Search Results (579)

In Global Navigation Satellite System (GNSS)-denied deep-sea environments, traditional scalar gravity matching navigation methods frequently suffer severe performance degradation in weak-feature, highly repetitive gravity anomaly regions. Inspired by the hippocampal spatial memory mechanism and natural graded foraging behavior of benthic marine organisms, this paper proposes a full-chain bionic framework named the Physics-Consistent Multi-Scale Adaptive Particle Filter for Gravity Matching Navigation (PC-MAPF-GM). This method endows the particle filter with four layers of biologically mimicked autonomous regulation capabilities: quantitative gravity field local suitability assessment, dynamically adjusted time-varying search scope, three-level multi-scale stepwise matching, and along-track trajectory motion physics consistency constraint. The verification of long-term shipborne lake experiments confirms that the proposed method reduces the final gravity matching positioning root mean square error (RMSE) to only 528.2 m, which is more than 41% lower than the classical terrain contour matching (TERCOM) benchmark and 31% lower than iterative closest contour point (ICCP). This biomimetic full-design-chain solution provides a robust new practical navigation paradigm for long-endurance fully autonomous underwater vehicles operating without any external auxiliary positioning information. Full article

Ukraine entered the definitive period of the EU Carbon Border Adjustment Mechanism (CBAM) in January 2026 as the largest exporter of CBAM-covered goods to the EU by physical volume, while its industrial base remains under direct wartime pressure. This study provides the first structural analysis of the open microaggregated dataset of the State Statistics Service of Ukraine (SSSU) on air pollutant and greenhouse gas emissions, covering 1990–2025 across 1284 territorial units, 128 substances, and 605 economic activities (NACE/KVED-2010). A documented harmonization procedure is proposed that resolves the 2020/2021 dimensional break and the ambiguity between oblast (region)- and hromada (municipality)-level records, yielding consistent 36-year series with independent national total validation for 2015–2025. Four phases are identified: transformational decline (1990–1999, −56.5%), stabilization (1999–2013, +4.6%), post-2014 structural decline (2013–2021, −47.9%), and the full-scale war shock (2021–2025, −55.0%). Stationary source emissions fell by 89.3% overall, but the wartime reduction reflects destruction and occupation of capacity, not decarbonization, as reflected in the collapse of metallurgy (−73.8%) and coke production (−89.6%) and the loss of the Mariupol district from statistical coverage after 2022. Mobile sources now supply 65% of the national total. Coal mine methane dominates stationary CH₄ (301 kt in 2021; ≈9.0 Mt CO₂ eq), directly relevant to Regulation (EU) 2024/1787. The regional Herfindahl–Hirschman index fell from 1847 (2021) to 1524 (2025), indicating war-driven regional deconcentration and a westward shift in the emission center of gravity. The findings are validated against independent satellite-based and conflict attribution estimates, and implications for monitoring, reporting and verification (MRV) infrastructure, CBAM default value exposure, and the phased design of Ukraine’s emissions trading system are derived. Full article

Extreme weather events increasingly affect the safety, durability, and operational performance of road infrastructure, creating the need for sustainable thermal management solutions. Among the available technologies, low-enthalpy geothermal systems offer significant advantages by providing continuous heating and cooling capabilities with reduced environmental impact compared to conventional maintenance practices. This study presents the methodology developed within the GEO-ROAD project to assess shallow geothermal resources across Spain and support the future deployment of geothermal road systems. The proposed framework integrates geological, thermal, and satellite-derived geophysical information through a unified GIS-based workflow, combining multivariate statistical analysis, map algebra, and automated geospatial processing to generate a regional geothermal potential model. In addition to conventional geological characterization, the methodology incorporates magnetic and gravity data from satellite missions, airborne surveys, and ground-based observations to improve the spatial representation of subsurface conditions. The resulting geothermal potential assessment constitutes a key component of the GEO-ROAD digital platform, where it will be combined with climatic risk maps and road infrastructure information to identify the most suitable locations for geothermal applications. By linking geothermal resource assessment with infrastructure-oriented decision-making, the proposed methodology provides a scalable and transferable framework for supporting the planning of sustainable and climate-resilient road thermal management systems. Full article

As the largest inland river basin in China’s extremely arid region, the stability of the groundwater–vegetatifon system in the Tarim River Basin is crucial for the consolidation of the ecological security barrier in the northwest. To reveal the evolution law of groundwater storage in the watershed from 2003 to 2024 and its response mechanism to vegetation dynamics, this study is based on GRACE gravity satellite, GLDAS land surface assimilation and MODIS remote sensing data. The Theil Sen trend analysis, Hurst index, spatiotemporal Granger causality test, and standardized multiple linear regression model are integrated to systematically analyze the spatiotemporal heterogeneity, future evolution trend, and multi-driving factor contribution pattern of groundwater storage (GWSA) in the watershed. The results showed that: (1) During the study period, the GWSA of the watershed showed a significant downward trend, with a rate of −3.5 mm/a, and experienced a spatial redistribution process of “comprehensive loss local recovery southern compensation northern loss”. The northern and peripheral regions faced new depletion risks. (2) The vegetation condition continues to improve, and the VCI gradually rises from the low to medium range, but the spatial heterogeneity increases synchronously; there is a significant spatial positive correlation between VCI and GWSA, with only a strong lag driving effect in the southwestern region (F > 40). The explanatory power of vegetation factors for groundwater in other regions is limited. (3) Future trend predictions show that over 70% of the region will continue in the direction of historical changes, and the continuous loss trend in the north is difficult to reverse. (4) There is significant spatial differentiation in the contribution rate of driving factors: vegetation conditions (VCI) are the dominant factor, controlling 57.53% of the watershed edge and eastern region; precipitation and temperature dominate the central region (24.94%) and southwestern desert areas (17.53%), respectively. The research results can provide scientific basis for differentiated ecological water delivery and refined management of water resources in the Tarim River Basin. Full article

Intensive groundwater exploitation in the Wei River Basin (WRB) has caused severe depletion. While Gravity Recovery and Climate Experiment (GRACE) satellites monitor these changes, their coarse resolution fails to account for soil erosion-induced mass loss on the Loess Plateau limit basin-scale accuracy. To address this, we developed the groundwater storage model to dynamically downscale GRACE data to the resolution of 0.05° grid. This physically based model integrates Darcy’s law, water-balance principles, and an innovative correction for soil erosion mass migration. Validated against well data with maximum correlative coefficient of 0.73, the model reveals a severe groundwater decline of 55.89 × 10⁸ m³/year from 2003 to 2023. The high-resolution results successfully capture localized over-extraction hotspots in the Guanzhong Plain, showing a west-to-east decreasing gradient in groundwater storage along the Wei River channel. Furthermore, quantitative analysis indicates that human activities, including primarily agricultural and urban extraction, are the overwhelming drivers, accounting for over 80% of storage depletion. This framework provides a robust methodological reference for isolating groundwater signals in erosion-prone regions and supports refined water management in semi-arid basins. Full article

Backpack and handheld LiDAR simultaneous localization and mapping (SLAM) systems have become an important solution for large-scale 3D data acquisition. Since Global Navigation Satellite System (GNSS) positioning is not always available in many LiDAR SLAM systems, point clouds acquired from different surveying projects or devices are represented in independent local coordinate systems and require coarse registration to fuse all data into a unified coordinate system. Existing coarse registration approaches based on local feature descriptors often depend on locally estimated surface normals or reference directions, whose repeatability can be affected by measurement noise and non-uniform sampling. To address this issue, this paper proposes a Global-Prior Augmented Fast Point Feature Histogram (GA-FPFH) descriptor. The proposed method constructs a Z-axis-augmented local reference frame (Z-LRF) using the gravity-aligned vertical direction provided by the SLAM system. Three new geometric components are proposed based on the Z-LRF and combined with conventional FPFH features to form a six-component and 66-dimensional descriptor. Experiments on 12 real-world point-cloud pairs show that GA-FPFH increases the inlier ratio by 26.9–148.9% and, across five registration algorithms, reduces the rotation error, translation error, and RMSE by 31.5–87.9%, 29.6–97.8%, and 42.4–97.6%, respectively, while increasing the overall registration success rate from 71.7% to 88.3%. The significant error reductions are partly attributable to the higher registration success rate and fewer failure cases. Full article

Identifying favourable zones for geothermal exploration at the regional scale remains challenging, particularly in areas where conventional geophysical surveys are spatially limited or economically unfeasible. This study presents an integrated framework for delineating geothermal favourability across the Iberian Peninsula using global gravity and magnetic products combined with subsurface thermal information. EGM2008, WGM2012, EMAG2, and WDMAM2 were compared and harmonized through geostatistical modelling, anisotropic ordinary kriging, and common-grid processing. Potential-field transformations and spectral coherence analysis were used to derive a Geophysical Favourability Index (FI_geof). This index was integrated with temperature at 100 m depth using weighted fuzzy logic, applying FuzzyLinear and FuzzyLarge membership functions with a 60% FI_geof and 40% temperature weighting, to obtain the Geothermal Favourability Index (FI_geot). Quantitative comparison and cross-validation indicated that EGM2008 and EMAG2 were the most suitable primary reference products within their respective datasets, whereas WGM2012 and WDMAM2 provided complementary regional-scale information. The fuzzy integration identified the highest favourability mainly in Galicia and the Levante–Betic sector, where elevated FI_geot values coincide with heat-flow values of approximately 96–154 mW m⁻² and comparatively high geothermal gradients. Around 20% of the study area was classified within the highest favourability category. The resulting FI_geot should be interpreted as a regional screening and prioritization tool rather than as direct evidence of an exploitable geothermal resource. Overall, the proposed methodology provides a reproducible approach for identifying priority areas for further geothermal investigation in large and incompletely characterized regions. Full article

Groundwater-storage anomalies (GWSA) derived from the Gravity Recovery and Climate Experiment (GRACE) mission provide valuable information for regional groundwater monitoring. Improving the spatial representation and temporal continuity of GRACE-derived GWSA is important for supporting groundwater assessment at subregional scales. A sequential framework combining Gaussian Process (GP) temporal gap filling and Random Forest (RF) spatial downscaling was developed for GWSA reconstruction in Henan Province, China, during 2002–2022. The GP model was used to reconstruct missing observations and characterize temporal variations, while the RF model statistically redistributed the GRACE-based GWSA signal using multi-source hydroclimatic predictors. The resulting dataset comprises model-derived GWSA estimates on a 1 km output grid constrained by the coarse spatial support of GRACE observations and the relationships learned from the auxiliary variables. Therefore, the 1 km grid spacing should not be interpreted as an independent 1 km resolving capability for groundwater-storage variations. Agreement with the parent GRACE-based GWSA product was used to assess coarse-scale reconstruction consistency rather than independent fine-scale accuracy. Comparison with groundwater-level anomalies from 63 monitoring wells yielded a correlation coefficient of 0.88, indicating temporal agreement at the sampled locations. Because the groundwater-level observations were not converted into storage anomalies using specific yield, this comparison does not establish absolute GWSA accuracy or independently validate the model-derived fine-scale spatial patterns. The reconstructed estimates revealed pronounced spatial heterogeneity in groundwater-storage changes, with persistent depletion concentrated in northern Henan, where groundwater decline rates exceeded 20 mm yr⁻¹. Overall, the framework improved the temporal continuity and spatial representation of GRACE-based groundwater-storage estimates while retaining the fundamental spatial constraints of satellite gravimetry. The results demonstrate the potential of integrating GRACE observations, machine learning, and multi-source Earth observation data to support regional groundwater assessment. Full article

Terrestrial water storage (TWS) is a key parameter for understanding regional water cycles and climate change. To address the low spatial resolution and temporal gaps of Gravity Recovery and Climate Experiment (GRACE) and its successor satellites (GRACE Follow-On) data, as well as the uneven spatial distribution of Global Navigation Satellite System (GNSS) stations, this study integrates GNSS vertical deformation with GRACE/GFO Mascon data to jointly invert and conduct an in-depth analysis of TWS changes and hydrological drought characteristics in three central Chinese provinces (Hubei, Hunan, and Jiangxi) from January 2011 to June 2023. For missing parts of GRACE and GNSS data, different methods were effectively employed to fill the gaps. The optimal weighting factors were then determined using the Akaike Bayesian Information Criterion (ABIC), leading to the inversion of TWS variations. Combined with hydrometeorological data (precipitation, evapotranspiration, and runoff), drought monitoring was further conducted. The results indicate that joint inversion effectively integrates the high-frequency spatial signals of GNSS with the large-scale smoothing features of GRACE. The spatial distribution of the annual TWS amplitude obtained from different methods (GRACE, GNSS-Green, GNSS-Slepian, and Joint) showed high consistency, generally exhibiting a pattern of lower values in the northwest and higher values in the southeast. Using the TWS derived from joint inversion, a drought index (Joint-DSI) was constructed, successfully identifying and tracking seven major drought events in the study area. Among these, the drought from April 2017 to November 2018 lasted the longest (20 months), while the event from August 2022 to June 2023 was the most severe, with a peak deficit of 142.303 km³. This study demonstrates that the joint inversion method can effectively overcome the spatiotemporal limitations of single observation techniques, providing a high-precision, high-resolution, and reliable geodetic approach for regional water resource management and extreme drought monitoring. Full article

The gravity navigation reference map is a foundational element of gravity matching-aided navigation systems, as it directly determines positioning accuracy and overall navigation performance. To improve fused gravity anomalies and reduce reliance on manually selected parameters, this study proposes an adaptive multi-scale frequency-domain reconstruction (AMFR) algorithm. Specifically, the target ocean covered by multi-source satellite gravity data is divided into multiple scales, and distinct fusion parameters are assigned according to the characteristics of multi-source gravity data in different sea areas to enhance the accuracy of the fused gravity navigation reference map. Seven fusion schemes with different filtering diameters and weighting strategies are designed for comparative analysis. We evaluate the algorithm’s performance using measured gravity data with varying spatial distributions from the South China Sea and the Western Pacific Ocean, employing both RMS comparison and matching positioning experiments. Experimental results demonstrate that the RMS of the gravity navigation reference map constructed by the proposed AMFR algorithm is reduced by 30.4%, and the matching positioning accuracy is improved by 23.4%. The AMFR algorithm effectively enhances the precision of the gravity navigation reference map and improves the navigation performance of the gravity matching-aided navigation system. Full article

Height systems form a mathematical interface between physical geodesy, engineering surveying, and digital cartography. Although satellite positioning efficiently provides ellipsoidal heights, practical infrastructure, mapping, hydrological, and monitoring tasks require gravity-related heights that are compatible with national vertical datums. This paper develops a denominator-based framework in which dynamic, orthometric, and normal heights are interpreted as metric realizations of a common geopotential number. Starting from the line-integral definition of geopotential, the principal height formulae are derived; first-order sensitivities to geoid undulation, height anomaly, and mean gravity are established; and uncertainty propagation is analyzed. A Romania-oriented computational experiment, explicitly defined as a representative model-behavior study rather than an official national adjustment, uses lowland, plateau, and mountain-influenced settings consistent with the Constanta and Black Sea 1975 normal-height context. The results show that modeled normal-orthometric separations remain below 3 mm in representative low-relief locations but increase to 17.1 mm in Suceava, 29.5 mm in Cluj-Napoca, and 85.6 mm in the mountain-influenced Brasov case. The dynamic-normal differences remain small at low elevations but become systematic where the normal-gravity denominator departs from the selected reference value. The Monte Carlo experiment indicates standard uncertainties of approximately 4.2–4.4 cm for normal heights when a 1.5 cm ellipsoidal-height uncertainty and a 4.0 cm quasi-geoid uncertainty are assumed. A single-point covariance example gives 31.7 mm for normal-height conversion and 36.9 mm for orthometric-height conversion under the stated correlation assumptions. The transformation-surface comparison further shows that a quadratic local model reduces leave-one-out cross-validation error from 16.73 mm to 9.95 mm relative to a planar model in the synthetic Romania-oriented scenario. The study concludes that the height-system label must be treated as part of the mathematical model and metadata, and it proposes a geopotential-centered computational pathway for survey adjustment, uncertainty control, and metadata-safe geospatial export. Full article

Our research explores the sensitivity of satellite constellations to fluctuations in the quantum gravitational field, with the aim of quantifying their potential impact on critical operations and precision measurement. The main objective is to quantify the potential impact of hypothetical quantum effects on the precise orbital dynamics of satellite constellations. The methods employed will involve the development of a sophisticated computational model using the quantum toolbox QuTIP in Python. Our model will simulate the trajectories of various satellite constellation configurations in two distinct gravitational frameworks: one based on classical general relativity and the other incorporating theoretical models of quantum gravitational fluctuations. The main task is to meticulously analyze and compare the resulting differences in key orbital parameters, including position, velocity, and orbital period, between these two scenarios. This comparative analysis is crucial in determining whether the minute stochastic perturbations resulting from quantum gravity could accumulate over time and measurably affect the performance and objectives of current and future high-precision satellite missions, such as those related to Earth observation, global navigation satellite systems (GNSSs), or space-based gravitational wave detectors. The expected results have provided essential insights into the potential need to integrate quantum gravitational corrections into very high-precision astrodynamics and will contribute significantly to ongoing theoretical and experimental efforts to unify quantum mechanics and general relativity at the macroscopic scale. Full article

Composite environmental risks accumulate unevenly along urban–rural gradients, yet the conditional and nonlinear interaction between built environment quality (BEQ) and urban–rural functional connectivity (URFC) remains poorly quantified at fine resolution. This study aims to determine whether, and under what conditions, BEQ moderates the relationship between URFC and a population-weighted composite risk index (CRI), and to translate the result into spatia targeted green-infrastructure priorities. We use 744,714 grid cells at 100 m resolution over Guangzhou, China. The framework couples entropy-weighted BEQ from satellite and street-view imagery, gravity-model URFC computed on the real road network, and a two-stage population-weighted CRI of heat and air hazards. We apply nested ordinary least squares with incremental F-tests, spatial-lag and spatial-error models, generalised additive models with B-spline bases, gradient-boosted trees with SHAP interaction values, and Baron–Kenny mediation analysis. The main BEQ × URFC estimates are negative across the parametric and machine-learning specifications. The interaction is, however, small: a spatial-lag model on a 10,000-cell subsample returns β = −5.4 × 10⁻⁴, but a scalable generalised-method-of-moments spatial regression on the full grid—where the spatial autoregressive coefficient reaches ρ ≈ 0.99—shows the coefficient to be negative yet not statistically significant, and a five-seed re-estimation confirms that the subsample-based significance is draw-dependent. We therefore interpret the buffering as directionally supported but small and not robustly significant once spatial autocorrelation is fully modelled. The buffering response is nonlinear in the GAM main effects, and BEQ buffers across the entire observed connectivity range rather than switching sign at an interior threshold; URFC functions predominantly as a moderator rather than a mediator. Population-stratified estimation shows that the buffering is exposure-conditional: it is strongest where population exposure is high and weakens or reverses in sparsely populated cells, consistent with the risk = hazard × exposure structure of CRI. Sensitivity tests across values of the distance-decay parameter, 100 entropy perturbations and spatial scales corroborate the buffering direction. The framework provides an evidentiary basis for prioritising green infrastructure in functionally connected, populated but environmentally degraded transition zones. Full article

Spatial and temporal patterns of terrestrial water storage (TWS), and their relationship with groundwater levels, were investigated with the Gravity Recovery and Climate Experiment (GRACE) satellite data, the Global Land Data Assimilation System (GLDAS) land surface model results, and climate observations for the Murray–Darling Basin (MDB). The results show that: (1) TWS displays a clear temporal variability: a negative TWS anomaly with a declining trend during 2002–2009, a positive TWS anomaly with a decreasing trend during 2010–2017, and a period of mixed positive and negative TWS anomalies being accompanied by an increasing trend from 2018 to 2025; (2) five dominant cluster patterns were identified that explain the spatial variability of temporal TWS across the MDB; (3) overall, TWS temporal variability is strongly correlated with rainfall, although it is weak at certain locations; (4) TWS is also influenced by evaporation (both actual and potential evapotranspiration, AET and PET) and runoff, and a combined model significantly improves the overall performance in explaining TWS temporal variability; and (5) TWS-derived groundwater storage changes show both similarities and differences in comparison with groundwater level observation changes, reflecting complex hydrogeological processes and the influence of human activities such as groundwater extraction. These findings provide valuable insights to support improved groundwater resource management with GRACE satellite information and land surface models. Full article

Agile attitude control of nanosatellites is increasingly required for high-resolution imaging, yet actuators that provide agility on larger spacecraft do not scale down well: reaction wheels are torque-limited and slew slowly, while miniaturized control moment gyroscopes (CMGs) deliver high torque but their stored wheel momentum produces a gyroscopic coupling torque that degrades fine pointing—an inherent agility–precision trade-off on low-inertia 3U platforms. This paper presents a two-step variable-speed CMG (VSCMG) strategy that preemptively decelerates the wheel momentum once the attitude error falls below a threshold, attenuating the gyroscopic torque before fine pointing and thus decoupling slewing from precision pointing. It is validated on an experimentally grounded model: a fabricated 1U-class four-CMG pyramid ($90\times 90\times 105$ mm, 584 g), gimbal dynamics identified experimentally ($93.2\%$ fit) and regulated by an integral-type optimal servo, and bench-measured wheel dynamics. At 560 km under aerodynamic and gravity-gradient disturbances, the strategy completes a 90° slew in 25.3 s at a mean slew rate of $3.55°/\mathrm{s}$ with $0.42°$ accuracy—$4.5\times$ faster than a reaction-wheel system and $12\times$ more accurate than single-mode CMG operation—with a Lyapunov-based stability guarantee. The spacecraft-level closed-loop performance is established in closed-loop simulation, while the component-level ground experiments verify only that the assumed wheel-speed and gimbal-rate envelopes are achievable on the prototype; the present work is thus a simulation study supported by experimentally identified actuator models, not a system-level experimental demonstration. These results show that momentum-managed VSCMG control substantially relieves the agility–precision trade-off within a 1U envelope under the single-axis 90° slew studied here, extending CMG-class agility to small form-factor satellites previously confined to reaction wheels. Full article