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

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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: 30 June 2025 | Viewed by 10256

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Prof. Dr. Jinyun Guo

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College of Geodesy and Geomatics, Shandong University of Science and Technology, Qingdao, China
Interests: space geodesy; marine geodesy; physical geodesy
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Prof. Dr. Cheinway Hwang

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Department of Civil Engineering, National Yang Ming Chiao Tung University, Taiwan 300093, China
Interests: geodesy; remote sensing; hydrology
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Dr. Yu Sun

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Academy of Digital China, Fuzhou University, Fuzhou, China
Interests: space geodesy; physical geodesy
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Dr. Tzu-pang Tseng

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Department of Civil Engineering, National Kaohsiung University of Science and Technology, Kaohsiung, Taiwan
Interests: satellite geodesy; GNSS
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Dr. Pia Addabbo

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Department of Telecommunication Engineering, University of Study “Giustino Fortunato”, 82100 Benevento, Italy
Interests: statistical signal processing; image processing; passive remote sensing (hyperspectral sensor); active remote sensing (radar, SAR, GNSS-R)
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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.
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
Dr. Pia Addabbo
Guest Editors

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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

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

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Remote Sensing in Space Geodesy and Cartography Methods II in Remote Sensing (10 articles)

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19 pages, 7979 KiB

Open AccessArticle

Seabed Depth Prediction Using Multi-Scale Gravity Anomalies and Fully Connected Deep Neural Networks: A Novel Approach Applied to the South China Sea

by Jiajia Yuan, Chen Yang, Di Dong, Jinyun Guo, Dechao An and Daocheng Yu

Remote Sens. 2025, 17(3), 412; https://doi.org/10.3390/rs17030412 - 25 Jan 2025

Viewed by 596

Abstract

Accurate seabed topography is crucial for marine research, resource exploration, and engineering applications. While deep learning techniques have been widely applied in seabed inversion, existing methods often overlook the multi-scale influence of gravity anomalies, particularly the critical role of short-wavelength gravity anomalies in resolving fine-scale bathymetric features. In this study, we propose a novel Fully Connected Deep Neural Network (FCDNN) approach that systematically integrates long-wavelength, short-wavelength, and residual gravity anomaly components for seabed topography inversion. Using multi-satellite altimetry-derived gravity anomaly data (SIO V32.1) and shipborne bathymetric data (NCEI), we constructed a high-resolution (1′ × 1′) seabed topography model for the South China Sea (108°E–121°E, 6°N–23°N), termed FCD_Depth_SCS. The workflow included multi-scale decomposition of gravity anomalies, linear regression-based residual calculation, and FCDNN-based nonlinear training to capture the complex relationships between gravity anomalies and water depth. The FCD_Depth_SCS model achieved a difference standard deviation (STD) of 44.755 m and a mean absolute percentage error (MAPE) of 2.903% when validated against 160,476 shipborne control points. This performance significantly outperformed existing models, including GEBCO_2024, SIOv25.1, DTU18, and GGM_Depth (derived from the Gravity–Geologic Method), whose STDs were 82.234 m, 108.241 m, 186.967 m, and 58.874 m, respectively. Notably, the inclusion of short-wavelength gravity anomalies enabled the model to capture fine-scale bathymetric variations, particularly in open-sea regions. However, challenges remain near coastlines and complex terrains, highlighting the need for further model partitioning to address localized nonlinearity. This study highlights the benefits of integrating multi-scale gravity anomaly data with a fully connected deep neural network. Employing this innovative and robust approach enables high-resolution inversion of seabed topography with enhanced precision. The proposed method provides significant advancements in accuracy and resolution, contributing valuable insights for marine environmental research, resource management, and oceanographic studies. Full article

(This article belongs to the Special Issue Remote Sensing in Space Geodesy and Cartography Methods (Third Edition))

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22 pages, 24182 KiB

Open AccessArticle

Evaluating the Signal Contribution of the DTU21MSS on Coastal Mean Dynamic Topography and Geostrophic Current Modeling: A Case Study in the African–European Region

by Hongkai Shi, Xiufeng He and Ole Baltazar Andersen

Remote Sens. 2024, 16(24), 4714; https://doi.org/10.3390/rs16244714 - 17 Dec 2024

Viewed by 609

Abstract

With the accumulation of synthetic aperture radar (SAR) altimetry data and advancements in retracking algorithms, the improved along-track spatial resolution and signal-to-noise ratio have significantly enhanced the availability and precision of sea surface height (SSH) measurements, particularly in challenging environments such as coastal areas, ocean currents, and polar regions. These improvements have refined the accuracy and reliability of mean sea surface (MSS) models, which in turn have enhanced the precision of mean dynamic topography (MDT) and geostrophic current models. However, in-depth research is required to quantify the specific contributions of SAR altimetry to these critical regions and their impacts on the MSS, MDT, and geostrophic currents. Given that DTU21MSS (Technical University of Denmark MSS 2021) incorporates a substantial amount of SAR altimetry data, this study utilized independent Sentinel-3A altimetric observations to evaluate the signal improvements of DTU21MSS compared with DTU15MSS, with a focus on its performance in polar, coastal, and current regions. In addition, a least-squares-based approach was employed to assess the impact of the improved MSS model on the deduced MDT and geostrophic current signals. The numerical results revealed that DTU21MSS achieved an accuracy improvement of ~8% within 20 km offshore compared with DTU15MSS. In the polar regions within 100 km offshore, DTU21MSS exhibited a maximum signal enhancement of ~0.1 m, with overall improvements of 10–20%. The DTU21MSS-derived MDT solution demonstrates better consistency with validation data, reducing the standard deviation of misfits from 0.058 m to 0.054 m. Signal enhancements of maximumly 0.1 m were observed in the polar regions and the Mediterranean/Red Sea. Furthermore, improvements in the MSS and its error information could directly enhance the deduced MDT models, highlighting its foundational role in precise oceanographic modeling. Full article

(This article belongs to the Special Issue Remote Sensing in Space Geodesy and Cartography Methods (Third Edition))

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15 pages, 5214 KiB

Open AccessArticle

An Empirical Atmospheric Weighted Average Temperature Enhancement Model in the Yunnan–Guizhou Plateau Considering Surface Temperature

by Yi Shen, Peicheng Li, Bingbing Zhang, Tong Wu, Junkuan Zhu, Qing Li and Wang Li

Remote Sens. 2024, 16(23), 4366; https://doi.org/10.3390/rs16234366 - 22 Nov 2024

Viewed by 694

Abstract

Atmospheric weighted mean temperature (Tm) is a crucial parameter for retrieving atmospheric precipitation using the Global Navigation Satellite System (GNSS). It plays a significant role in GNSS meteorology research. Although existing empirical models can quickly obtain Tm values for the Yunnan–Guizhou Plateau, their accuracy is generally low due to the region’s complex environmental and climatic conditions. To address this issue, this study proposes an enhanced empirical Tm model tailored for the Yunnan–Guizhou Plateau. This new model incorporates surface temperature (Ts) data and employs the least squares method to determine model coefficients, thereby improving the accuracy of the Tm empirical model. The research utilizes observational data from 16 radiosonde stations in the Yunnan–Guizhou Plateau from 2010 to 2018. By integrating Ts into the Hourly Global Pressure and Temperature (HGPT2) model, we establish the enhanced empirical Tm model, referred to as YGTm. We evaluate the accuracy of the YGTm model using Tm values obtained from the 2019 radiosonde station measurements as a reference. A comparative analysis is conducted against the Bevis model, the HGPT2 model, and the regional linear model LTm. The results indicate that at the modeling stations, the proposed enhanced model improves Tm prediction accuracy by 24.9%, 16.1%, and 22.4% compared to the Bevis, HGPT2, and LTm models, respectively. At non-modeling stations, the accuracy improvements are 26.2%, 17.1% and 24.4%, respectively. Furthermore, the theoretical root mean square error and relative error from using the YGTm model for GNSS water vapor retrieval are 0.27 mm and 0.93%, respectively, both of which outperform the comparative models. Full article

(This article belongs to the Special Issue Remote Sensing in Space Geodesy and Cartography Methods (Third Edition))

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15 pages, 14538 KiB

Open AccessArticle

Weighted Fusion Method of Marine Gravity Field Model Based on Water Depth Segmentation

by Zhaoyu Chen, Qiankun Liu, Ke Xu and Xiaoyang Liu

Remote Sens. 2024, 16(21), 4107; https://doi.org/10.3390/rs16214107 - 3 Nov 2024

Viewed by 1040

Abstract

Among the marine gravity field models derived from satellite altimetry, the Scripps Institution of Oceanography (SIO) series and Denmark Technical University (DTU) series models are the most representative and are often used to integrate global gravity field models, which were inverted by the deflection of vertical method and sea surface height method, respectively. The fusion method based on the offshore distance used in the EGM2008 model is just model stitching, which cannot realize the true fusion of the two types of marine gravity field models. In the paper, a new fusion method based on water depth segmentation is proposed, which established the Precision–Depth relationship of each model in each water depth segment in the investigated area, then constructed the FUSION model by weighted fusion based on the precision predicted from the Precision–Depth relationship at each grid in the whole region. The application in the South China Sea shows that the FUSION model built by the new fusion method has better accuracy than SIO28 and DTU17, especially in shallow water and offshore areas. Within 20 km offshore, the RMS of the FUSION model is 5.10 mGal, which is 8% and 4% better than original models, respectively. Within 100 m of shallow water, the accuracy of the FUSION model is 4.01 mGal, which is 14% and 12% higher than the original models, respectively. A further analysis shows that the fusion model is in better agreement with the seabed topography than original models. The new fusion method can blend the effective information of original models to provide a higher-precision marine gravity field. Full article

(This article belongs to the Special Issue Remote Sensing in Space Geodesy and Cartography Methods (Third Edition))

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16 pages, 13284 KiB

Open AccessArticle

Recovering Bathymetry Using BP Neural Network Combined with Modified Gravity–Geologic Method: A Case Study in the South China Sea

by Xiaodong Chen, Min Zhong, Mingzhi Sun, Dechao An, Wei Feng and Meng Yang

Remote Sens. 2024, 16(21), 4023; https://doi.org/10.3390/rs16214023 - 29 Oct 2024

Cited by 1 | Viewed by 1261

Abstract

The gravity–geologic method (GGM) is widely used for bathymetric predictions. However, the conventional GGM cannot be applied in regions without actual bathymetric data. The modified gravity–geologic method (MGGM) enhances the accuracy of bathymetric models by supplementing short-wavelength gravity anomalies with an a priori bathymetric model, but it overlooks the significance of actual bathymetric data in the prediction process. In this study, we used the BP neural network (BPNN), incorporating shipborne depth soundings and coastline data as zero-depth estimates combined with the MGGM to produce a bathymetric model (BPGGM_BAT) for the South China Sea (105°E–122°E, 0°N–26°N). The results indicate that the BPGGM_BAT model decreases the root-mean-square (RMS) of bathymetry differences from 154.33 m to approximately 140.43 m relative to multibeam depth data. Additionally, the RMS differences between the BPGGM_BAT model and multibeam depth data show further improvements of 19.63%, 20.10%, and 19.54% when compared with the recently released SRTM15_V2.6, GEBCO_2022, and topo_V27.1 models, respectively. The precision of the BPGGM_BAT model is comparable to that of the SDUST2023BCO model, as verified using multibeam depth data in open sea regions. The BPGGM_BAT model outperforms existing models with RMS differences of 8.54% to 32.66%, as verified using Electronic Navigational Chart (ENC) bathymetric data in the regions around the Zhongsha and Nansha Islands. A power density analysis suggests that the BPGGM_BAT model is superior to the MGGM_BAT model for predicting seafloor topography within wavelengths shorter than 15 km, and its performance is closely consistent with that of the topo_V27.1 and SDUST2023BCO models. Overall, this integrated method demonstrates significant potential for improving the accuracy of bathymetric predictions. Full article

(This article belongs to the Special Issue Remote Sensing in Space Geodesy and Cartography Methods (Third Edition))

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10 pages, 783 KiB

Open AccessCommunication

Comparing Link Budget Requirements for Future Space-Based Interferometers

by Callum Scott Sambridge, Jobin Thomas Valliyakalayil and Kirk McKenzie

Remote Sens. 2024, 16(19), 3598; https://doi.org/10.3390/rs16193598 - 26 Sep 2024

Viewed by 1025

Abstract

Inter-satellite interferometric missions are critical in the ongoing monitoring of climate change. Next-generation Earth geodesy missions are opportunities to improve on mission cost and measurement sensitivity through revised design. To be considered feasible, mission architectures must meet an optical power requirement that factors in both shot noise and laser frequency noise. Reference-transponder mission configurations, like the Gravity Recovery and Climate Experiment-Follow On (GRACE-FO) mission, are designed for measurement down to a received carrier-to-noise density ratio of 70 dB-Hz—1.9 picowatts in shot-noise-limited detection. This work shows, through modeling and simulation, that the optical power level required to perform robust measurement varies significantly between mission configurations. Alternate configurations, such as retro-reflector-based schemes, can operate robustly down to much lower carrier-to-noise density ratios, with the example parameters considered here: down to 29 dB-Hz—150 attowatts in shot-noise-limited detection. These results motivate exploration of alternate missions configurations with revised optical power requirements, increasing the feasibility of new designs. Full article

(This article belongs to the Special Issue Remote Sensing in Space Geodesy and Cartography Methods (Third Edition))

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21 pages, 8385 KiB

Open AccessArticle

On the Integration of VLBI Observations to GENESIS into Global VGOS Operations

by David Schunck, Lucia McCallum and Guifré Molera Calvés

Remote Sens. 2024, 16(17), 3234; https://doi.org/10.3390/rs16173234 - 31 Aug 2024

Cited by 2 | Viewed by 1239

Abstract

The upcoming European Space Agency (ESA) satellite mission GENESIS is an Earth-orbiting satellite carrying instruments of all four space geodetic techniques. The onboard transmitter for Very Long Baseline Interferometry (VLBI) will allow the observation of the satellite with VLBI radio telescopes. The objective of this study is to investigate the integration of VLBI observations of GENESIS into the operations of the VLBI Global Observing System (VGOS). Based on both current and foreseeable modern VGOS antenna networks, we consider the realistic observability of both geodetic radio sources and GENESIS. We conduct a comprehensive scheduling and perform extensive simulations of the VLBI observations. We assume that observations of GENESIS are scheduled within regular, geodetic experiments. The integration of GENESIS as an additional source in the scheduling results in a minimal degradation in the geodetic parameter estimation of station positions and dUT1 of less than 0.09 mm and 0.06 μs, respectively. The results suggest to schedule scans of GENESIS at intervals of about 5 min to limit the decrease in the number of observations of geodetic sources to less than 5% with respect to schedules containing only geodetic radio sources. The schedules for 24 h experiments comprise about 150 to 200 scans and 1000 to 5000 observations of GENESIS, depending on the size of the utilized network. The frame tie accuracy between the VLBI and GENESIS frames is assessed in the form of station positions, which are solely estimated from observations of GENESIS. Multiple 24 h experiments are simulated over 52 weeks with assumed session cadences of two to three experiments per week. By stacking the normal equations from three months of experiments, we obtain station position estimates with a precision of less than 10 mm. After 12 months, the repeatabilites are reduced to less than 5 mm. Full article

(This article belongs to the Special Issue Remote Sensing in Space Geodesy and Cartography Methods (Third Edition))

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16 pages, 5398 KiB

Open AccessArticle

Comparative Study of Seafloor Topography Prediction from Gravity–Geologic Method and Analytical Algorithm

by Yuwei Tian, Huan Xu, Jinhai Yu, Qiuyu Wang, Yongjun Jia and Xin Chen

Remote Sens. 2024, 16(17), 3154; https://doi.org/10.3390/rs16173154 - 27 Aug 2024

Viewed by 760

Abstract

Seafloor topography prediction can fill in sea areas without ship sounding data. However, the dependence of various topographic prediction algorithms on ship soundings varies significantly. Hence, this study explores the impact of the number and distributions of ship soundings on topographic prediction using the gravity–geologic method (GGM) and an analytical algorithm. Firstly, this study investigates the influence of ship sounding coverage on the two algorithms. The simulation results demonstrate that increasing coverage from 5.40% to 31.80%, coupled with more uniform distributions across the study area, substantially reduces the RMS error of the GGM. Specifically, the RMS error decreases from 238.68 m to 42.90 m, an improvement of 82.03%. The analytical algorithm maintains a consistent RMS error of 40.39 m because it does not depend on ship soundings. Furthermore, we select a 1° × 1° sea area (134.8°–135.8°E, 30.0°–31.0°N), and the ship soundings are divided into two control groups, Part I and Part II, with coverages of 8.19% and 33.19%, respectively. When Part II is used for calculation, the RMS error of the GGM decreases from 204.17 m to 126.95 m compared to when Part I is used, while the analytical algorithm exhibits an RMS error of 167.94 m. The findings indicate that the prediction accuracy of the GGM is significantly affected by ship soundings, whereas the analytical algorithm is more stable and independent of ship soundings. Based on simulation experiments and realistic examples, when the effective ship soundings coverage exceeds 30%, the GGM may have more advantages. Conversely, the analytical algorithm may be better. This suggests that effectively combining and utilizing different algorithms based on the ship sounding coverage can improve the accuracy of topographic prediction. This will provide a basis for integrating multiple algorithms to construct a global seafloor topography model. Full article

(This article belongs to the Special Issue Remote Sensing in Space Geodesy and Cartography Methods (Third Edition))

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18 pages, 13835 KiB

Open AccessArticle

A New Combination Approach for Gibbs Phenomenon Suppression in Regional Validation of Global Gravity Field Model: A Case Study in North China

by Yingchun Shen, Wei Feng, Meng Yang, Min Zhong, Wei Tian, Yuhao Xiong and Zhongshan Jiang

Remote Sens. 2024, 16(15), 2756; https://doi.org/10.3390/rs16152756 - 28 Jul 2024

Viewed by 1046

Abstract

A global gravity field model (GGM) is essential to be validated with ground-based or airborne observational data for the accurate application of the GGM at a regional scale. Furthermore, accurately understanding the commission errors between the GGM and observational data are crucial for improving regional gravity fields. Taking the North China region as an example, to circumvent the omission errors, it is necessary to unify the spatial resolutions of the EIGEN-6C4 model and terrestrial gravity observational data to 110 km (determined by the distribution of gravity stations) by employing the spherical harmonic function for the EIGEN-6C4 model and the Slepian basis function for the gravity data, respectively. However, the application of spherical harmonic function expansions in the gravity model results in the Gibbs phenomenon, which may be a primary factor contributing to commission errors and impedes the accurate validation of the EIGEN-6C4 model with terrestrial gravity data. To effectively mitigate this issue, this study proposes a combination approach of window function filtering and regional eigenvalue constraint (based on the Slepian basis). Utilizing the EIGEN-6C4 gravity model to derive the gravity disturbance field at a resolution of 110 km (with spherical harmonic expansion up to the 180th degree and order), the combination approach effectively suppresses over 90% of high-degree (above the 120th degree) Gibbs phenomena. This approach also reduces signal leakage outside the region, thus enhancing the spatial accuracy of the regional gravity disturbance field. A subsequent comparison of the regional gravity disturbance field derived from the true model and terrestrial gravity data in North China indicates excellent consistency, with a root mean squared error (RMSE) of 0.80 mGal. This validation confirms that the combined approach of window function filtering and regional eigenvalue constraints effectively mitigates the Gibbs phenomenon and yields precise regional gravity fields. This approach is anticipated to significantly benefit scientific applications such as improving the accuracy of regional elevation benchmarks and accurately inverting the Earth’s internal structure. Full article

(This article belongs to the Special Issue Remote Sensing in Space Geodesy and Cartography Methods (Third Edition))

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15 pages, 7825 KiB

Open AccessTechnical Note

D-InSAR-Based Analysis of Slip Distribution and Coulomb Stress Implications from the 2024 M_w 7.01 Wushi Earthquake

by Yurong Ding, Xin Liu, Xiaofeng Dai, Gaoying Yin, Yang Yang and Jinyun Guo

Remote Sens. 2024, 16(22), 4319; https://doi.org/10.3390/rs16224319 - 19 Nov 2024

Viewed by 878

Abstract

On 23 January 2024, an M_w 7.01 earthquake struck the Wushi County, Xinjiang Uygur Autonomous Region, China. The occurrence of this earthquake provides an opportunity to gain a deeper understanding of the rupture behavior and tectonic activity of the fault system in the Tianshan seismic belt. The coseismic deformation field of the Wushi earthquake was derived from Sentinel-1A ascending and descending track data using Differential Interferometric Synthetic Aperture Radar (D-InSAR) technology. The findings reveal a maximum line-of-sight (LOS) displacement of 81.1 cm in the uplift direction and 16 cm in subsidence. Source parameters were determined using an elastic half-space dislocation model. The slip distribution on the fault plane for the M_w 7.01 Wushi earthquake was further refined through a coseismic slip model, and Coulomb stress changes on nearby faults were calculated to evaluate seismic hazards in surrounding areas. Results indicate that the coseismic rupture in the M_w 7.01 Wushi earthquake sequence was mainly characterized by left-lateral strike-slip motion. The peak fault slip was 3.2 m, with a strike of 228.34° and a dip of 61.80°, concentrated primarily at depths between 5 and 25 km. The focal depth is 13 km. This is consistent with findings reported by organizations like the United States Geological Survey (USGS). The fault rupture extended to the surface, consistent with field investigations by the Xinjiang Uygur Autonomous Region Earthquake Bureau. Coulomb stress results suggest that several fault zones, including the Kuokesale, Dashixia, Piqiang North, Karaitike, southeastern sections of the Wensu, northwestern sections of the Tuoergan, and the Maidan-Sayram Fault Zone, are within regions of stress loading. These areas show an increased risk of future seismic activity and warrant close monitoring. Full article

(This article belongs to the Special Issue Remote Sensing in Space Geodesy and Cartography Methods (Third Edition))

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