the landing zones from an engineering perspective and provide different landing window options. The proposed method for selecting lunar landing zones is clearly superior to the gridding method. It enhances data processing for automatic lunar landing zone selection and progresses the selection process from qualitative to quantitative. Full article
(This article belongs to the Special Issue Advances in Exploring the Moon, Mars, and Asteroids Using Spacecraft Remote Sensing and Other Toolkits)
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22 pages, 8158 KiB  
Article
Extracting Mare-like Cryptomare Deposits in Cryptomare Regions Based on CE-2 MRM Data Using SVM Method
by Tianqi Tang, Zhiguo Meng, Yi Lian, Zhaoran Wei, Xuegang Dong, Yongzhi Wang, Mingchang Wang, Zhanchuan Cai, Xiaoping Zhang, Alexander Gusev and Yuanzhi Zhang
Remote Sens. 2023, 15(8), 2010; https://doi.org/10.3390/rs15082010 - 11 Apr 2023
Cited by 1 | Viewed by 1300
Abstract
A new kind of surface material is found and defined in the Balmer–Kapteyn (B-K) cryptomare region, Mare-like cryptomare deposits (MCD), representing highland debris mixed by mare deposits with a certain fraction. This postulates the presence of surface materials in the cryptomare regions. In [...] Read more.
A new kind of surface material is found and defined in the Balmer–Kapteyn (B-K) cryptomare region, Mare-like cryptomare deposits (MCD), representing highland debris mixed by mare deposits with a certain fraction. This postulates the presence of surface materials in the cryptomare regions. In this study, to objectively verify the existence of the MCD in the cryptomare regions, based on the Chang’E-2 microwave radiometer (MRM) data, the support vector machine (SVM) method was adopted, where the K-means algorithm was used to optimize the training samples and the random forest algorithm was used to select the proper band features. Finally, the extracted MCD is identified with the datasets including Lunar Reconnaissance Orbiter Wide Angle Camera, Diviner, and Clementine UV–VIS. The main findings are as follows: (1) Compared to the range outlined via the TB counter, the range of the MCD is objectively extracted using the SVM method in the B-K cryptomare region, which is reasonably indicated by the FeO abundance, TiO2 abundance, and rock abundance distributions. (2) The MCDs were extracted in the Dewar, Lomonosov–Fleming (L-F), and Schiller–Schickard (S-S) regions, indicating that the MCDs are widely distributed in the cryptomaria. (3) The presence of MCDs is concentrated in a limited region, accounting for 64.9%, 52.3%, 76.4%, and 64%, respectively, in the range of Dewar, L-F, S-S, and B-K regions identified using the optical data. The occurrence of the MCD gives a new understanding of the surface evolution in the cryptomare regions. Full article
(This article belongs to the Special Issue Advances in Exploring the Moon, Mars, and Asteroids Using Spacecraft Remote Sensing and Other Toolkits)
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27 pages, 8333 KiB  
Article
A Unified Brightness Temperature Features Analysis Framework for Mapping Mare Basalt Units Using Chang’e-2 Lunar Microwave Sounder (CELMS) Data
by Yu Li, Zifeng Yuan, Zhiguo Meng, Jinsong Ping and Yuanzhi Zhang
Remote Sens. 2023, 15(7), 1910; https://doi.org/10.3390/rs15071910 - 02 Apr 2023
Cited by 2 | Viewed by 1716
Abstract
The brightness temperature (TB) features extracted from Chang’e-2 Lunar Microwave Sounder (CELMS) data represent the passive microwave thermal emission (MTE) from the lunar regolith at different depths. However, there have been few studies assessing the importance and contribution of each T [...] Read more.
The brightness temperature (TB) features extracted from Chang’e-2 Lunar Microwave Sounder (CELMS) data represent the passive microwave thermal emission (MTE) from the lunar regolith at different depths. However, there have been few studies assessing the importance and contribution of each TB feature for mapping mare basalt units. In this study, a unified framework of TB features analysis is proposed through a case study of Mare Fecunditatis, which is a large basalt basin on the eastern nearside of the Moon. Firstly, TB maps are generated from original CELMS data. Next, all TB features are evaluated systematically using a range of analytical approaches. The Pearson coefficient is used to compute the correlation of features and basalt classes. Two distance metrics, normalized distance and J-S divergence, are selected to measure the discrimination of basalt units by each TB feature. Their contributions to basalt classification are quantitatively evaluated by the ReliefF method and out-of-bag (OOB) importance index. Then, principal component analysis (PCA) is applied to reduce the dimension of TB features and analyze the feature space. Finally, a new geological map of Mare Fecunditatis is generated using CELMS data based on a random forest (RF) classifier. The results will be of great significance in utilizing CELMS data more widely as an additional tool to study the geological structure of the lunar basalt basin. Full article
(This article belongs to the Special Issue Advances in Exploring the Moon, Mars, and Asteroids Using Spacecraft Remote Sensing and Other Toolkits)
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16 pages, 3605 KiB  
Article
Lunar Procellarum KREEP Terrane (PKT) Stratigraphy and Structure with Depth: Evidence for Significantly Decreased Th Concentrations and Thermal Evolution Consequences
by Jingyi Zhang, James W. Head, Jianzhong Liu and Ross W. K. Potter
Remote Sens. 2023, 15(7), 1861; https://doi.org/10.3390/rs15071861 - 30 Mar 2023
Cited by 4 | Viewed by 2169 | Correction
Abstract
Dating from the lunar magma ocean solidification period, the Procellarum KREEP Terrane (PKT) occupies 16% of the surface but has a much higher thorium abundance compared to the rest of the Moon and is thus interpreted to carry 40% of the radioactive elements [...] Read more.
Dating from the lunar magma ocean solidification period, the Procellarum KREEP Terrane (PKT) occupies 16% of the surface but has a much higher thorium abundance compared to the rest of the Moon and is thus interpreted to carry 40% of the radioactive elements by volume in the form of an anomalously thick KREEP-rich layer. Subsequent research has focused on the processes responsible for PKT concentration and localization (e.g., degree-1 convection, farside impact basin effects, etc.), and the effect of PKT high-radioactivity localization on lunar thermal evolution (e.g., topography relaxation, mantle heating, late-stage mare basalt generation, etc.). Here we use a stratigraphic approach and new crustal thickness data to probe the nature of the PKT with depth. We find that most PKT characteristics can be explained by sequential impact cratering events that excavated and redistributed to the surface/near-surface a much thinner Th-rich KREEP layer at depth, implying that no anomalous conditions of PKT thickness, radioactive abundances, geodynamics, thermal effects or magma generation are likely to be required as in the previous studies. Full article
(This article belongs to the Special Issue Advances in Exploring the Moon, Mars, and Asteroids Using Spacecraft Remote Sensing and Other Toolkits)
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14 pages, 3244 KiB  
Article
Wavelength Calibration for the LIBS Spectra of the Zhurong Mars Rover
by Yizhong Zhang, Xin Ren, Zhaopeng Chen, Wangli Chen, Zhenqiang Zhang, Xiangfeng Liu, Weiming Xu, Jianjun Liu and Chunlai Li
Remote Sens. 2023, 15(6), 1494; https://doi.org/10.3390/rs15061494 - 08 Mar 2023
Cited by 2 | Viewed by 1660
Abstract
China’s first Mars rover, Zhurong, landed on the southern region of Utopia Planitia, Mars, on 14 May 2021 (UTC). Zhurong is equipped with the Mars Surface Composition Detection Package (MarSCoDe), which analyzes the Martian surface’s material composition. Composed of laser-induced breakdown spectroscopy (LIBS), [...] Read more.
China’s first Mars rover, Zhurong, landed on the southern region of Utopia Planitia, Mars, on 14 May 2021 (UTC). Zhurong is equipped with the Mars Surface Composition Detection Package (MarSCoDe), which analyzes the Martian surface’s material composition. Composed of laser-induced breakdown spectroscopy (LIBS), short-wave infrared spectroscopy (SWIR), and a microimaging camera, MarsCoDe can work at a distance of 1.6–7 m to analyze element abundance and the mineralogy of targets on the Martian surface. Analysis shows that the wavelengths of MarSCoDe onboard LIBS spectra acquired within the same probe period will have different degrees of drift, leading to deviation in qualitative and quantitative elemental analysis. This paper finds that the spectrum drift follows a quadratic function relationship with the CCD temperature of the MarSCoDe spectrometer, based on which a wavelength calibration method is established. According to the function, the drift of a certain channel is calculated by the corresponding CCD temperature, and then the wavelength of the spectrum is calibrated by the drift. The accuracy of this calibration method for the position of peak wavelength in the LIBS spectrum can reach about 1/5 of the apparatus spectral width, and the cross-validation analysis using a norite standard sample shows that it is comparable to the wavelength calibration accuracy of the ChemCam onboard data product. Full article
(This article belongs to the Special Issue Advances in Exploring the Moon, Mars, and Asteroids Using Spacecraft Remote Sensing and Other Toolkits)
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17 pages, 7151 KiB  
Article
A Target-Based Non-Uniformity Self-Correction Method for Infrared Push-Broom Hyperspectral Sensors
by Bing Wu, Chengyu Liu, Rui Xu, Zhiping He, Bin Liu, Wangli Chen and Qing Zhang
Remote Sens. 2023, 15(5), 1186; https://doi.org/10.3390/rs15051186 - 21 Feb 2023
Cited by 2 | Viewed by 1418
Abstract
Non-uniformity in the response of spectral image elements is an inevitable phenomenon in hyperspectral imaging, which mainly manifests itself as the presence of band noise in the acquired hyperspectral data. This problem is prominent in the infrared band owing to the detector material, [...] Read more.
Non-uniformity in the response of spectral image elements is an inevitable phenomenon in hyperspectral imaging, which mainly manifests itself as the presence of band noise in the acquired hyperspectral data. This problem is prominent in the infrared band owing to the detector material, operating environment, and other factors. Non-uniformity is an important factor that can affect the quality of the hyperspectral data, which has a serious impact on both data analysis and applications and requires corrections via technical means wherever possible. This paper proposes a novel target-based non-uniformity self-correction method for infrared push-broom hyperspectral images. The Mars Mineralogical Spectrometer (MMS) onboard the Tianwen-1 orbiter was used as the research and application object. The model is constructed and applied to the target scene characteristics and detection patterns of Mars remote sensing exploration, which are combined with the causes of noise generation in the infrared spectral image bands. The design of the MMS dual-channel Visible-Near-Infrared (V-NIR) and Near-Mid-Infrared (N-MIR) co-field of view co-target detection and laboratory calibration data for the V-NIR spectral band can achieve non-uniformity corrections (NUCs). Therefore, for the MMS in-orbit Mars exploration mission, the method selected spectral data (920–1055 nm) characterized by a reduced atmospheric influence to iteratively obtain the homogeneous region, which was used to calculate the non-uniformity correction factor for the N-MIR spectral band. This method was compared, validated, and evaluated with other conventional methods using both laboratory and in-orbit hyperspectral data. The results showed that the experimental data corrections were comparable to laboratory calibrations, with a maximum relative deviation of <2.6%. These results prove that our method not only provides an excellent non-uniformity correction, but also ensures spectral fidelity. It can thus be used as a non-uniformity correction process for the MMS and similar hyperspectral imagers. Full article
(This article belongs to the Special Issue Advances in Exploring the Moon, Mars, and Asteroids Using Spacecraft Remote Sensing and Other Toolkits)
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19 pages, 2496 KiB  
Article
Initial Drift Correction and Spectral Calibration of MarSCoDe Laser-Induced Breakdown Spectroscopy on the Zhurong Rover
by Liangchen Jia, Xiangfeng Liu, Weiming Xu, Xuesen Xu, Luning Li, Zhicheng Cui, Ziyi Liu and Rong Shu
Remote Sens. 2022, 14(23), 5964; https://doi.org/10.3390/rs14235964 - 25 Nov 2022
Cited by 3 | Viewed by 1436
Abstract
The Mars Surface Composition Detector (MarSCoDe) carried by the Zhurong rover of China’s Tianwen-1 mission uses Laser-Induced Breakdown Spectroscopy (LIBS) to detect and analyze the material composition on Martian surfaces. As one extraterrestrial remote LIBS system, it is necessary to adopt effective and [...] Read more.
The Mars Surface Composition Detector (MarSCoDe) carried by the Zhurong rover of China’s Tianwen-1 mission uses Laser-Induced Breakdown Spectroscopy (LIBS) to detect and analyze the material composition on Martian surfaces. As one extraterrestrial remote LIBS system, it is necessary to adopt effective and reliable preprocessing methods to correct the spectral drift caused by the changes in environmental conditions, to ensure the analysis accuracy of LIBS scientific data. This paper focuses on the initial spectral drift correction and estimates the accuracy of on-board wavelength calibration on the LIBS calibration target measured by the MarSCoDe LIBS. There may be two cases during the instrument launch and landing, as well as the long-term operation: (a) the initial wavelength calibration relationship can still apply to the on-board LIBS measurement; and (b) the initial wavelength calibration relationship has been changed, and a new on-board calibration is needed to establish the current relationship. An approach of matching based on global iterative registration (MGR) is presented in respect to case (a). It is also compared with the approach of particle swarm optimization (PSO) for case (b). Furthermore, their accuracy is estimated with the comparison to the National Institute of Standards and Technology (NIST) database. The experimental results show that the proposed approach can effectively correct the drift of the on-board LIBS spectrum. The the root-mean-square error (RMSE) of the internal accord accuracy for three channels is 0.292, 0.223 and 0.247 pixels, respectively, compared with the corrected Ti-alloy spectrum and the NIST database, and the RMSE of the external accord accuracy is 0.232, 0.316 and 0.229 pixels, respectively, for other samples. The overall correction accuracy of the three channels is better than one-third of the sampling interval. Full article
(This article belongs to the Special Issue Advances in Exploring the Moon, Mars, and Asteroids Using Spacecraft Remote Sensing and Other Toolkits)
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22 pages, 9929 KiB  
Article
Comparison on Quantitative Analysis of Olivine Using MarSCoDe Laser-Induced Breakdown Spectroscopy in a Simulated Martian Atmosphere
by Xiangfeng Liu, Weiming Xu, Luning Li, Xuesen Xu, Hai Qi, Zhenqiang Zhang, Fan Yang, Zhixin Yan, Chongfei Liu, Rujun Yuan, Xiong Wan and Rong Shu
Remote Sens. 2022, 14(21), 5612; https://doi.org/10.3390/rs14215612 - 07 Nov 2022
Cited by 2 | Viewed by 1597
Abstract
A Mars Surface Composition Detector (MarSCoDe) instrument mounted on Zhurong rover of Tianwen-1, adopts Laser-Induced Breakdown Spectroscopy (LIBS), with no sample preparation or dust and coatings ablation required, to conduct rapid multi-elemental analysis and characterization of minerals, rocks and soils on the surface [...] Read more.
A Mars Surface Composition Detector (MarSCoDe) instrument mounted on Zhurong rover of Tianwen-1, adopts Laser-Induced Breakdown Spectroscopy (LIBS), with no sample preparation or dust and coatings ablation required, to conduct rapid multi-elemental analysis and characterization of minerals, rocks and soils on the surface of Mars. To test the capability of MarSCoDe LIBS measurement and quantitative analysis, some methods of multivariate analysis on olivine samples with gradient concentrations were inspected based on the spectra acquired in a Mars-simulated environment before the rover launch in 2020. Firstly, LIBS spectra need preprocessing, including background subtraction, random signal denoising, continuum baseline removal, spectral drift correction and wavelength calibration, radiation calibration, and multi-channel spectra subset merging. Then, the quantitative analysis with univariate linear regression (ULR) and multivariate linear regression (MLR) are performed on the characteristic lines, while principal component regression (PCR), partial least square regression (PLSR), ridge, least-absolute-shrinkage-and-selection-operator (LASSO) and elastic net, and nonlinear analysis with back-propagation (BP) are conducted on the entire spectral information. Finally, the performance on the quantitative olivine analyzed by MarSCoDe LIBS is compared with the mean spectrum and all spectra for each sample and evaluated by some statistical indicators. The results show that: (1) the calibration curve of ULR constructed by the characteristic line of magnesium and iron indicates the linear relationship between the spectral signal and the element concentration, and the limits of detection of forsterite and fayalite is 0.9943 and 2.0536 (c%) analyzed by mean spectra, and 2.3354 and 3.8883 (c%) analyzed by all spectra; (2) the R2 value on the calibration and validation of all the methods is close to 1, and the predicted concentration estimated by these calibration models is close to the true concentration; (3) the shrinkage or regularization technique of ridge, LASSO and elastic net perform better than the ULR and MLR, except for ridge overfitting on the testing sample; the best results can be obtained by the dimension reduction technique of PCR and PLSR, especially with PLSR; and BP is more applicable for the sample measured with larger spectral dataset. Full article
(This article belongs to the Special Issue Advances in Exploring the Moon, Mars, and Asteroids Using Spacecraft Remote Sensing and Other Toolkits)
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17 pages, 4252 KiB  
Article
Convolutional Neural Network Chemometrics for Rock Identification Based on Laser-Induced Breakdown Spectroscopy Data in Tianwen-1 Pre-Flight Experiments
by Fan Yang, Weiming Xu, Zhicheng Cui, Xiangfeng Liu, Xuesen Xu, Liangchen Jia, Yuwei Chen, Rong Shu and Luning Li
Remote Sens. 2022, 14(21), 5343; https://doi.org/10.3390/rs14215343 - 25 Oct 2022
Cited by 5 | Viewed by 2072
Abstract
Laser-induced breakdown spectroscopy (LIBS) coupled with chemometrics is an efficient method for rock identification and classification, which has considerable potential in planetary geology. A great challenge facing the LIBS community is the difficulty to accurately discriminate rocks with close chemical compositions. A convolutional [...] Read more.
Laser-induced breakdown spectroscopy (LIBS) coupled with chemometrics is an efficient method for rock identification and classification, which has considerable potential in planetary geology. A great challenge facing the LIBS community is the difficulty to accurately discriminate rocks with close chemical compositions. A convolutional neural network (CNN) model has been designed in this study to identify twelve types of rock, among which some rocks have similar compositions. Both the training set and the testing set are constructed based on the LIBS spectra acquired by Mars Surface Composition Detector (MarSCoDe) for China’s Tianwen-1 Mars exploration mission. All the spectra were collected from dedicated rock pellet samples, which were placed in a simulated Martian atmospheric environment. The classification performance of the CNN has been compared with that of three alternative machine learning algorithms, i.e., logistic regression (LR), support vector machine (SVM), and linear discriminant analysis (LDA). Among the four methods, it is on the CNN model that the highest classification correct rate has been obtained, as assessed by precision score, recall score, and the harmonic mean of precision and recall. Furthermore, the classification accuracy is inspected more quantitatively via Brier score, and the CNN is still the best performing model. The results demonstrate that the CNN-based chemometrics are an efficient tool for rock identification with LIBS spectra collected in a simulated Martian environment. Despite the relatively small sample set, this study implies that CNN-supported LIBS classification is a promising analytical technique for Tianwen-1 Mars mission and more planetary explorations in the future. Full article
(This article belongs to the Special Issue Advances in Exploring the Moon, Mars, and Asteroids Using Spacecraft Remote Sensing and Other Toolkits)
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16 pages, 7809 KiB  
Article
Machine Learning Fusion Multi-Source Data Features for Classification Prediction of Lunar Surface Geological Units
by Wei Zuo, Xingguo Zeng, Xingye Gao, Zhoubin Zhang, Dawei Liu and Chunlai Li
Remote Sens. 2022, 14(20), 5075; https://doi.org/10.3390/rs14205075 - 11 Oct 2022
Cited by 4 | Viewed by 1541
Abstract
Taking the Chang’e-4 and Chang’e-5 landing areas as the study areas, this study extracts the geological unit information from the regional USGS geological map, as well as the feature information such as topography and geomorphology, material composition and mineral abundance from Chang’e-2 DOM [...] Read more.
Taking the Chang’e-4 and Chang’e-5 landing areas as the study areas, this study extracts the geological unit information from the regional USGS geological map, as well as the feature information such as topography and geomorphology, material composition and mineral abundance from Chang’e-2 DOM and DEM, wide angle camera (WAC) and Kaguya multi-band imager data. By applying methods including the statistical-based estimation of mutual information of data and the integrated-algorithmic-model-based evaluation of feature importance to this extracted information, we screen the significant features and construct a high-precision classification model by combining machine learning algorithm with important features of sample data. The practical application of the multi-classification prediction on the complex geological units in the two study areas achieves 97.9% and 95.1% accuracy. At the same time, the significant characteristics of the study area are mined, and the rules and knowledge associated with the geological evolution of the study area are obtained. In this study, we carry out research on quantitative prediction and identification of lunar surface geological units based on large samples and construct a high-precision multi-classification model to achieve automatic classification and prediction on large sample geological units with high accuracy. This method provides a new idea for the predicted mapping of geological units of lunar global digital mapping. In addition, it helps to fully exploit the useful information in the data and enrich the knowledge regarding the formation and evolution of the Moon. Full article
(This article belongs to the Special Issue Advances in Exploring the Moon, Mars, and Asteroids Using Spacecraft Remote Sensing and Other Toolkits)
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26 pages, 5509 KiB  
Article
New Insights into Surface Deposits in the Balmer-Kapteyn Cryptomare Region Provided by Chang’E-2 Microwave Radiometer Data
by Tianqi Tang, Zhiguo Meng, Yi Lian, Zhiyong Xiao, Jingsong Ping, Zhanchuan Cai, Xiaoping Zhang, Xuegang Dong and Yuanzhi Zhang
Remote Sens. 2022, 14(18), 4556; https://doi.org/10.3390/rs14184556 - 12 Sep 2022
Cited by 5 | Viewed by 1445
Abstract
Lunar cryptomare records both early-stage mare volcanisms and large-scale impact cratering, which can provide important information about the thermal evolution of the Moon. We built a mixing dielectric constant model to represent the cryptomare deposits mixed by highland debris and mare deposits, and [...] Read more.
Lunar cryptomare records both early-stage mare volcanisms and large-scale impact cratering, which can provide important information about the thermal evolution of the Moon. We built a mixing dielectric constant model to represent the cryptomare deposits mixed by highland debris and mare deposits, and the proper radiative transfer simulation was constructed to evaluate the thermal emission features of surface deposits in the cryptomare region. The microwave radiometer (MRM) data in the Balmer-Kapteyn region were extracted, and the linear interpolation method was used to generate brightness temperature (TB) maps at noon and at night. To enhance the correlation between cryptomare deposits and TB performances, normalized TB (nTB) and TB difference (dTB) maps were also generated. Combined with the datasets, including Lunar Reconnaissance Orbiter Wide Angle Camera, Lunar Orbiter Laser Altimeter, and Diviner and Clementine UV–VIS, the main findings are as follows: (1) The mare-like cryptomare deposits were discovered and identified according to the nTB and dTB performances. Combined with the surface compositions, at least two kinds of buried mare deposits were identified in the B-K region, which erupted during different episodes. (2) A construct-like volcanic feature was suggested by the nTB and dTB performances. (3) The results of our analysis indicated the presence of materials with low dTB anomalies in the northern and southwestern parts of the cryptomare region and in the mare unit within the Vendelinus crater, which illustrates the heterogeneity of the lunar crust in the vertical direction. Full article
(This article belongs to the Special Issue Advances in Exploring the Moon, Mars, and Asteroids Using Spacecraft Remote Sensing and Other Toolkits)
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18 pages, 2132 KiB  
Article
A New Spectral Transformation Approach and Quantitative Analysis for MarSCoDe Laser-Induced Breakdown Spectroscopy (LIBS) Data
by Guobin Jin, Zhongchen Wu, Zongcheng Ling, Changqing Liu, Wang Liu, Wenxi Chen and Li Zhang
Remote Sens. 2022, 14(16), 3960; https://doi.org/10.3390/rs14163960 - 15 Aug 2022
Cited by 5 | Viewed by 1715
Abstract
Zhurong rover successfully landed on the southern of Utopia Planet of Mars on 15 May 2021. One laser-induced breakdown spectroscopy (LIBS) system, the main payload of the Mars Surface Composition Detector (MarSCoDe), was installed on the Zhurong rover aimed to measure the elements [...] Read more.
Zhurong rover successfully landed on the southern of Utopia Planet of Mars on 15 May 2021. One laser-induced breakdown spectroscopy (LIBS) system, the main payload of the Mars Surface Composition Detector (MarSCoDe), was installed on the Zhurong rover aimed to measure the elements and their abundance in Martian regolith. Now, there are three sets of LIBS system (ChemCam, SuperCam and MarSCoDe) working on Mars at difference landing sites with diverse geologic features. For Mars exploration, cross-validation is necessary to expand the model compatibility, test data validity, and get more available data of the same type payloads. Spectral transformation approach is the first step and crucial for cross-validation of LIBS analysis model. Herein, a new 4-step spectral transformation approach was proposed to transform the LIBS spectra between three different LIBS systems (i.e., ChemCam, MarSCoDe, SDU-LIBS (recorded by self-built LIBS system)), whose data were partly different in spectral characteristics. Based on this approach, SDU-LIBS and MarSCoDe spectra data were transformed into ChemCam uniform and then the three kinds of LIBS data can have more similar spectral features and share one PLS (partial least squares) model for quantitative analysis. Our approach enables to make up the signal differences between different LIBS systems and gets acceptable quantitative analysis results of SDU-LIBS and MarSCoDe spectra using quantitative PLS model built by ChemCam calibration sample set. This work verified feasibility and availability of our approach for cross validation of different LIBS systems. Based on this method, MarSCoDe data were analyzed and got the preliminary satisfying results although no analysis model of laboratory replica payload was available under the existing conditions. Full article
(This article belongs to the Special Issue Advances in Exploring the Moon, Mars, and Asteroids Using Spacecraft Remote Sensing and Other Toolkits)
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12 pages, 1491 KiB  
Article
Simplified Relations for the Martian Night-Time OH* Suitable for the Interpretation of Observations
by Mykhaylo Grygalashvyly, Dmitry S. Shaposhnikov, Alexander S. Medvedev, Gerd Reinhold Sonnemann and Paul Hartogh
Remote Sens. 2022, 14(16), 3866; https://doi.org/10.3390/rs14163866 - 09 Aug 2022
Cited by 1 | Viewed by 1156
Abstract
Observations of excited hydroxyl (OH*) emissions are broadly used for inferring information about atmospheric dynamics and composition. We present several analytical approximations for characterizing the excited hydroxyl layer in the Martian atmosphere. They include the OH* number density at the maximum and the [...] Read more.
Observations of excited hydroxyl (OH*) emissions are broadly used for inferring information about atmospheric dynamics and composition. We present several analytical approximations for characterizing the excited hydroxyl layer in the Martian atmosphere. They include the OH* number density at the maximum and the height of the peak, along with the relations for assessing different impacts on the OH* layer under night-time conditions. These characteristics are determined by the ambient temperature, atomic oxygen concentration, and their vertical gradients. The derived relations can be used for the analysis of airglow measurements and the interpretation of their variations. Full article
(This article belongs to the Special Issue Advances in Exploring the Moon, Mars, and Asteroids Using Spacecraft Remote Sensing and Other Toolkits)
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13 pages, 4862 KiB  
Technical Note
Inversion of Upstream Solar Wind Parameters from ENA Observations at Mars
by Yiteng Zhang, Lei Li, Lianghai Xie, Linggao Kong, Wenya Li, Binbin Tang, Jijie Ma and Aibing Zhang
Remote Sens. 2023, 15(7), 1721; https://doi.org/10.3390/rs15071721 - 23 Mar 2023
Viewed by 1229
Abstract
An algorithm has been developed to invert the solar wind parameters from the hydrogen energetic neutral atom (H-ENA) measured in near-Mars space. Supposing the H-ENA is produced by change exchange collision between protons that originated in the solar wind and neutrals in the [...] Read more.
An algorithm has been developed to invert the solar wind parameters from the hydrogen energetic neutral atom (H-ENA) measured in near-Mars space. Supposing the H-ENA is produced by change exchange collision between protons that originated in the solar wind and neutrals in the exosphere, an H-ENA model is established based on the magnetohydrodynamic (MHD) simulation of the solar wind interaction with Mars, to study the H-ENA characteristics. It is revealed that the solar wind H-ENAs are high-speed, low-temperature beams, just like the solar wind, while the magnetosheath H-ENAs are slower and hotter, with broader energy distribution. Assuming Maxwellian velocity distribution, the solar wind H-ENA flux is best fitted by a Gaussian function, from which the solar wind velocity, density, and temperature can be retrieved. Further investigation, based on the ENA flux simulated by the H-ENA model, reveals that the accuracy of inversed solar wind parameters is related to the angular and energy resolutions of the ENA detector. Finally, the algorithm is verified using the H-ENA observations from the Tianwen-1 mission. The upstream solar wind velocity when inversed is close to that of the in situ plasma measurement. Our result suggests the solar wind parameters inversed from H-ENA observation could be an important supplement to the dataset supporting studies on the Martian space environment, where long-term continuous monitoring of the upstream SW condition is lacking. Full article
(This article belongs to the Special Issue Advances in Exploring the Moon, Mars, and Asteroids Using Spacecraft Remote Sensing and Other Toolkits)
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11 pages, 3372 KiB  
Technical Note
Simulation of Transient Topside Layer in the Martian Ionosphere
by Chunhua Jiang, Rong Tian and Lehui Wei
Remote Sens. 2023, 15(3), 770; https://doi.org/10.3390/rs15030770 - 29 Jan 2023
Viewed by 1095
Abstract
Many Mars missions, e.g., Mariner, Viking, Mars Global Surveyor (MGS), Mars Express (MEX), and Mars Atmosphere and Volatile Evolution (MAVEN), have been launched to study the Martian atmosphere. These observations have improved our understanding of the ionosphere of Mars. Observations show that the [...] Read more.
Many Mars missions, e.g., Mariner, Viking, Mars Global Surveyor (MGS), Mars Express (MEX), and Mars Atmosphere and Volatile Evolution (MAVEN), have been launched to study the Martian atmosphere. These observations have improved our understanding of the ionosphere of Mars. Observations show that the Martian ionosphere could be divided into an M2 layer (at ~140 km altitude) and an M1 layer (at ~110 km altitude), ionized by EUV and X-ray solar radiation, respectively. However, there are still many scientific questions about the Martian ionosphere. A transient topsider layer (also called the M3 layer, at ~160–~220 km) can frequently be measured above the M2 layer in the Martian ionosphere. The statistical characteristics of the M3 layer show that it is not irradiated by solar incident radiation. Many candidate mechanisms have been suggested to explain the formation of the M3 layer. However, the method of describing or modeling the M3 layer is still one of the many open scientific questions about the Martian ionosphere. This study used a one-dimensional model, including photochemical production, loss, and dynamic transport processes to simulate the transient topside layer in the Martian ionosphere. The M3 layer was reproduced by a perturbed vertical plasma drift in this study. The enhancement of the electron temperature induced by the dynamic process of plasma could facilitate the formation of the M3 layer. Our results show that the vertical transport process of plasma might be more crucial in producing the M3 layer in the topside Martian ionosphere. Full article
(This article belongs to the Special Issue Advances in Exploring the Moon, Mars, and Asteroids Using Spacecraft Remote Sensing and Other Toolkits)
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13 pages, 4562 KiB  
Technical Note
The Lunar Regolith Structure and Electromagnetic Properties of Chang’E-5 Landing Site
by Yuxi Li, Bin Zhou, Shaoxiang Shen, Wei Lu, Chuanjun Tang, Shidong Li, Yan Su, Shun Dai and Guangyou Fang
Remote Sens. 2022, 14(18), 4539; https://doi.org/10.3390/rs14184539 - 11 Sep 2022
Cited by 3 | Viewed by 2008
Abstract
On 1 December 2020, China’s Chang’E-5 (CE-5) probe successfully landed in the northeastern Oceanus Procellarum. This work mainly presents the results of Lunar Regolith Penetrating Radar (LRPR) equipped on the CE-5 Lander. The lunar regolith structure of the landing site from the surface [...] Read more.
On 1 December 2020, China’s Chang’E-5 (CE-5) probe successfully landed in the northeastern Oceanus Procellarum. This work mainly presents the results of Lunar Regolith Penetrating Radar (LRPR) equipped on the CE-5 Lander. The lunar regolith structure of the landing site from the surface to 3-m depth is unveiled by LRPR, which found that abundant rock fragments are distributed in uniform lunar regolith. The imaging result proved that the drilling and sampling process was prevented by big rocks at about 100 cm depth. On the basis of the response of lunar soil to electromagnetic (EM) wave, the EM properties of the landing site estimate that the relative dielectric constant and the loss tangent are 2.520 ± 0.186 and 0.0133 ± 0.0020, respectively. Full article
(This article belongs to the Special Issue Advances in Exploring the Moon, Mars, and Asteroids Using Spacecraft Remote Sensing and Other Toolkits)
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