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Advances in Remote Sensing of Mars: Geomorphological Research and Environmental Assessment

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: 31 May 2024 | Viewed by 2079

Special Issue Editor


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Guest Editor
Department of Earth and Planetary Sciences, University of New Mexico, Albuquerque, NM 87131, USA
Interests: geomorphology and surface processes; remote sensing; geographic information system; climate reconstruction
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

While our current understanding of Martian geomorphology has significantly improved over the last decade, many processes and rates remain poorly understood and/or are subject to multiple and conflicting interpretations, in part due to a lack of clear terrestrial analogs. The coupling of new sensors and high-resolution repeat imagery has allowed the observation of surface-altering processes, which provide insights into recent changes on the Martian surface. As a result, many existing hypotheses regarding form and process, including some dating to interpretations made during the era of early coarser resolution imagery, are being overturned.

This Special Issue aims to address the use of new satellite sensors and rover platforms in order to interpret and reinterpret Martian geomorphology. Research papers may address anything from satellite and rover remote sensing systems that collect data to the analysis of specific geomorphic forms and processes using this data, to studies that interpret past and current rates of deposition and erosion on the Martian surface. The scope of the submitted articles includes, but is not limited, to the following topics:

  • Satellite and rover remote sensing of the Martian surface:
    • satellite/rover RS sensor systems (current and future planned)
    • terrain analysis techniques as applied to mars
    • change detection/current geomorphic activity
  • Analysis of Martian geomorphic forms, processes and rates, including, but not limited to, the following:
    • glacial: cirques, eskers, moraines, lineated valley fill
    • periglacial: frost polygons, araneiforms
    • hillslope: slope streaks, recurring slope lineae, landslides, chaos terrain
    • aeolian: TARs, barchans, ventifacts, yardangs, dust deposition
    • fluvial: river channels, deltas, alluvial fans
    • rates of erosion and deposition: cratering impacts, physical and chemical processes
  • Terrestrial analogs for Martian landforms

Prof. Dr. Louis Scuderi
Guest Editor

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

  • satellite sensors
  • rover sensors
  • terrain analysis
  • geomorphic processes
  • Martian landforms
  • rates
  • terrestrial analogs

Published Papers (2 papers)

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20 pages, 7774 KiB  
Article
Automatic Martian Polar Ice Cap Extraction Algorithm for Remote Sensing Data and Analysis of Their Spatiotemporal Variation Characteristics
by Weiye Xu, Zhulin Chen, Huifang Zhang, Kun Jia, Degyi Yangzom, Xiang Zhao, Yunjun Yao and Xiaotong Zhang
Remote Sens. 2024, 16(7), 1201; https://doi.org/10.3390/rs16071201 - 29 Mar 2024
Viewed by 422
Abstract
The detection of Martian polar ice cap change patterns is important for understanding their effects on driving Mars’s global water cycle and for regulating atmospheric circulation. However, current Martian ice cap identification using optical remote sensing data mainly relies on visual interpretation, which [...] Read more.
The detection of Martian polar ice cap change patterns is important for understanding their effects on driving Mars’s global water cycle and for regulating atmospheric circulation. However, current Martian ice cap identification using optical remote sensing data mainly relies on visual interpretation, which makes it difficult to quickly extract ice caps from multiple images and analyze their fine-scale spatiotemporal variation characteristics. Therefore, this study proposes an automatic Martian polar ice cap extraction algorithm for remote sensing data and analyzes the dynamic change characteristics of the Martian North Pole ice cap using time-series data. First, the automatic Martian ice cap segmentation algorithm was developed based on the ice cap features of high reflectance in the blue band and low saturation in the RGB band. Second, the Martian North Pole ice cap was extracted for the three Martian years MY25, 26, and 28 using Mars Orbiter Camera (MOC) Mars Daily Global Maps (MDGMs) data, which had better spatiotemporal continuity to analyze its variation characteristics. Lastly, the spatiotemporal variation characteristics of the ice cap and the driving factors of ice cap ablation were explored for the three aforementioned Martian years. The results indicated that the proposed automatic ice cap extraction algorithm had good performance, and the classification accuracy exceeded 93%. The ice cap ablation boundary retreat rates and spatiotemporal distributions were similar for the three years, with approximately 105 km2 of ice cap ablation for every one degree of areocentric longitude of the Sun (Ls). The main driving factor of ice cap ablation was solar radiation, which was mainly related to Ls. In addition, elevation had a different effect on ice cap ablation at different Ls in the same latitude area near the ablation boundary of the ice cap. Full article
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20 pages, 5898 KiB  
Article
Rover Attitude and Camera Parameter: Rock Measurements on Mars Surface Based on Rover Attitude and Camera Parameter for Tianwen-1 Mission
by Dian Zheng, Linhui Wei, Weikun Lv, Yu Liu and Yumei Wang
Remote Sens. 2023, 15(18), 4388; https://doi.org/10.3390/rs15184388 - 06 Sep 2023
Viewed by 1381
Abstract
Rocks, prominent features on the surface of Mars, are a primary focus of Mars exploration missions. The accuracy of recognizing rock information, including size and position, deeply affects the path planning for rovers on Mars and the geological exploration of Mars. In this [...] Read more.
Rocks, prominent features on the surface of Mars, are a primary focus of Mars exploration missions. The accuracy of recognizing rock information, including size and position, deeply affects the path planning for rovers on Mars and the geological exploration of Mars. In this paper, we present a rock measurement method for the Mars surface based on a Rover Attitude and Camera Parameter (RACP). We analyze the imaging process of the Navigation and Terrain Camera (NaTeCam) on the Zhurong rover, which involves utilizing a semi-spherical model (SSM) to characterize the camera’s attitude, a projection model (PM) to connect the image data with the three-dimensional (3D) environment, and then estimating the distance and size of rocks. We conduct a test on NaTeCam images and find that the method is effective in measuring the distance and size to Martian rocks and identifying rocks at specific locations. Furthermore, an analysis of the impact of uncertain factors is conducted. The proposed RACP method offers a reliable solution for automatically analyzing the rocks on Mars, which provides a possible solution for the route planning in similar tasks. Full article
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