Submit to Special Issue Submit Abstract to Special Issue Review for Remote Sensing Propose a Special Issue

Journal Menu

Journal Browser

Special Issue "Remote Sensing in Space Geodesy and Cartography Methods II"

Special Issue Editors
Special Issue Information
Keywords
Published Papers

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: 29 February 2024 | Viewed by 3174

Share This Special Issue

Special Issue 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, Taipei, Taiwan
Interests: satellite geodesy; oceanography; theory of parameter estimation
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 broad research 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, better visualization of multisource data, and the construction of the 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 aims to 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 and planet; 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:

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 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

Published Papers (4 papers)

Download All Papers

Order results

Result details

Show export options Show export options

Select all

Export citation of selected articles as:

Research

Open AccessArticle

Spatial Development of Strong Storm-Induced Ionospheric Perturbations during 25–27 August 2018

and

Remote Sens. 2023, 15(10), 2549; https://doi.org/10.3390/rs15102549 - 12 May 2023

Viewed by 529

Abstract

The 25–27 August 2018 geomagnetic storm was the third largest storm in the 24th solar cycle. It was a surprising space event that originated from low-level solar activity. This study provides an overview of the temporal–spatial behaviors of plasma irregularities as functions of geographic longitude, latitude, and altitude using ground-based (GNSS receivers and ionosonde) instruments and space-borne Swarm satellites. The results not only reveal enhanced equatorial ionization anomaly (EIA) and hemispheric asymmetry over the Asian–Australian and American sectors at a particular time but also hemispheric asymmetric features of global ROT in the main and recovery phases. Additionally, this storm triggered positive plasma irregularities in altitudes of 100 to 150 km near the Auroral zone, and the changed ratio of bottom-side plasma irregularities exceeded 250%. This finding has been cross-validated by other instruments and models. Furthermore, the storm significantly affected the thermospheric O/N₂ density ratio, equatorial electrojet, and vertical E×B drifts. The equatorial and mid-latitude plasma irregularities may be a combined action of thermospheric composition change, equatorial electrojet, and vertical E×B drifts. Finally, the storm induced positive Joule heating irregularities in the Auroral ionosphere in altitudes of 100 to 400 km with a maximum changed ratio of over 200%, as well as enhanced cross-Polar voltage to ~90 kv. The Polar ionospheric irregularities may be associated with additional energy input through particle precipitation, Joule heating, and ionospheric current intensification. Full article

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

► Show Figures

Figure 1

Open AccessCommunication

A Double-Adaptive Adjustment Algorithm for Ionospheric Tomography

and

Remote Sens. 2023, 15(9), 2307; https://doi.org/10.3390/rs15092307 - 27 Apr 2023

Cited by 1 | Viewed by 480

Abstract

A double-adaptive adjustment algorithm (DAAA) is proposed to reconstruct three-dimensional ionospheric electron density (IED) distribution. In the DAAA method, the relaxation factor of the multiplicative algebraic reconstruction technique (MART) is first adaptively adjusted by introducing adaptive MART (AMART). To avoid the voxels without any rays traversing them becoming dependent on the initial IED values, smoothing constraints are generally imposed on the adaptive multiplicative algebraic reconstruction technique (AMART). In general, the elements of the smoothing matrices are invariant in the iterative process. They affect the accuracy and efficiency of the IED inversion. To overcome the above limitation, the adaptive adjustments of the constrained matrix elements are subsequently carried out. Both numerical simulation and actual global navigation satellite system (GNSS) experimental results validate that the accuracy and efficiency of ionospheric tomography have been improved by the DAAA method. Finally, the new algorithm is applied to reconstruct the three-dimensional structure of the ionosphere during different geomagnetic activities. The comparisons show that the vertical profiles of the DAAA method are in agreement with those recorded from the ionosonde, and the inverted vertical total electron content (VTEC) of the DAAA method also agrees with the ionospheric products of center for orbit determination in Europe (CODE) during geomagnetic quiet and geomagnetic storms. The comparisons confirm the reliability and superiority of the DAAA method. Full article

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

► Show Figures

Figure 1

Open AccessArticle

Improving the Detection Accuracy of Underwater Obstacles Based on a Novel Combined Method of Support Vector Regression and Gravity Gradient

and

Remote Sens. 2023, 15(8), 2188; https://doi.org/10.3390/rs15082188 - 20 Apr 2023

Viewed by 1017

Abstract

Underwater gravity gradient detection techniques are conducive to ensuring the safety of submersible sailing. In order to improve the accuracy of underwater obstacle detection based on gravity gradient detection technology, this paper studies the gravity gradient underwater obstacle detection method based on the combined support vector regression (SVR) algorithm. First, the gravity gradient difference ratio (GGDR) equation, which is only related to the obstacle’s position, is obtained based on the gravity gradient equation by using the difference and ratio methods. Aiming at solving the shortcomings of the GGDR equation based on Newton–Raphson method (NRM), combined with SVR algorithm, a novel SVR–gravity gradient joint method (SGJM) is proposed. Second, the differential ratio dataset is constructed by simulating the gravity gradient data generated by obstacles, and the obstacle location model is trained using SVR. Four measuring lines were selected to verify the SVR-based positioning model. The verification results show that the mean absolute error of the new method in the x, y, and z directions is less than 5.39 m, the root-mean-square error is less than 7.58 m, and the relative error is less than 4% at a distance of less than 500 m. These evaluation metrics validate the reliability of the novel SGJM-based detection of underwater obstacles. Third, comparative experiments based on the novel SGJM and traditional NRM were carried out. The experimental results show that the positioning accuracy of x and z directions in the obstacle’s position calculation based on the novel SGJM is improved by 88% and 85%, respectively. Full article

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

► Show Figures

Figure 1

Open AccessArticle

Study on the Variations in Water Storage in Lake Qinghai Based on Multi-Source Satellite Data

and

Remote Sens. 2023, 15(7), 1746; https://doi.org/10.3390/rs15071746 - 24 Mar 2023

Viewed by 708

Abstract

Performing research on the variation in lake water on the Qinghai–Tibet Plateau (QTP) can give the area’s ecological environmental preservation a scientific foundation. In this paper, we first created a high-precision dataset of lake water level variation every 10 days, from July 2002 to December 2022, using multi-source altimetry satellite SGDR data (Envisat RA-2, SARAL, Jason-1/2, and Sentinel-3A/3B SRAL), which integrated the methods of atmospheric path delay correction, waveform re-tracking, outlier detection, position reduction using a height difference model, and inter-satellite deviation adjustment. Then, using Landsat-5 Thematic Mapper, Landsat-7 Enhanced Thematic Mapper, and Landsat 8 Operational Land Imager data, an averaged area series of Lake Qinghai (LQ) from September to November, each year from 2002 to 2019, was produced. The functional connection between the water level and the area was determined by fitting the water level–area series data, and the lake area time series, of LQ. Using the high-precision lake water level series, the fitted lake surface area time series, and the water storage variation equation, the water storage variation time series of LQ was thus calculated every 10 days, from July 2002 to December 2022. When the hydrological gauge data from the Xiashe station and data from the worldwide inland lake water level database are used as references, the standard deviations of the LQ water level time series are 0.0676 m and 0.1201 m, respectively. The results show that the water storage of LQ increases by 11.022 × 10⁹ m³ from July 2002 to December 2022, with a growth rate of 5.3766 × 10⁸ m³/a. The growth rate from January 2005 to January 2015 is 4.4850 × 10⁸ m³/a, and from January 2015 to December 2022, the growth rate is 8.9206 × 10⁸ m³/a. Therefore, the increased rate of water storage in LQ over the last 8 years has been substantially higher than in the previous 10 years. Full article

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

► Show Figures

Journal Menu

Journal Browser

Special Issue "Remote Sensing in Space Geodesy and Cartography Methods II"

Share This Special Issue

Special Issue Editors

Special Issue Information

Keywords

Published Papers (4 papers)

Research

Further Information

Guidelines

MDPI Initiatives

Follow MDPI