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Remote Sensing
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Remote Sensing in Space Geodesy and Cartography Methods (Fourth Edition)
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Remote Sensing in Space Geodesy and Cartography Methods (Fourth Edition)

A Special Issue of Remote Sensing (ISSN 2072-4292) belonging to the section "Satellite Missions for Earth and Planetary Exploration".

Deadline for manuscript submissions: 31 January 2027 | Viewed by 2342

Editors

Prof. Dr. Jinyun Guo

E-Mail Website
Guest Editor
College of Geodesy and Geomatics, Shandong University of Science and Technology, Qingdao, China
Interests: space geodesy; marine geodesy; physical geodesy
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Cheinway Hwang

E-Mail Website
Guest Editor
Department of Civil Engineering, National Yang Ming Chiao Tung University, Hsinchu 300, Taiwan
Interests: geodesy; remote sensing; hydrology
Special Issues, Collections and Topics in MDPI journals
Dr. Yu Sun

E-Mail Website
Guest Editor
Academy of Digital China, Fuzhou University, Fuzhou, China
Interests: space geodesy; physical geodesy
Special Issues, Collections and Topics in MDPI journals
Dr. Tzu-pang Tseng

E-Mail Website
Guest Editor
Department of Civil Engineering, National Kaohsiung University of Science and Technology, Kaohsiung, Taiwan
Interests: satellite geodesy; GNSS
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

In recent decades, the massive amounts of remote sensing data obtained from space geodetic techniques, such as satellite gravimetry, satellite geodesy, GNSS, InSAR, and LiDAR, have greatly advanced the field of space geodesy and have also facilitated innovation in data mining and cartography methods. As new space platforms are continuously developed and novel measurements obtained, space geodesy and cartography are faced with unprecedented challenges and opportunities; these include the accurate determination of Earth’s shape and gravity field, the better visualization of multisource data, and the construction of a digital Earth. All of these fields require more advanced and sophisticated remote sensing methods and applications.

It is our pleasure to announce the new edition of the Special Issue "Remote Sensing in Space Geodesy and Cartography Methods (Fourth Edition)". This Special Issue will highlight remote sensing methods and applications in space geodesy and cartography, embracing the scope of the Satellite Missions for Earth and Planetary Exploration section of Remote Sensing.

This Special Issue will publish studies covering all aspects of satellite gravimetry, satellite altimetry, satellite optical/multispectral/hyperspectral/SAR remote sensing, GNSS, LiDAR, deep space detection, space geodetic theory and techniques, the space environment, and the digital Earth; additionally, we are interested in theory, methods, techniques, algorithms, data validation, scientific products, and applications. Review articles are also welcome. Articles may address, but are not limited to, the following:

  • Digital Earth;
  • Topography and thematic mapping;
  • Earth shape and gravity field modeling;
  • Co-ordinate reference frame and deformation monitoring;
  • Planet geodesy and cartography;
  • Space environment and deep space detection.

Prof. Dr. Jinyun Guo
Prof. Dr. Cheinway Hwang
Dr. Yu Sun
Dr. Tzu-pang Tseng
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 250 words) can be sent to the Editorial Office for assessment.

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-anonymized 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

  • GNSS
  • LiDAR
  • satellite gravimetry
  • satellite altimetry
  • optical/multispectral/hyperspectral/SAR remote sensing
  • space geodetic technique
  • deep space detection

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  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
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  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
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Further information on MDPI's Special Issue policies can be found here.

Related Special Issue

Published Papers (3 papers)

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Research

19 pages, 16403 KB  
Article
Seafloor Topography Prediction from Altimetry-Derived Gravity Data Using a Wavelet-Assisted and High-Frequency Enhancement Neural Network
by Shuai Wang, Shaofeng Bian, Guojun Zhai and Nengfang Chao
Remote Sens. 2026, 18(18), 3174; https://doi.org/10.3390/rs18183174 - 15 Sep 2026
Viewed by 134
Abstract
Seafloor topography (ST) has important significance for earth science research, marine resource exploration and underwater navigation. The conventional ST inversion methods are limited by linear approximation and poor small-scale topographic feature prediction. This study proposes a novel Wavelet-Assisted and High-Frequency Enhancement Neural Network [...] Read more.
Seafloor topography (ST) has important significance for earth science research, marine resource exploration and underwater navigation. The conventional ST inversion methods are limited by linear approximation and poor small-scale topographic feature prediction. This study proposes a novel Wavelet-Assisted and High-Frequency Enhancement Neural Network (WAHFENN), an architecture integrating discrete wavelet transform (DWT), low-frequency retainment module (LFRM) and high-frequency enhancement module (HFEM) to enhance bathymetry prediction accuracy and capture small-scale topographic features. We apply the WAHFENN to predict the ST in a local area of the South China Sea (SCS). The results demonstrate that the WAHFENN model achieves a standard deviation (STD) of 50.66 m against shipborne single-beam check points, outperforming the topo_27.1 and SDUST2023BCO models by 31.46% and 28.49%, and surpassing the conventional Smith and Sandwell (SAS) method, gravity-geological method (GGM), and convolutional neural network (CNN) method by 78.23 m, 65.18 m, and 4.4 m, respectively. The WAHFENN model achieves a STD of 103.80 m against shipborne multibeam bathymetry data, representing improvements of 38.75%, 25.16%, and 15.58% over the SAS, GGM, and CNN models, respectively. The topographic detail comparisons and power spectral density analysis demonstrate that the WAHFENN model has the potential to outperform conventional methods in identifying small-scale topographic features. Full article
(This article belongs to the Special Issue Remote Sensing in Space Geodesy and Cartography Methods (Fourth Edition))
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21 pages, 6507 KB  
Article
Deriving Deflection of the Vertical and Gravity Anomaly from SWOT/KaRIn Data Using an Optimized Discretization Method
by Hengyang Guo, Xiaoyun Wan and Xing Wu
Remote Sens. 2026, 18(9), 1360; https://doi.org/10.3390/rs18091360 - 28 Apr 2026
Viewed by 663
Abstract
The Surface Water and Ocean Topography (SWOT) mission carries a Ka-band interferometric radar altimeter (KaRIn), which enables high-resolution wide-swath measurements of sea surface height, providing new opportunities for deriving high-precision marine gravity fields. The discretization method used by the Scripps Institution of Oceanography [...] Read more.
The Surface Water and Ocean Topography (SWOT) mission carries a Ka-band interferometric radar altimeter (KaRIn), which enables high-resolution wide-swath measurements of sea surface height, providing new opportunities for deriving high-precision marine gravity fields. The discretization method used by the Scripps Institution of Oceanography (SIO) is one of the simplest methods for deriving deflections of the vertical (DOV), as it avoids parameter estimation and complex mathematical procedures. However, this method only uses adjacent observations for first-order differentiation and ignores diagonal directions, resulting in relatively low data utilization for SWOT/KaRIn data. The optimized discretization method is proposed to take advantage of the two-dimensional characteristics of KaRIn data. Multi-directional data is introduced to estimate the DOV (SWOT_DOV), and the numerical differentiation strategy is extended to higher orders. These significantly improve the solution quality. The standard deviation (STD) of the differences between SWOT_DOV and north_32.1 is 1.60 μrad, and that with east_32.1 is 2.02 μrad. Gravity anomalies are further derived using the inverse Vening-Meinesz formula. Validation using NCEI shipborne gravity data indicates an STD of 3.85 mGal. Further analyses considering seafloor topography gradient, depth, and offshore distance demonstrate that SWOT/KaRIn data have a stable capability to restore high-precision marine gravity field features. Full article
(This article belongs to the Special Issue Remote Sensing in Space Geodesy and Cartography Methods (Fourth Edition))
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17 pages, 12414 KB  
Article
A Spatiotemporal Subgrid Least Squares Approach to DEM Generation of the Greenland Ice Sheet from ICESat-2 Laser Altimetry
by Qiyu Wang, Jinyun Guo, Tao Jiang and Xin Liu
Remote Sens. 2025, 17(24), 4027; https://doi.org/10.3390/rs17244027 - 13 Dec 2025
Viewed by 761
Abstract
Greenland, home to the largest ice sheet in the Northern Hemisphere, provides a crucial digital elevation model (DEM) for understanding polar climate evolution and valuable data for global climate change research. Based on ICESat-2 laser altimetry data collected from satellite observations over Greenland [...] Read more.
Greenland, home to the largest ice sheet in the Northern Hemisphere, provides a crucial digital elevation model (DEM) for understanding polar climate evolution and valuable data for global climate change research. Based on ICESat-2 laser altimetry data collected from satellite observations over Greenland between November 2020 and November 2021, the Shandong University of Science and Technology 2021 DEM (SDUST2021DEM) with 500 m grid resolution at the epoch of May 2021 was constructed using a spatiotemporally fitted subgrid least squares method. The precision of the DEM was evaluated by comparison with National Aeronautics and Space Administration IceBridge data and supplemented by GNSS station measurements. The median difference between the DEM and IceBridge data was −0.33 m, the mean deviation −0.58 m, and the median absolute deviation 2.31 m. The accuracy of SDUST2021DEM exhibits a clear spatial pattern: it is higher in the central ice sheet than at the margins, decreases in regions with complex terrain, and remains more reliable in areas characterized by gentle slopes and flat terrain. Overall, the SDUST2021DEM demonstrates stable accuracy and can reliably produce high-precision DEMs for a specific temporal epoch. Full article
(This article belongs to the Special Issue Remote Sensing in Space Geodesy and Cartography Methods (Fourth Edition))
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