High-precision Global Navigation Satellite System (GNSS) observations in Antarctica play an important role in monitoring bedrock deformation, which comprises the viscoelastic response to past ice-load changes (Glacial Isostatic Adjustment, GIA) and the elastic response to present-day ice-mass change. Although multi-GNSS constellations are commonly evaluated collectively, the influence of constellation-specific orbital configurations and signal architectures under extreme polar conditions remains insufficiently characterized. Using observations from seven Antarctic IGS stations (PALM, SCTB, DUMG, CAS1, DAV1, MAW1, and SYOG) spanning 2019-2025, the performance of the Galileo and the BeiDou Navigation Satellite System (BDS) constellations was investigated with respect to orbital geometry, multipath behavior, inter-system bias (ISB) variability, and Precise Point Positioning (PPP) convergence characteristics. Polar skyplot analyses indicated that BDS geostationary (GEO) and inclined geosynchronous orbit (IGSO) satellites remain predominantly below 15 degrees elevation at Antarctic latitudes, contributing disproportionately to low-elevation observation density and elevated multipath susceptibility. When GEO/IGSO observations were excluded, the BDS medium Earth orbit (MEO) sub-constellation exhibited positioning behavior broadly comparable to Galileo's predominantly MEO-based architecture. During austral summer periods, Galileo E5 observations exhibited lower sensitivity to seasonal firn-related reflectivity changes compared to BDS B2a, consistent with the expected robustness of the wideband Alternative Binary Offset Carrier (AltBOC) modulation. Wintertime temperature minima below -50 degrees C were associated with seasonally varying ISB patterns exhibiting apparent lag behavior on the order of several weeks, although the underlying physical mechanisms require further investigation. Static PPP analyses further indicated that multi-GNSS solutions using GPS+GLONASS+Galileo + BDS-MEO achieved shorter median convergence times than standalone Galileo or BDS-ALL solutions under both geomagnetically quiet and elevated solar activity conditions. In addition, MEO-filtered multi-GNSS processing yielded lower vertical velocity uncertainties than BDS-ALL solutions. These findings suggest that constellation-aware processing strategies may improve positioning stability and velocity estimation performance for Antarctic GNSS applications relative to conventional all-in-view approaches.
The rapid global expansion of offshore wind power has created an urgent demand for efficient methods to map the deployment scale of offshore wind turbines (OWTs). Synthetic Aperture Radar (SAR) is well suited to this task due to its wide spatial coverage and frequent revisit capability. However, most existing SAR-based detection methods rely on multi-temporal image stacking to suppress dynamic vessel interference or data-intensive deep learning workflows requiring substantial annotated training data and cloud-computing resources. These dependencies introduce update latencies ranging from months to a year. In this study, we propose a practical method for detecting OWTs from a single SAR image by integrating morphological features and spatial distribution analysis. The method combines adaptive target extraction, morphological filtering, and spatial statistical analysis to identify regularly spaced turbine clusters and derive their geographic coordinates. Case studies in the southern Shandong Peninsula, Jiangsu coast, and German Bight demonstrate that the proposed method achieves reliable detection performance across diverse marine environments. Rather than replacing high-accuracy centralized global datasets or multi-temporal deep learning systems, the proposed method serves as a lightweight alternative strategy, offering a practical solution for timely and on-demand OWT inventory updating, offshore engineering site assessment, and maritime navigation safety management.
Persistent coastal siltation at port entrances increases dredging demand and threatens navigation safety, while bathymetric surveys remain costly for decadal assessment. This study presents a tide-aware Synthetic Aperture Radar (SAR) framework for quantifying siltation evolution in the northern sector of Taichung Port, Taiwan, using 276 Sentinel-1 ascending-track VV images acquired from 2015 to 2024. The ascending VV configuration was selected based on sample-area ocean-siltation separability, and all images were processed using a standardized radiometric and geometric workflow. Siltation boundaries were delineated using an Active Contour Model to extract continuous water-siltation interfaces under speckled, diffuse-backscatter conditions without training data. Among the archive, 82 convergent images were retained and grouped into six tide-gauge-based tidal-height classes. Tide-normalized results show persistent expansion across all tidal groups, with regression-based annual increases of 0.051-0.074 km2/yr. Endpoint-based rates of 0.047-0.075 km2/yr were consistent with the fitted slopes. Under comparable low-tide conditions, the mapped area increased from 1.722 km2 in 2016 to 2.215 km2 in 2024, yielding a net expansion of 0.493 km2. Independent optical aerial photos showed consistent directional expansion, with paired optical/SAR areas of 1.063/1.197, 1.533/1.503, and 2.231/2.147 km2 in 2016, 2023, and 2024, respectively. These results support quantitative siltation assessment and port maintenance planning.
The geodetic facilities at Corsica, which were initially developed for the purpose of monitoring the performance of nadir satellite altimeters, have been adapted to calibrate successive satellite altimeters in an absolute sense. In anticipation of SWOT, a preliminary phase of extension of the reference surfaces of the Corsica site was executed in June 2021, followed by a subsequent phase in May 2022. To further refine the along-track resolution of the nadir altimetry satellites, additional surveys were conducted in 2023, 2024, and 2025, focusing on the ground tracks of historical satellites. The measurements were carried out using the instruments developed by DT-INSU (CalNaGeo and Cyclop & eacute;e), which demonstrated a centimeter level consistency. A thorough analysis of GNSS processing employing various methodologies has been conducted, including differential and Precise Point Positioning approaches with the use of the GPS and Galileo constellations. This analysis underscores the considerable potential of Precise Point Positioning. The subsequent sections present the various stages of processing the GNSS reference surface derived from the aforementioned surveys. It is demonstrated that the GNSS reference surface ultimately exhibits a precision of a few millimeters. Preliminary results demonstrate the high potential of the Corsica facilities to provide insight into the SWOT measurement precision.
