remotesensing-logo

Journal Browser

Journal Browser

State of the Art of GNSS and SAR/InSAR Techniques for Geomatic Applications

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Remote Sensing in Geology, Geomorphology and Hydrology".

Deadline for manuscript submissions: 31 August 2025 | Viewed by 2538

Special Issue Editors


E-Mail Website
Guest Editor
Istituto Nazionale di Geofisica e Vulcanologia, Osservatorio Vesuviano, 80124 Napoli, Italy
Interests: GNSS; remote sensing; geomatics; faulting; deformation

Special Issue Information

Dear Colleagues,

Modern remote sensing and space geodetic technologies, as important tools for earth observation and characterization, provide continuous, spatial-scale data sets, making high-resolution mapping possible at different spatio-temporal scales. In particular, synthetic aperture radar (SAR) and global satellite navigation system (GNSS) are powerful means to study the physical processes and interactions of geomorphic dynamics at different spatial scales.

Synthetic aperture radar (SAR), as an all-weather sensor, can work continuously day and night. SAR interferometry (InSAR) is a commonly used technique to quantify the ground motion processes using phase information. At the same time, with the continuous advancement of feature extraction technologies such as machine learning/deep learning models, data mining, and fusion, it is gradually being widely used in the study of mapping dynamics.

We are pleased to announce a new Special Issue on remote sensing. Research topics include, but are not limited to, the following:

  • Earth observation using GNSS time series in near real-time;
  • Processing and analysis methods using InSAR data;
  • New data processing algorithms and programs based on SAR data;
  • Integration and fusion of multi-source data;
  • Measurements combined with accurate geographic information systems;
  • Subsurface and surface deformation/subsidence dynamics;
  • Dynamic changes in fault/crustal trajectories and geometry;
  • Physical processes at different time and space scales before and after geological disasters;
  • Risk avoidance research on geological disasters such as landslides, earthquakes, and volcanic activities;
  • Mapping applications of GNSS/SAR combined with advanced artificial intelligence technology.

Dr. Claudia Pipitone
Prof. Dr. Gino Dardanelli
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

  • geomatic applications
  • SAR/InSAR
  • GNSS time series
  • deformation analysis
  • fault/crustal property
  • active tectonics
  • multi-source data integration
  • seismic activities
  • stability modeling
  • time series analysis
  • landslides
  • hazard mapping

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • Reprint: MDPI Books provides the opportunity to republish successful Special Issues in book format, both online and in print.

Further information on MDPI's Special Issue policies can be found here.

Published Papers (2 papers)

Order results
Result details
Select all
Export citation of selected articles as:

Research

Jump to: Review

38 pages, 13454 KiB  
Article
Deep Learning Innovations: ResNet Applied to SAR and Sentinel-2 Imagery
by Giuliana Bilotta, Luigi Bibbò, Giuseppe M. Meduri, Emanuela Genovese and Vincenzo Barrile
Remote Sens. 2025, 17(12), 1961; https://doi.org/10.3390/rs17121961 - 6 Jun 2025
Viewed by 189
Abstract
The elevated precision of data regarding the Earth’s surface, facilitated by the enhanced interoperability among various GNSSs (Global Navigation Satellite Systems), enables the classification of land use and land cover (LULC) via satellites equipped with optical sensors, such as Sentinel-2 of the Copernicus [...] Read more.
The elevated precision of data regarding the Earth’s surface, facilitated by the enhanced interoperability among various GNSSs (Global Navigation Satellite Systems), enables the classification of land use and land cover (LULC) via satellites equipped with optical sensors, such as Sentinel-2 of the Copernicus program, which is crucial for land use management and environmental planning. Likewise, data from SAR satellites, such Copernicus’ Sentinel-1 and Jaxa’s ALOS PALSAR, provide diverse environmental investigations, allowing different types of spatial information to be analysed thanks to the particular features of analysis based on radar. Nonetheless, in optical satellites, the relatively low resolution of Sentinel-2 satellites may impede the precision of supervised AI classifiers, crucial for ongoing land use monitoring, especially during the training phase, which can be expensive due to the requirement for advanced technology and extensive training datasets. This project aims to develop an AI classifier utilising high-resolution training data and the resilient architecture of ResNet, in conjunction with the Remote Sensing Image Classification Benchmark (RSI-CB128). ResNet, noted for its deep residual learning capabilities, significantly enhances the classifier’s proficiency in identifying intricate patterns and features from high-resolution images. A test dataset derived from Sentinel-2 raster images is utilised to evaluate the effectiveness of the neural network (NN). Our goals are to thoroughly assess and confirm the efficacy of an AI classifier utilised on high-resolution Sentinel-2 photos. The findings indicate substantial enhancements compared to current classification methods, such as U-Net, Vision Transformer (ViT), and OBIA, underscoring ResNet’s transformative capacity to elevate the precision of land use classification. Full article
Show Figures

Figure 1

Review

Jump to: Research

23 pages, 10008 KiB  
Review
Multi-Global Navigation Satellite System for Earth Observation: Recent Developments and New Progress
by Shuanggen Jin, Xuyang Meng, Gino Dardanelli and Yunlong Zhu
Remote Sens. 2024, 16(24), 4800; https://doi.org/10.3390/rs16244800 - 23 Dec 2024
Viewed by 1699
Abstract
The Global Navigation Satellite System (GNSS) has made important progress in Earth observation and applications. With the successful design of the BeiDou Navigation Satellite System (BDS), four global navigation satellite systems are available worldwide, together with Galileo, GLONASS, and GPS. These systems have [...] Read more.
The Global Navigation Satellite System (GNSS) has made important progress in Earth observation and applications. With the successful design of the BeiDou Navigation Satellite System (BDS), four global navigation satellite systems are available worldwide, together with Galileo, GLONASS, and GPS. These systems have been widely employed in positioning, navigation, and timing (PNT). Furthermore, GNSS refraction, reflection, and scattering signals can remotely sense the Earth’s surface and atmosphere with powerful implications for environmental remote sensing. In this paper, the recent developments and new application progress of multi-GNSS in Earth observation are presented and reviewed, including the methods of BDS/GNSS for Earth observations, GNSS navigation and positioning performance (e.g., GNSS-PPP and GNSS-NRTK), GNSS ionospheric modelling and space weather monitoring, GNSS meteorology, and GNSS-reflectometry and its applications. For instance, the static Precise Point Positioning (PPP) precision of most MGEX stations was improved by 35.1%, 18.7%, and 8.7% in the east, north, and upward directions, respectively, with PPP ambiguity resolution (AR) based on factor graph optimization. A two-layer ionospheric model was constructed using IGS station data through three-dimensional ionospheric model constraints and TEC accuracy was increased by about 20–27% with the GIM model. Ten-minute water level change with centimeter-level accuracy was estimated with ground-based multiple GNSS-R data based on a weighted iterative least-squares method. Furthermore, a cyclone and its positions were detected by utilizing the GNSS-reflectometry from the space-borne Cyclone GNSS (CYGNSS) mission. Over the years, GNSS has become a dominant technology among Earth observation with powerful applications, not only for conventional positioning, navigation and timing techniques, but also for integrated remote sensing solutions, such as monitoring typhoons, river water level changes, geological geohazard warnings, low-altitude UAV navigation, etc., due to its high performance, low cost, all time and all weather. Full article
Show Figures

Graphical abstract

Back to TopTop