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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 October 2024) | Viewed by 16837

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Special Issue Editors

Prof. Dr. Zhiping He

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Guest Editor

Shanghai Institute of Technical Physics, Chinese Academy of Sciences, Shanghai 200083, China
Interests: space optics; optoelectronic technology

Prof. Dr. Oleg Korablev

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Guest Editor

Space Research Institute, Russian Academy of Sciences, 84/32 Profsoyuznaya Str., Moscow 117997, Russia
Interests: physics of planets; remote sensing; space instruments

Prof. Dr. Bin Xue

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Guest Editor

Xi'an Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Xi’an 710119, China
Interests: spectral imaging technology; new optical remote sensing method

Prof. Dr. Genghua Huang

E-Mail Website
Guest Editor

Shanghai Institute of Technical Physics, Chinese Academy of Sciences, Shanghai 200083, China
Interests: satellite-based laser altimetry; laser 3D imaging; photon counting LIDAR

Special Issue Information

Dear Colleagues,

Planetary exploration is of great significance in promoting the development of science and technology and advancing human civilization more broadly, representing the frontier field of science and technology development in the world. Laser and optical remote sensing payloads, including cameras, spectrometers, imaging spectrometers, and LiDAR, have been widely applied in planetary exploration, playing an irreplaceable role with excellent prospects for scientific and technological applications. While the techniques of laser and optical remote sensing for planetary exploration are similar to those applied for Earth remote sensing, the application of laser and optical remote sensing in planetary exploration is confronted with problems such as complex deep space environments, lighter and smaller requirements on payloads with lower power consumption and long-life payload design requirements, and therefore requires specialized research.

With the development of computational optics, machine learning, materials science and other fields, laser and optical payloads will definitely achieve higher resolution, higher sensitivity and wider detection range to help planetary remote sensing exploration.

This Special Issue aims to study key technologies in laser and optical remote sensing, focusing on topics ranging from remote sensing payload development, breakthroughs in key technologies, research on quantification methods and data processing for scientific applications. In addition, new methods and research on the topic of multi-source data composite applications in laser/optical remote sensing are also welcome. Articles may cover, but are not limited to, the following areas:

Laser and optical remote sensing payload for planetary exploration
Research on key technique of remote sensing payload
Research on spectral detection and component analysis technique
Research on LiDAR detection and navigation technique
Research on passive optical remote sensing technique
Optical laser/detector/sensor for navigation and guidance of deep space exploration
Research on novel method and technique adapted to complex space exploration
Dark and weak target detection method
Research on modeling/simulation/calibration/data processing/analysis of remote sensing payload
Multi-source remote sensing data composite application method

Prof. Dr. Zhiping He
Prof. Dr. Oleg Korablev
Prof. Dr. Bin Xue
Prof. Dr. Genghua Huang
Guest Editors

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Keywords

laser and optical remote sensing payload
key technique of remote sensing payload
spectrometer and imaging spectrometer
laser altimeter and LiDAR
optical camera
calibration technique
data processing technique
lunar/Martian/planetary/deep space exploration
laser/optical/multi-spectral/hyper-spectral remote sensing

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Published Papers (11 papers)

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Research

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16 pages, 6426 KiB

Open AccessArticle

Unveiling Illumination Variations During a Lunar Eclipse: Multi-Wavelength Spaceborne Observations of the January 21, 2019 Event

by Min Shu, Tianyi Xu, Wei Cai, Shibo Wen, Hengyue Jiao and Yunzhao Wu

Remote Sens. 2024, 16(22), 4181; https://doi.org/10.3390/rs16224181 - 9 Nov 2024

Viewed by 398

Abstract

Space-based observations of the total lunar eclipse on 21 January 2019 were conducted using the geostationary Earth-orbiting satellite Gaofen-4 (GF-4). This study represents a pioneering effort to address the observational gap in full-disk lunar eclipse photometry from space. With its high resolution and ability to capture the entire lunar disk, GF-4 enabled both quantitative and qualitative analyses of the variations in lunar brightness, as well as spectra and color changes, across two spatial dimensions, from the whole lunar disk to resolved regions. Our results indicate that before the totality phase of the lunar eclipse, the irradiance of the Moon diminishes to below approximately 0.19% of that of the uneclipsed Moon. Additionally, we observed an increase in lunar brightness at the initial entry into the penumbra. This phenomenon is attributed to the opposition effect, providing scientific evidence for this unexpected behavior. To investigate detailed spectral variations, specific calibration sites, including the Chang’E-3 landing site, MS-2 in Mare Serenitatis, and the Apollo 16 highlands, were analyzed. Notably, the red-to-blue ratio dropped below 1 near the umbra, contradicting the common perception that the Moon appears red during lunar eclipses. The red/blue ratio images reveal that as the Moon enters Earth’s umbra, it does not simply turn red; instead, a blue-banded ring appears at the boundary due to ozone absorption and the lunar surface composition. These findings significantly enhance our understanding of atmospheric effects on lunar eclipses and provide crucial reference information for the future modeling of lunar eclipse radiation, promoting the integration of remote sensing science with astronomy. Full article

(This article belongs to the Special Issue Laser and Optical Remote Sensing for Planetary Exploration)

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14 pages, 3057 KiB

Open AccessArticle

A Signal-Based Auto-Focusing Method Available for Raman Spectroscopy Acquisitions in Deep Space Exploration

by Yiheng Liu, Changqing Liu, Yanqing Xin, Ping Liu, Ayang Xiao and Zongcheng Ling

Remote Sens. 2024, 16(5), 820; https://doi.org/10.3390/rs16050820 - 27 Feb 2024

Viewed by 1360

Abstract

With the development of technology and methodologies, Raman spectrometers are becoming efficient candidate payloads for planetary materials characterizations in deep space exploration missions. The National Aeronautics and Space Administration (NASA) already deployed two Raman instruments, Super Cam and SHERLOC, onboard the Perseverance Rover in the Mars 2020 mission. In the ground test, the SHERLOC team found an axial offset (~720 μm) between the ACI (Autofocus Context Imager) and the spectrometer focus, which would obviously affect the acquired Raman intensity if not corrected. To eliminate this error and, more importantly, simplify the application of Raman instruments in deep space exploration missions, we propose an automatic focusing method wherein Raman signals are optimized during spectrum collection. We put forward a novel method that is realized by evaluating focus conditions numerically and searching for the extremum point as the final focal point. To verify the effectiveness of this method, we developed an Auto-focus Raman Probe (SDU-ARP) in our laboratory. This method provides a research direction for scenarios in which spectrometers cannot focus on a target using any other criterion. The utilization of this auto-focusing method can offer better spectra and fewer acquisitions in focusing procedure, and the spectrometer payload can be deployed in light-weight bodies (e.g., asteroids) or in poor illumination conditions (e.g., the permanently shadowed region in the Lunar south polar area) in deep space exploration missions. Full article

(This article belongs to the Special Issue Laser and Optical Remote Sensing for Planetary Exploration)

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23 pages, 9419 KiB

Open AccessArticle

A Space Target Detection Method Based on Spatial–Temporal Local Registration in Complicated Backgrounds

by Yueqi Su, Xin Chen, Chen Cang, Fenghong Li and Peng Rao

Remote Sens. 2024, 16(4), 669; https://doi.org/10.3390/rs16040669 - 13 Feb 2024

Cited by 3 | Viewed by 1137

Abstract

Human space exploration has brought a growing crowded operating environment for in-orbit spacecraft. Monitoring the space environment and detecting space targets with photoelectric equipment has extensive and realistic significance in space safety. In this study, a local spatial–temporal registration (LSTR) method is proposed to detect moving small targets in space. Firstly, we applied the local region registration to estimate the neighbor background motion model. Secondly, we analyzed the temporal local grayscale difference between the strong clutter and target region and measured the temporal local–central region difference to enhance the target. Then, the temporal pixel contrast map was calculated, which further retains the target signal and suppresses the residue clutter. Finally, a simple adaptive threshold segmentation algorithm was applied to the saliency map to segment the targets. Comparative experiments were conducted on four groups of image sequences to validate the efficiency and robustness of the algorithm. The experimental findings indicate that the proposed method performs well in target enhancement and clutter suppression under different scenarios. Full article

(This article belongs to the Special Issue Laser and Optical Remote Sensing for Planetary Exploration)

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17 pages, 10763 KiB

Open AccessArticle

YOLO-Crater Model for Small Crater Detection

by Lingli Mu, Lina Xian, Lihong Li, Gang Liu, Mi Chen and Wei Zhang

Remote Sens. 2023, 15(20), 5040; https://doi.org/10.3390/rs15205040 - 20 Oct 2023

Cited by 5 | Viewed by 2998

Abstract

Craters are the most prominent geomorphological features on the surface of celestial bodies, which plays a crucial role in studying the formation and evolution of celestial bodies as well as in landing and planning for surface exploration. Currently, the main automatic crater detection models and datasets focus on the detection of large and medium craters. In this paper, we created 23 small lunar crater datasets for model training based on the Chang’E-2 (CE-2) DOM, DEM, Slope, and integrated data with 7 kinds of visualization stretching methods. Then, we proposed the YOLO-Crater model for Lunar and Martian small crater detection by replacing EioU and VariFocal loss to solve the crater sample imbalance problem and introducing a CBAM attention mechanism to mitigate interference from the complex extraterrestrial environment. The results show that the accuracy (

P

= 87.86%,

R

= 66.04%, and

F 1

= 75.41%) of the Lunar YOLO-Crater model based on the DOM-MMS (Maximum-Minimum Stretching) dataset is the highest and better than that of the YOLOX model. The Martian YOLO-Crater, trained by the Martian dataset from the 2022 GeoAI Martian Challenge, achieves good performance with

P

= 88.37%,

R

= 69.25%, and

F 1

= 77.65%. It indicates that the YOLO-Crater model has strong transferability and generalization capability, which can be applied to detect small craters on the Moon and other celestial bodies. Full article

(This article belongs to the Special Issue Laser and Optical Remote Sensing for Planetary Exploration)

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13 pages, 2698 KiB

Open AccessCommunication

Pilot Study of Low-Light Enhanced Terrain Mapping for Robotic Exploration in Lunar PSRs

by Jae-Min Park, Sungchul Hong and Hyu-Soung Shin

Remote Sens. 2023, 15(13), 3412; https://doi.org/10.3390/rs15133412 - 5 Jul 2023

Cited by 2 | Viewed by 1753

Abstract

The recent discovery of water ice in the lunar polar shadowed regions (PSRs) has driven interest in robotic exploration, due to its potential utilization to generate water, oxygen, and hydrogen that would enable sustainable human exploration in the future. However, the absence of direct sunlight in the PSRs poses a significant challenge for the robotic operation to obtain clear images, consequently impacting crucial tasks such as obstacle avoidance, pathfinding, and scientific investigation. In this regard, this study proposes a visual simultaneous localization and mapping (SLAM)-based robotic mapping approach that combines dense mapping and low-light image enhancement (LLIE) methods. The proposed approach was experimentally examined and validated in an environment that simulated the lighting conditions of the PSRs. The mapping results show that the LLIE method leverages scattered low light to enhance the quality and clarity of terrain images, resulting in an overall improvement of the rover’s perception and mapping capabilities in low-light environments. Full article

(This article belongs to the Special Issue Laser and Optical Remote Sensing for Planetary Exploration)

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26 pages, 4823 KiB

Open AccessArticle

Investigation into the Affect of Chemometrics and Spectral Data Preprocessing Approaches upon Laser-Induced Breakdown Spectroscopy Quantification Accuracy Based on MarSCoDe Laboratory Model and MarSDEEP Equipment

by Ziyi Liu, Luning Li, Weiming Xu, Xuesen Xu, Zhicheng Cui, Liangchen Jia, Wenhao Lv, Zhihui Shen and Rong Shu

Remote Sens. 2023, 15(13), 3311; https://doi.org/10.3390/rs15133311 - 28 Jun 2023

Cited by 3 | Viewed by 1696

Abstract

As part of China’s Tianwen-1 Mars mission, the Mars Surface Composition Detector (MarSCoDe) instrument on the Zhurong rover adopts laser-induced breakdown spectroscopy (LIBS) to perform chemical component detection of the materials on the Martian surface. However, it has always been a challenging issue to achieve high accuracy in LIBS quantification. This study investigated the effect of chemometrics and spectral data preprocessing approaches on LIBS quantification accuracy based on different chemometrics algorithms and diverse preprocessing methods. A total of 2340 LIBS spectra were collected from 39 kinds of geochemical samples by a laboratory duplicate model of the MarSCoDe instrument. The samples and the MarSCoDe laboratory model were placed in a simulated Martian atmosphere environment based on equipment called the Mars-Simulated Detection Environment Experiment Platform (MarSDEEP). To quantify the concentration of MgO in the samples, we employed two common LIBS chemometrics; i.e., partial least squares (PLS) and a back-propagation neural network (BPNN). Meanwhile, in addition to necessary routine preprocessing such as dark subtraction, we used five specific preprocessing approaches, namely intensity normalization, baseline removal, Mg-peak wavelength correction, Mg-peak feature engineering, and concentration range reduction. The results indicated that the performance of the BPNN was better than that of the PLS and that the preprocessing of Mg-peak wavelength correction had the most prominent effect to improve the quantification accuracy. The results of this study are expected to provide inspiration for the processing and analysis of the in situ LIBS data acquired by MarSCoDe on Mars. Full article

(This article belongs to the Special Issue Laser and Optical Remote Sensing for Planetary Exploration)

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21 pages, 8599 KiB

Open AccessArticle

Passive 3D Imaging Method Based on Photonics Integrated Interference Computational Imaging System

by Ben Ge, Qinghua Yu, Jialiang Chen and Shengli Sun

Remote Sens. 2023, 15(9), 2333; https://doi.org/10.3390/rs15092333 - 28 Apr 2023

Cited by 2 | Viewed by 1439

Abstract

Planetary, lunar, and deep space exploration has become the frontier of remote sensing science, and three-dimensional (3D) positioning imaging technology is an important part of lunar and deep space exploration. This paper presents a novel passive 3D imaging method based on the photonics integrated interference computational imaging system. This method uses a photonics integrated interference imaging system with a complex lens array. The midpoints of the interference baselines formed by these lenses are not completely overlapped. The distance between the optical axis and the two lenses of the interference baseline are not equal. The system is used to obtain the complex coherence factor of the object space at a limited working distance, and the image evaluation optimization algorithm is used to obtain the clear images and 3D information of the targets of interest. The simulation results show that this method is effective for the working scenes with targets located at single or multiple limited working distances. The sharpness evaluation function of the target presents a good unimodality near its actual distance. The experimental results of the interference of broad-spectrum light show that the theoretical basis of this method is feasible. Full article

(This article belongs to the Special Issue Laser and Optical Remote Sensing for Planetary Exploration)

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19 pages, 21341 KiB

Open AccessArticle

A Phase Difference Measurement Method for Integrated Optical Interferometric Imagers

by Jialiang Chen, Qinghua Yu, Ben Ge, Chuang Zhang, Yan He and Shengli Sun

Remote Sens. 2023, 15(8), 2194; https://doi.org/10.3390/rs15082194 - 21 Apr 2023

Cited by 2 | Viewed by 2319

Abstract

Interferometric imagers based on integrated optics have the advantages of miniaturization and low cost compared with traditional telescope imaging systems and are expected to be applied in the field of space target detection. Phase measurement of the complex coherence factor is crucial for the image reconstruction of interferometric imaging technology. This study discovers the effect of the phase of the complex coherence factor on the extrema of the interference fringes in the interferometric imager and proposes a method for calculating the phase difference of the complex coherence factor of two interference signals by comparing the extrema of the interferometric fringes in the area of approximate linear change in the envelope shape to obtain the phase information required for imaging. Experiments using two interferometric signals with a phase difference of

π

were conducted to verify the validity and feasibility of the phase difference measurement method. Compared with the existing phase measurement methods, this method does not need to calibrate the position of the zero optical path difference and can be applied to the integrated optical interferometric imager using a single-mode fiber, which also allows the imager to work in a more flexible way. The theoretical phase measurement accuracy of this method is higher than 0.05

π

, which meets the image reconstruction requirements. Full article

(This article belongs to the Special Issue Laser and Optical Remote Sensing for Planetary Exploration)

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Review

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23 pages, 6340 KiB

Open AccessReview

A Review of Lidar Technology in China’s Lunar Exploration Program

by Genghua Huang and Weiming Xu

Remote Sens. 2024, 16(23), 4354; https://doi.org/10.3390/rs16234354 - 22 Nov 2024

Viewed by 180

Abstract

Lidar technology plays a pivotal role in lunar exploration, particularly in terrain mapping, 3D topographic surveying, and velocity measurement, which are crucial for guidance, navigation, and control. This paper reviews the current global research and applications of lidar technology in lunar missions, noting that existing efforts are primarily focused on 3D terrain mapping and velocity measurement. The paper also discusses the detailed system design and key results of the laser altimeter, laser ranging sensor, laser 3D imaging sensor, and laser velocity sensor used in the Chang’E lunar missions. By comparing and analyzing similar foreign technologies, this paper identifies future development directions for lunar laser payloads. The evolution towards multi-beam single-photon detection technology aims to enhance the point cloud density and detection efficiency. This manuscript advocates that China actively advance new technologies and conduct space application research in areas such as multi-beam single-photon 3D terrain mapping, lunar surface water ice measurement, and material composition analysis, to elevate the use of laser pay-loads in lunar and space exploration. Full article

(This article belongs to the Special Issue Laser and Optical Remote Sensing for Planetary Exploration)

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10 pages, 3369 KiB

Open AccessTechnical Note

Photometric Characteristics of Lunar Soils: Results from Spectral Analysis of Chang’E-5 In Situ Data Using Legendre Phase Function

by Meizhu Wang, Dawei Liu, Rui Xu and Zhiping He

Remote Sens. 2024, 16(16), 3053; https://doi.org/10.3390/rs16163053 - 19 Aug 2024

Viewed by 722

Abstract

China’s Chang’E-5 (CE-5) mission has successfully landed in the Northern Oceanus Procellarum of the Moon. Lunar mineralogical spectrometer (LMS), as one of the important payloads onboard CE-5 Lander–Ascender Combination, aims to study the physical and compositional properties of the landing area. This paper applies the Legendre phase function to correct the photometric effects on the LMS in situ spectra and reveal the photometric characteristic of the CE-5 landing area. LMS obtained the reflectance spectra in various geometric configurations by performing full-view scanning of the CE-5 landing area. By fitting these LMS spectral data, the parameters

b = - 0.29

and

c = 0.44

of the Legendre phase function were obtained. This indicates the strong forward scattering characteristic of the CE-5 landing area, which is similar to that of the Chang’E-4 (CE-4) landing area, and the side scattering is weaker than that of CE-4. In addition, we derived the FeO content of the landing area using the photometric-corrected LMS spectral data. Our results demonstrate that the estimated FeO content of the landing area is close to the laboratory measured data of the returned samples. The LMS in situ reflectance data will contribute to a better understanding of the physical and mineralogical properties of the CE-5 landing area. Full article

(This article belongs to the Special Issue Laser and Optical Remote Sensing for Planetary Exploration)

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16 pages, 4674 KiB

Open AccessTechnical Note

Multi-Aperture Joint-Encoding Fourier Ptychography for a Distributed System

by Tianyu Wang, Meng Xiang, Fei Liu, Jinpeng Liu, Xue Dong, Sen Wang, Gang Li and Xiaopeng Shao

Remote Sens. 2024, 16(6), 1017; https://doi.org/10.3390/rs16061017 - 13 Mar 2024

Cited by 1 | Viewed by 1205

Abstract

High-resolution infrared remote sensing imaging is critical in planetary exploration, especially under demanding engineering conditions. However, due to diffraction, the spatial resolution of conventional methods is relatively low, and the spatial bandwidth product limits imaging systems’ design. Extensive research has been conducted with the aim of enhancing spatial resolution in remote sensing using a multi-aperture structure, but obtaining high-precision co-phase results using a sub-aperture remains challenging. A new high-resolution imaging method utilizing multi-aperture joint-encoding Fourier ptychography (JEFP) is proposed as a practical means to achieve super-resolution infrared imaging using distributed platforms. We demonstrated that the JEFP approach achieves pixel super-resolution with high efficiency, without requiring subsystems to perform mechanical scanning in space or to have high position accuracy. Our JEFP approach extends the application scope of Fourier ptychographic imaging, especially in distributed platforms for planetary exploration applications. Full article

(This article belongs to the Special Issue Laser and Optical Remote Sensing for Planetary Exploration)

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