TerraMosaic Daily Digest: September 21, 2026
Daily Summary
Earthquake studies confront incomplete observations across timescales. A likelihood-free ETAS framework combines approximate Bayesian computation with stochastic optimization, recovers physical parameters from severely incomplete synthetic catalogs and scales sub-quadratically with catalog size. At Lake Malawi, sediment chronology, seismic imaging and finite-element modeling link 1.38 million years of hydrological loading to a 73% mean reduction in slip rate across four intrarift faults after the Mid-Pleistocene Transition. Laboratory fault reactivation further shows that aseismic slip can account for about 90% of total moment while governing the non-monotonic evolution of permeability.
Slope-hazard studies move from surface symptoms toward internal state and uncertainty. Ambient-noise interferometry resolves rainfall-linked seismic-velocity reductions of up to 4% within a monitored highway cut slope. Physical models of ancient landslide deposits show that clay content reorganizes wetting, pore-pressure response and localized remobilization, whereas Bayesian multi-task Gaussian processes transfer information across loess-landslide types and raise held-out runout R² from 0.66 to 0.98 within Heifangtai. Post-wildfire debris-flow experiments identify how mixed soil hydrophobicity controls air entrapment and sediment rheology.
Hydroclimatic work expands both hazard coverage and decision variables. National flood-susceptibility mapping in Nigeria, radar-informed watershed prioritization in Colombia and community-centered assessment of Himalayan avalanches and glacial-lake-outburst floods address data-sparse exposure. A new US precipitation-frequency dataset reports climate-oscillation effects of up to 40% in some regions, while a GRDC-constrained global water-budget product reduces closure inconsistencies across precipitation, evapotranspiration, runoff and storage. Compound-heatwave studies project Eurasian extremes beyond mean warming, while a generative attribution model assigns greater than 95% probability that post-2015 emissions intensified recent European heat.
Earth-observation methods are being tested against operational defects rather than clean benchmarks alone. RSPDBench exposes model-dependent losses under physically grounded product degradations, including compound failures not predictable from isolated corruptions. UniGIO unifies station-data imputation, generation and forecasting while improving extreme-event capture; a lightweight remote-sensing agent learns from executable environmental feedback; and direction-aware seismic pretraining improves cross-area acoustic-impedance inversion. Across the longer methods tail, uncertainty-aware downscaling, soil-moisture retrieval, LiDAR registration and open-set spectral analysis widen the monitoring toolkit, but most hazard benefits remain prospective.
Key Trends
The collection is unified by a shift from complete-data assumptions toward state-aware inference under missing, biased or spatially uneven observations.
- Incomplete observations are becoming part of the model: Likelihood-free seismic inference, masked global station modeling and sparse-observation correction treat catalog gaps, missing stations and delayed measurements as explicit statistical structure.
- Internal state is displacing surface-only hazard indicators: Seismic-velocity changes, pore-pressure evolution, fault permeability and hydrophobicity-dependent rheology expose subsurface processes that inventories or surface displacement alone cannot resolve.
- Uncertainty is becoming an output rather than a caveat: Bayesian runout transfer, simulation-based earthquake inference, conformal snow forecasts and product-degradation benchmarks quantify where predictions are supported and where deployment assumptions fail.
- Hazard datasets are moving toward decision-ready variables: Water-budget closure, climate-conditioned precipitation frequency, cryospheric risk and extreme-discharge warning connect observations to exposure, thresholds and response rather than stopping at environmental description.
- Foundation models are being stress-tested for Earth observation: Remote-sensing agents, foundation-model degradation benchmarks and forest point-cloud pretraining target long-horizon autonomy and transfer, but domain-specific reliability still depends on sensor physics and product quality.
Selected Papers
The 21 September collection is led by likelihood-free earthquake forecasting, hydroclimate-sensitive rift-fault mechanics, ambient-noise monitoring of rainfall-weakened cut slopes, clay-controlled reactivation of ancient landslide deposits and uncertainty-aware loess-landslide runout prediction. Companion studies address post-wildfire debris-flow rheology, national and watershed-scale flood susceptibility, Himalayan cryospheric risk, meteotsunamis, climate-conditioned precipitation frequency, global water-budget closure and robustness of Earth-observation foundation models.
1. A Likelihood-Free Framework for Seismic Forecasting Models: Application to Incomplete ETAS Model via Simulation-Based Inference
Core Problem: Massive, short-term-incomplete earthquake catalogs make conventional ETAS likelihood optimization biased and computationally difficult.
Key Innovation: Combines approximate Bayesian computation with stochastic optimization to recover incomplete-ETAS parameters from summary statistics, with synthetic tests showing robust recovery and sub-quadratic scaling.
2. Influence of Surface Processes on Intrarift Fault Displacement: 1.38 Million Years of Fault Slip Behavior in the Lake Malawi (Nyasa) Rift
Core Problem: Quantify how large Quaternary lake-level changes altered intrarift fault loading and slip over geological time.
Key Innovation: Integrates a 1.38-million-year sediment chronology, seismic slip histories and finite-element stress modeling, finding a 73% post-MPT slip-rate reduction across four faults.
3. Short-term monitoring of cut slope along highway using the ambient noise method
Core Problem: Surface displacement monitoring may miss internal stiffness degradation that precedes rainfall-induced slope failure.
Key Innovation: Tracks daily seismic velocity changes with ambient-noise interferometry, resolving rainfall-linked reductions up to 4% and frequency-dependent recoveries in a monitored highway slope.
4. Revealing six decades of ground deformation in the Koaʻe fault system on Kīlauea
Core Problem: Event-specific surveys obscure the long-term spatial organization of deformation across the Koaʻe Fault System.
Key Innovation: Integrates leveling, EDM and crack records since 1966, resolving episodic extension, up to 2 m subsidence and transient displacements associated with remote magmatic and tectonic events.
5. National-Scale Flood Susceptibility Mapping of Nigeria Using Statistical and Machine Learning Models with Satellite-Driven Validation for Data-Sparse Environments
Core Problem: Data scarcity limits national-scale flood susceptibility models and independent spatial validation in Nigeria.
Key Innovation: Compares statistical and machine-learning models with satellite-driven validation to construct a national susceptibility assessment for a data-sparse environment.
6. Cryospheric risks in the Himalayan region: impacts and community perceptions on snow avalanches and GLOFs in Chitral, Pakistan
Core Problem: Remote Himalayan communities face interacting avalanche and GLOF hazards whose local impacts and perceptions are poorly integrated into risk assessment.
Key Innovation: Combines hazard evidence with community perceptions in Chitral to characterize compound cryospheric risks and response priorities.
7. Identifying flash flood-prone watersheds using geomorphological and radar-derived rainfall features: a case study in Antioquia, Colombia
Core Problem: Rapid watershed prioritization is difficult where detailed hydrologic observations are sparse.
Key Innovation: Combines geomorphological indicators with radar-derived rainfall features to identify flash-flood-prone watersheds in Antioquia.
8. Effects of clay content on reactivation modes of ancient landslide deposits under rainfall
Core Problem: Clay content changes infiltration, water retention and strength, but its control on localized remobilization within old deposits is poorly resolved.
Key Innovation: Physical models contrast two clay contents and reveal distinct wetting, pore-pressure and progressive-collapse modes without reactivation of the pre-existing basal surface.
9. Bayesian multi-task Gaussian process regression for cross-type landslide runout prediction under data imbalance
Core Problem: Small, imbalanced inventories limit transferable runout prediction across shallow loess and loess-bedrock landslides.
Key Innovation: Couples task and input kernels with NUTS posterior sampling, raising held-out loess-bedrock R² from 0.66 to 0.98 while retaining near-nominal interval coverage in Heifangtai.
10. Seismic and Aseismic Slip Compete to Regulate Permeability Evolution During Fault Reactivation
Core Problem: Permeability evolution during reactivation depends on competing seismic and aseismic slip whose respective roles are difficult to isolate.
Key Innovation: Uses controlled fault-reactivation observations to distinguish how seismic and aseismic slip compete in regulating transient permeability.
11. Post-Wildfire Debris Flow Rheology of Mixed Hydrophobicity Sands
Core Problem: Hydrophobicity mixtures created by wildfire may change granular-flow rheology, but the effect is absent from standard debris-flow descriptions.
Key Innovation: Experiments on mixed-hydrophobicity sands quantify post-fire rheological behavior and provide process constraints for debris-flow modeling.
12. WildfireSpreadBench: The Metric Decides the Model in Wildfire Spread Prediction
Core Problem: Average precision can reward spatially excessive wildfire forecasts that are poorly suited to threshold-based operational decisions.
Key Innovation: Benchmarks six models with threshold-dependent metrics and identifies over-, balanced- and under-prediction regimes that AP alone conceals.
13. UniGIO: Unified Generative Global In-situ Weather Modeling from Spatiotemporal Incomplete Observations
Core Problem: Sparse and incomplete station observations impede global modeling of localized and transient weather dynamics.
Key Innovation: Unifies forecasting, imputation and generation from masked station observations, using spatial mixers, event alignment and local refinement to improve extremes capture on Weather-5K.
14. Predictors and Orchestrators: Parsimonious Machine Learning within an Agentic AI Harness for Multi-Horizon Karst Aquifer Forecasting
Core Problem: Karst recharge is nonlinear and event-driven, complicating reliable multi-week groundwater forecasts and threshold monitoring.
Key Innovation: Benchmarks five model families over 79 years, embeds the strongest parsimonious model in an auditable five-agent workflow and evaluates operational drought-stage agreement.
15. RS-Claw-Evolution: Environment-Feedback-Driven Evolution for Lightweight Remote Sensing Agents in Long-Horizon Tasks
Core Problem: Compact remote-sensing agents lose long-horizon state and receive sparse feedback during interactive geospatial tasks.
Key Innovation: Uses executable-state interaction, failure-aware experience learning and environment-reward reinforcement learning to raise a Qwen3-4B agent to 65.9% on Earth-Bench.
16. ClimTip-GML: A global bias-corrected and downscaled dataset for assessing impacts of climate tipping events
Core Problem: Impact studies of AMOC and Amazon tipping require high-resolution, bias-corrected and physically consistent climate scenarios.
Key Innovation: Publishes 0.25-degree, eight-variable, century-scale simulations with and without AMOC or Amazon transitions, using generative downscaling and multivariate validation.
17. A global terrestrial water budget discrete grid dataset constrained by GRDC observations (2000-2020)
Core Problem: A global terrestrial water budget discrete grid dataset constrained by GRDC observations (2000–2020) Kai Li, Juanle Wang, Congrong Li, Xianglin Ji, and Lizhi Pan Earth Syst.
Key Innovation: We combined multiple global data sources with river measurements from thousands of basins to create monthly maps of rain, evaporation, river flow, and stored water from 2000 to 2020.
18. Daily Precipitation-Frequency Estimates under Climate Oscillations across the Conterminous United States
Core Problem: Daily Precipitation-Frequency Estimates under Climate Oscillations across the Conterminous United States Ali Takallou, Nibedita Samal, and Hamid Moradkhani Earth Syst.
Key Innovation: We created a new high-resolution dataset for the conterminous United States by combining long-term precipitation records with spatial and climate information.
19. Comparative frequency-dependent harbor response to meteotsunamis along the Argentine and Uruguayan coasts
Core Problem: Meteotsunamis, long ocean waves generated by rapidly propagating atmospheric disturbances, frequently affect the southeastern coast of South America.
Key Innovation: Although their generation and propagation across the Buenos Aires continental shelf have been extensively investigated, their response within regional harbors remains poorly understood.
20. Signal reconstruction of microseismic water inrush based on composite multi-scale permutation entropy and complementary ensemble empirical mode decomposition
Core Problem: Microseismic signals associated with tunnel water inrush are frequently obscured by construction disturbances and equipment noise, hindering waveform recognition and time–frequency analysis.
Key Innovation: This study proposes a denoising and reconstruction method combining composite multiscale permutation entropy and complementary ensemble empirical mode decomposition (CMPE–CEEMD).
21. An efficient energy-based approach for identification of velocity-pulse periods
Core Problem: Reasonable identification of pulse period is essential for near-fault velocity-pulse simulation, structural response analysis, and probabilistic seismic hazard analysis.
Key Innovation: To address this limitation, this study aims to propose a simple yet robust method for identifying velocity-pulse periods directly from the elastic input energy spectrum, which reflects not only the amplitude and frequency content but also the duration and energy content of ground motions.
22. A simple preliminary seismic design procedure for low-to-medium rise reinforced concrete buildings
Core Problem: This paper describes and evaluates a simplified preliminary seismic design procedure, recently refined by the authors and implemented in the 2018 Turkish Building Earthquake Regulation (TBER 2018), for low- to medium-rise (2–8 stories with a maximum story height of 4 m) reinforced concrete buildings without significant structural irregularities.
Key Innovation: It applies to buildings with either moment-resisting frames (frame-only) or combined frame–wall (dual) systems.
23. Height-dependent nonlinear seismic response of masonry-infilled RC frame buildings with pilotis configurations
Core Problem: This study investigates the nonlinear seismic response of reinforced concrete (RC) frame buildings with masonry infills, with particular emphasis on pilotis-induced vertical irregularities and height-dependent behaviour.
Key Innovation: In particular, the presence of pilotis introduces a height-dependent transition in structural behaviour: low- to mid-rise structures exhibit limited sensitivity to ground-storey irregularities, whereas taller systems show increased concentration of deformation and force demand at the base.
24. Resilience-Oriented Post-Earthquake Restoration of Substations: Repair Sequencing and Resource Scheduling
Core Problem: Substations are critical components of power systems, and their post-earthquake restoration depends on topology, repair sequencing, and available resources.
Key Innovation: This study develops a resilience-oriented restoration framework in which a connectivity-based functionality model and minimum repair sets define the tasks required to restore functionality.
25. Concurrent Eurasian Heatwaves Will Intensify Beyond the Mean Warming
Core Problem: Abstract Concurrent heatwaves over Europe and North China are the most frequent compound heat extremes across the Northern Hemisphere.
Key Innovation: They are systematically organized by a recurrent teleconnection along the polar front jet over Eurasia.
26. Global Emissions Since the Paris Agreement Have Intensified Europe's Recent Heatwaves
Core Problem: Abstract Understanding the consequences of continued greenhouse‐gas emissions requires determining whether recent emissions can be robustly linked to changes in extreme weather events.
Key Innovation: Using this approach, we find strong evidence (>95% probability) that the combined effects of anthropogenic emissions released since the 2015 UN Paris Agreement have increased the intensity of Europe's summer temperature extremes since 2021.
27. Strengthening earthquake crisis management in France through international post-earthquake lessons
Core Problem: Moderate-seismicity countries cannot rely solely on exercises to reveal the coordination failures that emerge after damaging earthquakes.
Key Innovation: Synthesizes French exercise and earthquake reviews with international post-event lessons through policy-transfer and organizational-learning frameworks, emphasizing context-aware rather than uncritical transfer.
28. t0: A Time-Series Foundation Model for Forecasting with Context
Core Problem: We present $t_0$, a family of open-weights foundation models for forecasting with multivariate context.
Key Innovation: Pretraining combines curated public data with synthetic generator families constructed to contain covariate-to-target dependencies.
29. Enhanced early warning of extreme river discharge events in the Yangtze River Basin using atmospheric circulation signals
Core Problem: Title-level focus: identifies the problem signaled by: Enhanced early warning of extreme river discharge events in the Yangtze River Basin using atmospheric circulation signals.
Key Innovation: Title-signalled approach or contribution: The title identifies the study direction, but the available public metadata do not expose methods, validation or quantitative results. Methods, data and results could not be assessed because no reliable abstract was available.
30. The role of permafrost at Zonag Lake with its 2011 outburst: Insights from long-term and short-term perspectives
Core Problem: Title-level focus: identifies the problem signaled by: The role of permafrost at Zonag Lake with its 2011 outburst: Insights from long-term and short-term perspectives.
Key Innovation: Title-signalled approach or contribution: The title identifies the study direction, but the available public metadata do not expose methods, validation or quantitative results. Methods, data and results could not be assessed because no reliable abstract was available.
31. Topography and unsaturated zone thickness influence groundwater drought response and recovery in karst critical zone
Core Problem: Title-level focus: identifies the problem signaled by: Topography and unsaturated zone thickness influence groundwater drought response and recovery in karst critical zone.
Key Innovation: Title-signalled approach or contribution: The title identifies the study direction, but the available public metadata do not expose methods, validation or quantitative results. Methods, data and results could not be assessed because no reliable abstract was available.
32. Analyzing hydrological degradation vulnerability of non-perennial rivers shaped by groundwater stress, geogenic hazard and limited storage potential
Core Problem: Title-level focus: identifies the problem signaled by: Analyzing hydrological degradation vulnerability of non-perennial rivers shaped by groundwater stress, geogenic hazard and limited storage potential.
Key Innovation: Title-signalled approach or contribution: The title identifies the study direction, but the available public metadata do not expose methods, validation or quantitative results. Methods, data and results could not be assessed because no reliable abstract was available.
33. Spatiotemporal evolution and concentration of global meteorological drought burden from a three-dimensional object perspective
Core Problem: Title-level focus: identifies the problem signaled by: Spatiotemporal evolution and concentration of global meteorological drought burden from a three-dimensional object perspective.
Key Innovation: Title-signalled approach or contribution: The title identifies the study direction, but the available public metadata do not expose methods, validation or quantitative results. Methods, data and results could not be assessed because no reliable abstract was available.
34. 2D Finite Element Analysis of Seismic Amplification in Slopes under SV-Wave Excitation
Core Problem: Title-level focus: identifies the problem signaled by: 2D Finite Element Analysis of Seismic Amplification in Slopes under SV-Wave Excitation.
Key Innovation: Title-signalled approach or contribution: The title identifies the study direction, but the available public metadata do not expose methods, validation or quantitative results. Methods, data and results could not be assessed because no reliable abstract was available.
35. Extended Stochastic Finite-Fault Ground-Motion Simulation Incorporating Variable Stress Parameter and Stochastic Slip Models
Core Problem: Title-level focus: identifies the problem signaled by: Extended Stochastic Finite-Fault Ground-Motion Simulation Incorporating Variable Stress Parameter and Stochastic Slip Models.
Key Innovation: Title-signalled approach or contribution: The title identifies the study direction, but the available public metadata do not expose methods, validation or quantitative results. Methods, data and results could not be assessed because no reliable abstract was available.
36. Runout of submarine granular flow over sloping beds: Insights from CFD-DEM simulations
Core Problem: Title-level focus: identifies the problem signaled by: Runout of submarine granular flow over sloping beds: Insights from CFD–DEM simulations.
Key Innovation: Title-signalled approach or contribution: The title identifies the study direction, but the available public metadata do not expose methods, validation or quantitative results. Methods, data and results could not be assessed because no reliable abstract was available.
37. Settlement considerations for offshore wind turbine foundations subjected to earthquake-induced liquefaction
Core Problem: Title-level focus: identifies the problem signaled by: Settlement considerations for offshore wind turbine foundations subjected to earthquake-induced liquefaction.
Key Innovation: Title-signalled approach or contribution: The title identifies the study direction, but the available public metadata do not expose methods, validation or quantitative results. Methods, data and results could not be assessed because no reliable abstract was available.
38. Generalized Multimodal Foundation Model
Core Problem: Making prediction with multimodal data is widely used in diverse scenarios.
Key Innovation: To this end, we propose a simple and effective learning paradigm based on training over the generation of large-scale synthetic multimodal datasets with diverse causal structures that formally characterize the generative processes of multimodal data in real world.
39. StationPDE: Station-Oriented Surface PDE Learning for Multi-Station Multivariate Weather Forecasting
Core Problem: Multi-station multivariate weather forecasting aims to forecast future weather variables at multiple weather stations from historical surface observations.
Key Innovation: To bridge this gap, we propose StationPDE, a station-oriented surface PDE learning model.
40. Gaussian Process Decorrelation for Spatiotemporal Deep Learning-Based Snow Water Equivalent Prediction
Core Problem: In the Western United States, snowmelt is essential to the agricultural industry in addition to being a key source of municipal drinking water.
Key Innovation: Consequently, accurate snowpack forecasting is critical for water policy and management.
41. MarsRecon: Self-Supervised and Multimodal Surface Representations for Mars
Core Problem: High-resolution orbital imagery offers a rich record of the Martian surface, but sparse geological labels limit supervised representation learning.
Key Innovation: We present MarsRecon, a geospatially aware pipeline for learning visual and multimodal representations from HiRISE observations of Olympus Mons.
42. ZIL: Zero-shot Image-to-LiDAR Registration
Core Problem: Image-to-LiDAR registration estimates the camera pose of an image with respect to a LiDAR point cloud.
Key Innovation: We propose ZIL, the first foundation model for zero-shot non-synchronized image-to-LiDAR registration.
43. SatOV: Restoring Spatial Priors for Training-Free Open-Vocabulary Segmentation in Remote Sensing Imagery
Core Problem: Open-vocabulary semantic segmentation (OVS) of remote sensing imagery is a challenging pixel-level task requiring strong generalization and adaptation to the spatial characteristics of remote sensing data.
Key Innovation: To address these complementary deficiencies, we propose SatOV, a training-free framework for open-vocabulary remote sensing segmentation that restores spatial priors at two stages of the representation pipeline.
44. M3GA-Wild: A Large-Scale Dataset and Benchmark for Multi-Modal Multi-session Ground-to-Aerial Place Recognition in Forests
Core Problem: We present M3GA-Wild, the first benchmark for multi-modal, multi-session ground-to-aerial place recognition in forests.
Key Innovation: M3GA-Wild unifies and extends existing forest localisation datasets, providing a holistic benchmark with synchronised RGB imagery and LiDAR from ground traversals spanning 36 km, aligned high-resolution aerial imagery and multi-altitude LiDAR covering 370 hectares, and accurate geo-referenced 6-DoF poses for precise evaluation.
45. RSPDBench: Benchmarking Vision Foundation Models on Earth Observation Tasks Under Physically Grounded Remote-Sensing Product Degradations
Core Problem: Clean benchmarks do not reveal how remote-sensing product defects affect deployed foundation models.
Key Innovation: Evaluates seven foundation-model entries across five EO datasets under audited primitive and compound degradations, exposing model-dependent excess losses up to 38 percentage points.
46. From Regional to Global: Transfer Learning for Atmospheric Transport Emulators
Core Problem: Greenhouse gas emissions estimates can be derived using inverse methods by combining atmospheric concentration observations with chemical transport models.
Key Innovation: Previously we developed a performant atmospheric transport emulator that approximates LPDM outputs ("footprints") over South America ~1,000X faster than the UK Met Office's LPDM.
47. Taking a Second Look: Correcting Sea Ice Forecasts with Sparse Observations
Core Problem: Sea ice forecasts are issued several days ahead, allowing errors to accumulate while new, often sparse sea ice concentration (SIC) observations become available.
Key Innovation: We therefore introduce ECHO (Evidence-guided Correction with Heterogeneous prOpagation), where ECHO-Scale adapts propagation distance while preserving correction geometry, and ECHO-Delta learns a bounded residual around fixed propagation.
48. Direction-Aware Masked Pretraining for 3D Seismic Representation Learning and Transfer to Cross-Area Acoustic Impedance Inversion
Core Problem: Large archives of unlabeled three-dimensional seismic data offer opportunities for self-supervised representation learning and subsequent transfer to acoustic impedance inversion.
Key Innovation: We propose a direction-aware masked autoencoder for three-dimensional post-stack seismic data, combining anisotropic tokenization, direction-aware representation, trace-aligned tube masking, and reconstruction constraints designed for reflector continuity and waveform characteristics.
49. Toward a foundation model for forest point clouds
Core Problem: Forest inventories increasingly rely on artificial intelligence (AI) models to derive forest attributes from large-scale 3D point clouds.
Key Innovation: Inspired by recent developments in language modelling and computer vision, we take a step toward a foundation model (FM) for 3D forestry.
50. ITMSL: an improved ice thickness inversion model integrating basal sliding dynamics for High Mountain Asia (v1.0.0)
Core Problem: ITMSL: an improved ice thickness inversion model integrating basal sliding dynamics for High Mountain Asia (v1.0.0) Xiaoguang Pang, Liming Jiang, Yuxuan Wu, Xi Lu, Yi Liu, Xiaoen Li, and Tingting Yao Geosci.
Key Innovation: This paper presents the Ice Thickness Model considering Sliding Law (ITMSL) model, which integrates a basal sliding law with laminar flow equation, with the objective of simulating basal sliding to enhance the accuracy of ice thickness inversion.
51. SWOT Wide-Swath Altimetry for Inland-Water Remote Sensing: Applications, Challenges, and Prospects-A Systematic Bibliometric and Thematic Review
Core Problem: The Surface Water and Ocean Topography (SWOT) mission represents a major advance in satellite hydrology by extending conventional nadir altimetry to two-dimensional wide-swath observations of the inland-water surface elevation, extent, width, and slope.
Key Innovation: This review combines a bibliometric analysis of 556 publications indexed in the Web of Science Core Collection from January 2019 to April 2026 with a thematic synthesis of representative post-launch studies.
52. Downscaling of SMAP Soil Moisture Based on the Transformer Algorithm in Anhui Province
Core Problem: Soil moisture (SM) is critical for climate, water, and agriculture, but Soil Moisture Active Passive (SMAP) passive microwave products have coarse resolution, limiting regional applications.
Key Innovation: This study develops an SM downscaling framework based on Transformer and its variants (PatchTST and iTransformer), integrating multi-source satellite and groundwater data to generate 1 km daily SM products (2015–2022).
53. CYGNSS Soil Moisture Performance in Guinea Savanna Region: Extended and Quadruple Collocation Evidence from Benue State, Nigeria
Core Problem: Reliable soil moisture information is essential for agricultural drought warning, but tropical smallholder regions often lack ground networks for validating satellite products.
Key Innovation: A covariance-pathway Quadruple Collocation (QC) analysis then introduced the European Space Agency Climate Change Initiative active microwave soil moisture product (ESA CCI ACTIVE) as a fourth, structurally distinct product to test whether the CYGNSS–SMAP pair exhibited significant direct error correlation.
54. Asymmetric creep behavior and a mechanism of longitudinal crack development in cold-region subgrades under the sunny-shady slope effect
Core Problem: Longitudinal cracking is a common form of distress that compromises the performance of frozen ground subgrades.
Key Innovation: Persistent thermal asymmetry between the sunny and shady sides of a subgrade contributes to differential deformation, but the coupling among temperature evolution, ice-water phase change, and creep remains unclear.
55. Tunnel Convergence in Squeezing Ground with Strain Localisation
Core Problem: Modelling strain-softening behaviour in rocks and hard clays presents significant challenges due to strain localisation, which may lead to non-unique and mesh-dependent numerical solutions.
Key Innovation: In engineering practice, computationally tractable alternatives are therefore often used, including softening models suppressing strain localisation (hereafter referred to as non-localised softening analyses) or perfectly plastic models based on residual strength (hereafter referred to as perfectly plastic residual-strength analyses).
56. Finite element force method for joint and material nonlinearity problems
Core Problem: For geotechnical structures such as slopes and tunnels, their deformation and strength are characterized by both joint nonlinearity and material nonlinearity.
Key Innovation: Although the proposed solution is implemented within the framework of the force method, most of the involved matrices are identical to those employed in the traditional displacement method, facilitating its straightforward transplantation into displacement method-based programs.
57. What Is the Observed Sensitivity of Arctic Sea Ice?
Core Problem: Abstract The observed sensitivity of the Arctic summer sea‐ice area (SIA) to changes in the external forcing is a key quantity for understanding and projecting sea‐ice loss.
Key Innovation: We do so by developing and using a novel linear autoregressive AR(1) emulator.
58. Upper Rio Grande Streamflow, Climate, and Recent Increases in Runoff Efficiency
Core Problem: Abstract The Rio Grande is the main source of surface water supply for south‐central Colorado and much of New Mexico, with obligations via interstate and international treaties to Texas and Mexico.
Key Innovation: Recent drought conditions exacerbated by a warming climate have increased demand for this limited water supply.
59. Investigating the Overburden Correction Factor (Kσ) in silty sand using centrifuge modeling
Core Problem: Title-level focus: identifies the problem signaled by: Investigating the Overburden Correction Factor ( K σ ) in silty sand using centrifuge modeling.
Key Innovation: Title-signalled approach or contribution: The title identifies the study direction, but the available public metadata do not expose methods, validation or quantitative results. Methods, data and results could not be assessed because no reliable abstract was available.
60. Can AlphaEarth foundations redefine the paradigm of gridded population mapping? A systematic evaluation across 18 global cities and large-scale mapping applications
Core Problem: Title-level focus: identifies the problem signaled by: Can AlphaEarth foundations redefine the paradigm of gridded population mapping? A systematic evaluation across 18 global cities and large-scale mapping applications.
Key Innovation: Title-signalled approach or contribution: The title identifies the study direction, but the available public metadata do not expose methods, validation or quantitative results. Methods, data and results could not be assessed because no reliable abstract was available.
61. Using distributed temperature sensing (DTS) to locate and characterize snow depth and snowmelt in boreal landscapes
Core Problem: Title-level focus: identifies the problem signaled by: Using distributed temperature sensing (DTS) to locate and characterize snow depth and snowmelt in boreal landscapes.
Key Innovation: Title-signalled approach or contribution: The title identifies the study direction, but the available public metadata do not expose methods, validation or quantitative results. Methods, data and results could not be assessed because no reliable abstract was available.
62. Three-dimensional dynamic coupling mechanisms of shield tunnels in upper-soft-lower-hard strata under dispersive Rayleigh-Love wave excitation: A closed-form analytical framework
Core Problem: Title-level focus: identifies the problem signaled by: Three-dimensional dynamic coupling mechanisms of shield tunnels in upper-soft–lower-hard strata under dispersive Rayleigh–Love wave excitation: A closed-form analytical framework.
Key Innovation: Title-signalled approach or contribution: The title identifies the study direction, but the available public metadata do not expose methods, validation or quantitative results. Methods, data and results could not be assessed because no reliable abstract was available.
63. Geodetic constraints on regional scale mountain bedrock aquifer properties
Core Problem: Title-level focus: identifies the problem signaled by: Geodetic constraints on regional scale mountain bedrock aquifer properties.
Key Innovation: Title-signalled approach or contribution: The title identifies the study direction, but the available public metadata do not expose methods, validation or quantitative results. Methods, data and results could not be assessed because no reliable abstract was available.
64. An improved differentiable finite element method for saturated-unsaturated seepage with time-stepping, parallel, and inverse strategies
Core Problem: Title-level focus: identifies the problem signaled by: An improved differentiable finite element method for saturated–unsaturated seepage with time–stepping, parallel, and inverse strategies.
Key Innovation: Title-signalled approach or contribution: The title identifies the study direction, but the available public metadata do not expose methods, validation or quantitative results. Methods, data and results could not be assessed because no reliable abstract was available.
65. A volume-adaptive mixture-theory MPS model for transitional fluid-granular dynamics and impulse waves
Core Problem: Title-level focus: identifies the problem signaled by: A volume-adaptive mixture-theory MPS model for transitional fluid–granular dynamics and impulse waves.
Key Innovation: Title-signalled approach or contribution: The title identifies the study direction, but the available public metadata do not expose methods, validation or quantitative results. Methods, data and results could not be assessed because no reliable abstract was available.
66. Soil Structure Interaction Effects on the Seismic Performance of a Building Frame with Reusable Semi-Rigid Beam-to-Column Joints and Precast Geopolymer Concrete Slabs
Core Problem: Title-level focus: identifies the problem signaled by: Soil Structure Interaction Effects on the Seismic Performance of a Building Frame with Reusable Semi-Rigid Beam-to-Column Joints and Precast Geopolymer Concrete Slabs.
Key Innovation: Title-signalled approach or contribution: The title identifies the study direction, but the available public metadata do not expose methods, validation or quantitative results. Methods, data and results could not be assessed because no reliable abstract was available.
67. An Innovative Seismic Retrofitting Strategy with Staged-Damage Control for RC frames
Core Problem: Title-level focus: identifies the problem signaled by: An Innovative Seismic Retrofitting Strategy with Staged-Damage Control for RC frames.
Key Innovation: Title-signalled approach or contribution: The title identifies the study direction, but the available public metadata do not expose methods, validation or quantitative results. Methods, data and results could not be assessed because no reliable abstract was available.
68. Dual-Level Global Sensitivity and Seismic Fragility Analysis of Monopile-Supported Offshore Wind Turbines via physics-based surrogate modeling
Core Problem: Title-level focus: identifies the problem signaled by: Dual-Level Global Sensitivity and Seismic Fragility Analysis of Monopile-Supported Offshore Wind Turbines via physics-based surrogate modeling.
Key Innovation: Title-signalled approach or contribution: The title identifies the study direction, but the available public metadata do not expose methods, validation or quantitative results. Methods, data and results could not be assessed because no reliable abstract was available.
69. WaveDSNet: A Wavelet-Enhanced Discrepancy Semantic Network for Water Change Detection in SAR Imagery
Core Problem: Title-level focus: identifies the problem signaled by: WaveDSNet: A Wavelet-Enhanced Discrepancy Semantic Network for Water Change Detection in SAR Imagery.
Key Innovation: Title-signalled approach or contribution: The title identifies the study direction, but the available public metadata do not expose methods, validation or quantitative results. Methods, data and results could not be assessed because no reliable abstract was available.
70. FlexSnow: A flexible snow optics model framework integrating diverse snow microstructures and light-absorbing constituent mixtures in multiple layers
Core Problem: Title-level focus: identifies the problem signaled by: FlexSnow: A flexible snow optics model framework integrating diverse snow microstructures and light-absorbing constituent mixtures in multiple layers.
Key Innovation: Title-signalled approach or contribution: The title identifies the study direction, but the available public metadata do not expose methods, validation or quantitative results. Methods, data and results could not be assessed because no reliable abstract was available.
71. SolarFlowRefiner: Refinement-Aware Flow Matching for Surface Solar Radiation Downscaling
Core Problem: High-resolution surface solar radiation (SSR) is important for solar forecasting and grid operation.
Key Innovation: Post-hoc refinement also introduces a stage-wise mismatch: the generator is optimized independently, even though its output determines the refiner's initial state.
72. Dimensionality reduction for AI based hyperspectral image classification based on XAI
Core Problem: This research addresses the challenge of limited material recycling in wood recycling processes by leveraging artificial intelligence (AI)-based dimensionality reduction.
Key Innovation: Focusing on explainable AI (XAI) methods, this paper contributes to a broader research initiative, presenting a solution framework that enhances the sustainability and efficiency of wood recycling processes.
73. PanoSeg3R: Feed-Forward 3D Semantic Segmentation for Panoramic Images with an Automatic Data Curation Pipeline
Core Problem: We present PanoSeg3R, a feed-forward framework for 3D panoramic semantic segmentation.
Key Innovation: Furthermore, we introduce an automatic panorama data curation pipeline that leverages the complementary strengths of off-the-shelf foundation models to generate reliable pseudo semantic annotations, substantially expanding the training data and improving zero-shot generalization.
74. ScaleBlind: Point Cloud Completion under Unknown Scale
Core Problem: Point cloud completion aims to infer a complete 3D shape from a partial point cloud and serves as a fundamental building block for downstream tasks such as reconstruction, editing, and simulation.
Key Innovation: Motivated by this insight, we propose ScaleBlind, a novel framework that leverages foundation-model-based image completion to recover global scale directly from partial inputs and then faithfully produces the 3D completion.
75. Towards robust multimodal 3D object detection via visual foundation models
Core Problem: Multimodal 3D object detection is fundamental to robust perception in autonomous driving because it integrates complementary information from LiDAR and camera sensors.
Key Innovation: To address this problem, we propose RoboDistill, a robust and generalizable multimodal 3D object detection framework that leverages visual foundation models (VFMs), such as the Segment Anything Model (SAM).
76. Compact Low-Cost Hyperspectral Imaging via Angular-to-Spectral Diversity Conversion
Core Problem: Snapshot hyperspectral imaging avoids sequential scanning, but systems that jointly achieve stable reconstruction, low cost, and compact optics remain limited.
Key Innovation: We present a snapshot hyperspectral imaging system based on angular-to-spectral diversity conversion.
77. Which Terrain Is Better? Preference Learning with VLM Prototypes for Off-Road Traversability Ranking
Core Problem: In vision-based off-road navigation, a robot needs to know not only which obstacles to avoid but also which terrain is better.
Key Innovation: We present TravPro, which converts these annotations into ordered region pairs and fits a small readout on frozen vision--language model (VLM) patch tokens to these pairs.
78. Learning-Based 3D Reconstruction of Power Networks from Aerial Point Clouds
Core Problem: This paper presents an end-to-end framework for reconstructing overhead power utility network topology and extracting span-level physical metadata from large-scale aerial LiDAR.
Key Innovation: The pipeline begins with semantic segmentation of the input point cloud using an improved KPConv-based model, in which data sampling and loss functions are adapted to emphasize pole and conductor (wire) classes.
79. NeuIDO: Neural Intrinsic Dynamics Operator for Physics-Informed 4D World Models
Core Problem: World models aim to capture environmental dynamics and predict future trajectories, showing growing potential for embodied intelligence.
Key Innovation: Physics-informed 4D generation integrates physical simulation to predict 3D object interactions, offering a promising pathway toward world models.
80. Do LiDAR Language Models Really Understand Spatio-temporal Relationships?
Core Problem: Recent 4D LiDAR language models aim to reason about objects and their evolving spatial relationships.
Key Innovation: We introduce LiDAR-Hallu, a geometry-referenced benchmark and diagnostic protocol with 10,000 questions across 150 nuScenes scenes.
81. HyperCLIP++: Fine-tuning CLIP forOpen-vocabulary Semantic Segmentation in Hyperbolic Space
Core Problem: CLIP, a foundational vision-language model, has emerged as a powerful tool for open-vocabulary semantic segmentation.
Key Innovation: Building on this, we propose HyperCLIP++, a novel and parameter-efficient adaptation strategy.
82. Inference of Unknown Dynamical Components Using Next Generation Reservoir Computing: From Chaotic Systems to Climate Data
Core Problem: We investigate next generation reservoir computing (NGRC) as a data-driven approach for inferring unseen components of dynamical systems.
Key Innovation: We compare NGRC with traditional reservoir computing (RC) using the Lorenz and R\"ossler system, where two unknown components are inferred from one given component.
83. When Wider Views Fail: Stress-Testing Feed-Forward 3D Reconstruction
Core Problem: Feed-forward 3D reconstruction models enable efficient geometry estimation from sparse images, but their pretrained nature can make them vulnerable to distribution shifts beyond their training data.
Key Innovation: Identifying these failure modes is important for understanding when such models can be reliably deployed in unconstrained imaging settings.
84. Learning Prognostic Variables for AI Convective Parameterizations via Symbolic Distillation
Core Problem: Hybrid AI-physics climate modeling aims to improve coarse (~100km-resolution) Earth system models by learning to parameterize subgrid processes from high-fidelity data.
Key Innovation: We then replace the autoencoder with symbolic equations that govern the time evolution of the latent variables, yielding additional prognostic memory variables that can be integrated alongside the resolved atmospheric state.
85. WorldCrafter: Consistent Video World Model with Implicit 3D-aware Memory
Core Problem: Video world models enable interactive exploration of dynamic environments, yet struggle to respect prior observations over long horizons and across viewpoints.
Key Innovation: We present WorldCrafter, a video world model that learns a camera-queryable implicit 3D-aware memory for this purpose.
86. A sliding EOF-based deep learning framework for spatiotemporal forecasting of wind and wave fields
Core Problem: Conventional damage detection techniques are gradually being replaced by state-of-the-art smart monitoring and decision-making solutions.
Key Innovation: Near real-time and online damage assessment in structural health monitoring (SHM) systems is a promising transition toward bridging the gaps between the past’s applicative inefficiencies and the emerging technologies of the future.
87. Improving global and regional ocean heat content by consistently combining GRACE gravity, satellite altimetry and Argo profile observations in a joint inversion framework
Core Problem: Improving global and regional ocean heat content by consistently combining GRACE gravity, satellite altimetry and Argo profile observations in a joint inversion framework Bernd Uebbing, Kristin Vielberg, Roelof Rietbroek, Bene Aschenneller, Armin Köhl, and Jürgen Kusche Earth Syst.
Key Innovation: Sci.
88. TEMPL: a Multi-Platform LiDAR Dataset of a Temperate Forest in the Eastern United States
Core Problem: TEMPL: a Multi-Platform LiDAR Dataset of a Temperate Forest in the Eastern United States Sangyoon Park, Zachary Nelson Horve, Cameron Patrick Wingren, Michael R.
Key Innovation: We created a public dataset from nine plots in the Central Hardwood Forest of the eastern United States using aircraft, drones, backpacks, and field surveys.
89. A decade-scale catalog of coherent atmospheric infrasound transients from a three-element array at Jang Bogo Station, Terra Nova Bay, East Antarctica (2017-2026)
Core Problem: A decade-scale catalog of coherent atmospheric infrasound transients from a three-element array at Jang Bogo Station, Terra Nova Bay, East Antarctica (2017–2026) Yongcheol Park, Jinhoon Jung, and Won Sang Lee Earth Syst.
Key Innovation: Sci.
90. DIRECT 1.0: a diffusion-based generative model for dense sea surface temperature reconstructions from sparse satellite observations
Core Problem: DIRECT 1.0: a diffusion-based generative model for dense sea surface temperature reconstructions from sparse satellite observations Grega Rovšček, Matjaž Ličer, Alexander Barth, and Matej Kristan Geosci.
Key Innovation: We developed a new computer model that fills in these missing areas while also estimating how uncertain the reconstruction is.
91. MHBA-TransUNet: Shallow-Deep Collaborative RGB-DSM Fusion with Hybrid Bidirectional Attention for High-Resolution Remote Sensing Semantic Segmentation
Core Problem: High-resolution remote sensing semantic segmentation using RGB imagery and digital surface models (DSM) remains challenging because of insufficient shallow cross-modal fusion and inadequate coordination between global semantics and local spatial information.
Key Innovation: To address these issues, we propose MHBA-TransUNet, a hybrid encoder–decoder network for RGB–DSM semantic segmentation.
92. Unit-Simplex-Inspired Graph Attention Network for Robust Endmember Determination in Hyperspectral Imagery
Core Problem: Endmember extraction (EE) in an unmixing chain aims at determining source component spectra constituting pixels from hyperspectral imagery.
Key Innovation: In this paper, we propose a novel unit-simplex-inspired graph attention network (GAT) to identify endmembers based on the pure pixel assumption.
93. Estimating Ground-Level PM2.5 over Beijing-Tianjin-Hebei from DQ-1 Wide-Swath Imager Signals and ERA5 Meteorology Using Physics-Guided Feature Engineering
Core Problem: The DaQi-1 (DQ-1) Wide-Swath Imager (WSI) combines an approximately 2300 km swath with 15 visible-to-shortwave-infrared channels at 75–600 m resolution, providing broad regional coverage and flexible spectral support.
Key Innovation: We developed an ExtraTrees estimator from WSI signals and ERA5 planetary boundary-layer height, winds, and relative humidity for Beijing–Tianjin–Hebei in 2024.
94. Fracture network construction and damage dependent strength of coal samples based on CT scanning
Core Problem: The fracture network may significantly influence the stability and fluid flow of a coal rock mass.
Key Innovation: This study presents a novel approach for constructing fracture network and investigating damage-dependent strength for coal samples based on CT scanning techniques.
95. Experimental Study on Spatiotemporal Propagation of Stress Waves and Failure Characteristics of Rock in Double-Hole Blasting Under in-Situ Stress
Core Problem: Deep rock blasting is characterized by dynamic-static coupled failure under the combined effects of in-situ stress and multi-borehole blasting loads.
Key Innovation: These findings validate the proposed theoretical model and provide insights into the control mechanism of crack propagation under in-situ stress, offering guidance for blasting design in deep rock engineering.
96. Settlement of Peaty Clay Improved with T-Shaped Deep Mixing Columns Incorporating Cement and Rice Husk Ash
Core Problem: This study aims to evaluate the effectiveness of the T-shaped Deep Mixing (TDM) method for peaty clay stabilization using cement combined with rice husk ash (RHA) as a sustainable binder, with particular emphasis on settlement reduction and the influence of TDM column geometry.
Key Innovation: Conventional deep mixing (DM) columns exhibit notable limitations, including high settlement, diminished strength with depth, and increased material costs.
97. Oblique Migration of Megaripples Under an Obtuse Bimodal Wind Regime in Qaidam Basin, China
Core Problem: Abstract Megaripple crestlines are commonly treated as transverse indicators of wind or sand‐transport direction.
Key Innovation: However, Martian observations show that some large ripples, bright‐toned megaripples, and small Transverse Aeolian Ridges (TARs) can migrate obliquely or longitudinally, a phenomenon not previously documented on Earth.
98. New Constraint on Future Ocean Heat Uptake Revealed by Considering Model Spread of Radiative Forcing
Core Problem: Abstract Radiative forcing is the fundamental driver of ocean heat uptake ; however, its contribution to intermodel spread in has not been quantified.
Key Innovation: We address this gap by leveraging a new set of CMIP6 experiments that diagnoses time‐varying for the first time in 11 models.
99. Dual-Pathway Influence of Submesoscale Processes on the Southern Ocean Meridional Overturning Circulation
Core Problem: Abstract The Southern Ocean meridional overturning circulation (MOC) play a crucial role in the global ocean water mass and heat redistribution, greatly modulating the earth climate variation.
Key Innovation: Although mesoscale eddies are known as an important component of the residual‐mean MOC that typically oppose wind‐driven Eulerian overturning, the contribution of submesoscale processes remains poorly understood.
100. Early Eocene Compressional Deformation in the Northeastern Tibetan Plateau Recorded by Magnetic Fabrics of the Longzhong Basin
Core Problem: Abstract Intracontinental deformation records how early Eocene India–Asia collisional stress propagated into continental interiors.
Key Innovation: How rapidly compression reached the far field, and whether coeval Paleo‐Pacific slab dynamics contributed, remain debated.
101. Reaction-Gated Transient Permeability in Ductile Shear Zones
Core Problem: Abstract Ductile shear zones act as transient pathways for crustal fluids, yet the conditions under which their connected porosity becomes sufficient to conduct are not well constrained.
Key Innovation: We present a porosity balance in which connected porosity evolves under three competing processes: creation by creep cavitation, creation by metamorphic reaction, and thermally activated closure.
102. Effect of scour- and cyclic loading-induced soil-monopile stiffness degradation on long-term dynamic response of support structures for OWT
Core Problem: Title-level focus: identifies the problem signaled by: Effect of scour- and cyclic loading-induced soil-monopile stiffness degradation on long-term dynamic response of support structures for OWT.
Key Innovation: Title-signalled approach or contribution: The title identifies the study direction, but the available public metadata do not expose methods, validation or quantitative results. Methods, data and results could not be assessed because no reliable abstract was available.
103. Active learning structural reliability analysis using Separable PINNs
Core Problem: Title-level focus: identifies the problem signaled by: Active learning structural reliability analysis using Separable PINNs.
Key Innovation: Title-signalled approach or contribution: The title identifies the study direction, but the available public metadata do not expose methods, validation or quantitative results. Methods, data and results could not be assessed because no reliable abstract was available.
104. A multiscale approach for the uncertainty quantification in the steady-state response of nonlinear soil-structure systems
Core Problem: Title-level focus: identifies the problem signaled by: A multiscale approach for the uncertainty quantification in the steady-state response of nonlinear soil-structure systems.
Key Innovation: Title-signalled approach or contribution: The title identifies the study direction, but the available public metadata do not expose methods, validation or quantitative results. Methods, data and results could not be assessed because no reliable abstract was available.
105. Toward fine-scale microwave monitoring of dryland vegetation: an alternative high spatial resolution vegetation optical depth retrieval algorithm from Sentinel-1 over the Sahel region
Core Problem: Title-level focus: identifies the problem signaled by: Toward fine-scale microwave monitoring of dryland vegetation: an alternative high spatial resolution vegetation optical depth retrieval algorithm from Sentinel-1 over the Sahel region.
Key Innovation: Title-signalled approach or contribution: The title identifies the study direction, but the available public metadata do not expose methods, validation or quantitative results. Methods, data and results could not be assessed because no reliable abstract was available.
106. Spatiotemporal extension of all-sky downward shortwave radiation over mountainous area
Core Problem: Title-level focus: identifies the problem signaled by: Spatiotemporal extension of all-sky downward shortwave radiation over mountainous area.
Key Innovation: Title-signalled approach or contribution: The title identifies the study direction, but the available public metadata do not expose methods, validation or quantitative results. Methods, data and results could not be assessed because no reliable abstract was available.
107. SNAIL-Radar-Indoor:A large-scale handheld LiDAR-4D radar-IMU dataset for robust SLAM in degraded environments
Core Problem: Title-level focus: identifies the problem signaled by: SNAIL-Radar-Indoor:A large-scale handheld LiDAR–4D radar–IMU dataset for robust SLAM in degraded environments.
Key Innovation: Title-signalled approach or contribution: The title identifies the study direction, but the available public metadata do not expose methods, validation or quantitative results. Methods, data and results could not be assessed because no reliable abstract was available.
108. Evolving transformers with reinforcement learning-enhanced grey wolf optimisation for remote sensing image segmentation
Core Problem: Title-level focus: identifies the problem signaled by: Evolving transformers with reinforcement learning-enhanced grey wolf optimisation for remote sensing image segmentation.
Key Innovation: Title-signalled approach or contribution: The title identifies the study direction, but the available public metadata do not expose methods, validation or quantitative results. Methods, data and results could not be assessed because no reliable abstract was available.
109. HELIOS-Net: Hourly daytime estimation of land surface temperature with integration of observational solar-cloud-satellite geometry and deep neural network
Core Problem: Title-level focus: identifies the problem signaled by: HELIOS-Net: Hourly daytime estimation of land surface temperature with integration of observational solar-cloud-satellite geometry and deep neural network.
Key Innovation: Title-signalled approach or contribution: The title identifies the study direction, but the available public metadata do not expose methods, validation or quantitative results. Methods, data and results could not be assessed because no reliable abstract was available.
110. Analysis of intraday urban thermal anisotropy and downward shortwave radiation through UAV experiment and coupled model
Core Problem: Title-level focus: identifies the problem signaled by: Analysis of intraday urban thermal anisotropy and downward shortwave radiation through UAV experiment and coupled model.
Key Innovation: Title-signalled approach or contribution: The title identifies the study direction, but the available public metadata do not expose methods, validation or quantitative results. Methods, data and results could not be assessed because no reliable abstract was available.
111. Remote-sensing-assisted and in situ-constrained reconstruction of 4-hourly chlorophyll-a dynamics in inland lakes using vision Mamba and temporal attention
Core Problem: Title-level focus: identifies the problem signaled by: Remote-sensing-assisted and in situ-constrained reconstruction of 4-hourly chlorophyll-a dynamics in inland lakes using vision Mamba and temporal attention.
Key Innovation: Title-signalled approach or contribution: The title identifies the study direction, but the available public metadata do not expose methods, validation or quantitative results. Methods, data and results could not be assessed because no reliable abstract was available.
112. Reference-anchored envelope modelling for predicting tree mortality hotspots driven by drought
Core Problem: Title-level focus: identifies the problem signaled by: Reference-anchored envelope modelling for predicting tree mortality hotspots driven by drought.
Key Innovation: Title-signalled approach or contribution: The title identifies the study direction, but the available public metadata do not expose methods, validation or quantitative results. Methods, data and results could not be assessed because no reliable abstract was available.
113. Automatic detection of water leakage defects in tunnel linings from GPR images using a MIL-based dual-path dynamic feature fusion approach
Core Problem: Title-level focus: identifies the problem signaled by: Automatic detection of water leakage defects in tunnel linings from GPR images using a MIL-based dual-path dynamic feature fusion approach.
Key Innovation: Title-signalled approach or contribution: The title identifies the study direction, but the available public metadata do not expose methods, validation or quantitative results. Methods, data and results could not be assessed because no reliable abstract was available.
114. Image-based Bayesian learning of geological knowledge and TBM operational data for prediction of rock mass classifications multi-step ahead of tunnel face
Core Problem: Title-level focus: identifies the problem signaled by: Image-based Bayesian learning of geological knowledge and TBM operational data for prediction of rock mass classifications multi-step ahead of tunnel face.
Key Innovation: Title-signalled approach or contribution: The title identifies the study direction, but the available public metadata do not expose methods, validation or quantitative results. Methods, data and results could not be assessed because no reliable abstract was available.
115. Automated multiscale damage assessment of power cable tunnel using ConvNeXt V2 and Panoptic FPN with super-resolution enhancement
Core Problem: Title-level focus: identifies the problem signaled by: Automated multiscale damage assessment of power cable tunnel using ConvNeXt V2 and Panoptic FPN with super-resolution enhancement.
Key Innovation: Title-signalled approach or contribution: The title identifies the study direction, but the available public metadata do not expose methods, validation or quantitative results. Methods, data and results could not be assessed because no reliable abstract was available.
116. Reconstruction of post-mining porosity-permeability field in abandoned coal mine goaf and its implication for CO₂ sequestration
Core Problem: Title-level focus: identifies the problem signaled by: Reconstruction of post-mining porosity-permeability field in abandoned coal mine goaf and its implication for CO2 sequestration.
Key Innovation: Title-signalled approach or contribution: The title identifies the study direction, but the available public metadata do not expose methods, validation or quantitative results. Methods, data and results could not be assessed because no reliable abstract was available.
117. Modeling of instability in cemented granular materials with an enhanced multiscale model
Core Problem: Title-level focus: identifies the problem signaled by: Modeling of instability in cemented granular materials with an enhanced multiscale model.
Key Innovation: Title-signalled approach or contribution: The title identifies the study direction, but the available public metadata do not expose methods, validation or quantitative results. Methods, data and results could not be assessed because no reliable abstract was available.
118. An equivalent model for flow and solute transport in rough fractures based on a comprehensive roughness parameter
Core Problem: Title-level focus: identifies the problem signaled by: An equivalent model for flow and solute transport in rough fractures based on a comprehensive roughness parameter.
Key Innovation: Title-signalled approach or contribution: The title identifies the study direction, but the available public metadata do not expose methods, validation or quantitative results. Methods, data and results could not be assessed because no reliable abstract was available.
119. Stability analysis of L-shaped caisson quay wall under strip load
Core Problem: Title-level focus: identifies the problem signaled by: Stability analysis of L-shaped caisson quay wall under strip load.
Key Innovation: Title-signalled approach or contribution: The title identifies the study direction, but the available public metadata do not expose methods, validation or quantitative results. Methods, data and results could not be assessed because no reliable abstract was available.
120. Long-term evolution of negative skin friction on piles in coastal soft ground: Effects of vacuum-preloading depth and surcharge
Core Problem: Title-level focus: identifies the problem signaled by: Long-term evolution of negative skin friction on piles in coastal soft ground: Effects of vacuum-preloading depth and surcharge.
Key Innovation: Title-signalled approach or contribution: The title identifies the study direction, but the available public metadata do not expose methods, validation or quantitative results. Methods, data and results could not be assessed because no reliable abstract was available.
121. Machine-learning-improved tide-wave simulations and joint extreme analysis for wave energy assessment in the Taiwan Strait
Core Problem: Title-level focus: identifies the problem signaled by: Machine-learning-improved tide–wave simulations and joint extreme analysis for wave energy assessment in the Taiwan Strait.
Key Innovation: Title-signalled approach or contribution: The title identifies the study direction, but the available public metadata do not expose methods, validation or quantitative results. Methods, data and results could not be assessed because no reliable abstract was available.
122. Road-Structure-Guided Sampling-Controlled Trajectory Aggregation for Road Extraction from High-Resolution Remote Sensing Imagery
Core Problem: Title-level focus: identifies the problem signaled by: Road-Structure-Guided Sampling-Controlled Trajectory Aggregation for Road Extraction from High-Resolution Remote Sensing Imagery.
Key Innovation: Title-signalled approach or contribution: The title identifies the study direction, but the available public metadata do not expose methods, validation or quantitative results. Methods, data and results could not be assessed because no reliable abstract was available.
123. SMGNet: A Lightweight Spectral-Mamba-Guided Network for Hyperspectral Image Classification
Core Problem: Title-level focus: identifies the problem signaled by: SMGNet: A Lightweight Spectral-Mamba-Guided Network for Hyperspectral Image Classification.
Key Innovation: Title-signalled approach or contribution: The title identifies the study direction, but the available public metadata do not expose methods, validation or quantitative results. Methods, data and results could not be assessed because no reliable abstract was available.
124. Robustness Assessment of PolSAR Target Detection Under Transferable Amplitude-Phase Perturbations
Core Problem: Title-level focus: identifies the problem signaled by: Robustness Assessment of PolSAR Target Detection Under Transferable Amplitude–Phase Perturbations.
Key Innovation: Title-signalled approach or contribution: The title identifies the study direction, but the available public metadata do not expose methods, validation or quantitative results. Methods, data and results could not be assessed because no reliable abstract was available.
125. Spaceborne Ultra-High-Resolution Sliding Spotlight SAR Imaging Algorithm Based on United Azimuth Time-Frequency Polynomial Compensation
Core Problem: Title-level focus: identifies the problem signaled by: Spaceborne Ultra-High-Resolution Sliding Spotlight SAR Imaging Algorithm Based on United Azimuth Time-Frequency Polynomial Compensation.
Key Innovation: Title-signalled approach or contribution: The title identifies the study direction, but the available public metadata do not expose methods, validation or quantitative results. Methods, data and results could not be assessed because no reliable abstract was available.
126. MS2-UAV: A Controlled Multisensor and Multi-Temporal Low-Altitude UAV Benchmark for Fusion-Aware Map-Based Localization
Core Problem: Title-level focus: identifies the problem signaled by: MS2-UAV: A Controlled Multisensor and Multi-Temporal Low-Altitude UAV Benchmark for Fusion-Aware Map-Based Localization.
Key Innovation: Title-signalled approach or contribution: The title identifies the study direction, but the available public metadata do not expose methods, validation or quantitative results. Methods, data and results could not be assessed because no reliable abstract was available.
127. An Empirical Comparison of Optical Time-Series Reconstruction and Terrain/SAR Feature Augmentation for Land-Cover Classification in Cloud-Prone Mountainous Regions
Core Problem: Title-level focus: identifies the problem signaled by: An Empirical Comparison of Optical Time-Series Reconstruction and Terrain/SAR Feature Augmentation for Land-Cover Classification in Cloud-Prone Mountainous Regions.
Key Innovation: Title-signalled approach or contribution: The title identifies the study direction, but the available public metadata do not expose methods, validation or quantitative results. Methods, data and results could not be assessed because no reliable abstract was available.
128. MDFPF-Net: Multi-Domain Feature Perceptual Fusion Network for Hyperspectral Unmixing
Core Problem: Title-level focus: identifies the problem signaled by: MDFPF-Net: Multi-Domain Feature Perceptual Fusion Network for Hyperspectral Unmixing.
Key Innovation: Title-signalled approach or contribution: The title identifies the study direction, but the available public metadata do not expose methods, validation or quantitative results. Methods, data and results could not be assessed because no reliable abstract was available.
129. Hardness-Aware Contrastive Learning with Data Condensation for Open-Set Hyperspectral Image Classification
Core Problem: Title-level focus: identifies the problem signaled by: Hardness-Aware Contrastive Learning with Data Condensation for Open-Set Hyperspectral Image Classification.
Key Innovation: Title-signalled approach or contribution: The title identifies the study direction, but the available public metadata do not expose methods, validation or quantitative results. Methods, data and results could not be assessed because no reliable abstract was available.
130. CTF-SRNet: A Cross-Modal Text and Feature Modulation Network for Remote Sensing Image Super-Resolution
Core Problem: Title-level focus: identifies the problem signaled by: CTF-SRNet: A Cross-Modal Text and Feature Modulation Network for Remote Sensing Image Super-Resolution.
Key Innovation: Title-signalled approach or contribution: The title identifies the study direction, but the available public metadata do not expose methods, validation or quantitative results. Methods, data and results could not be assessed because no reliable abstract was available.
131. Quantifying Uncertainty Bounds in Spectral Shallow Water Bathymetry: The Profile Likelihood Framework for Semi-Analytical Models
Core Problem: Title-level focus: identifies the problem signaled by: Quantifying Uncertainty Bounds in Spectral Shallow Water Bathymetry: The Profile Likelihood Framework for Semi-Analytical Models.
Key Innovation: Title-signalled approach or contribution: The title identifies the study direction, but the available public metadata do not expose methods, validation or quantitative results. Methods, data and results could not be assessed because no reliable abstract was available.
132. Two-Stage Active-Passive Synergistic Water Depth Estimation Using Shallow Water Probability Constraint and Multi-Feature Attention ResNet
Core Problem: Title-level focus: identifies the problem signaled by: Two-Stage Active—Passive Synergistic Water Depth Estimation Using Shallow Water Probability Constraint and Multi-Feature Attention ResNet.
Key Innovation: Title-signalled approach or contribution: The title identifies the study direction, but the available public metadata do not expose methods, validation or quantitative results. Methods, data and results could not be assessed because no reliable abstract was available.
133. Contrastive World Models
Core Problem: World models trained via pixel reconstruction can struggle in visually complex environments, where irrelevant information dominates the objective and distract the model from information relevant to planning and control.
Key Innovation: We present Contrastive World Models, an approach for learning latent dynamics models without pixel reconstruction.
134. Combining Foundation Model Confidence and Monocular Depth for Training-Free Out-of-Distribution Segmentation
Core Problem: Autonomous vehicles operating in open-world scenarios are inevitably confronted with previously unknown objects, such as exotic animals or loose cargo.
Key Innovation: We propose a training-free method that derives dense OOD scores directly from the confidence predictions of a foundation segmentation model, without any task-specific fine-tuning or access to anomalous data.
135. A paired synthetic construction-site image dataset for robust computer vision under adverse conditions
Core Problem: Computer-vision systems used for construction monitoring can degrade under adverse environmental and visual conditions, yet such conditions remain underrepresented in existing construction image datasets.
Key Innovation: We present ConSynth-X, a paired synthetic construction-site image dataset containing 34,199 images derived from 3,109 real-world source scenes.
136. High-resolution Nitrogen Dioxide Maps Reveal Exposure Limit Breaches across Europe
Core Problem: Nitrogen dioxide (NO2) is a common air pollutant, released into the atmosphere through the incomplete burning of fossil fuels, and associated with respiratory and cardiovascular diseases in humans.
Key Innovation: The revised EU Ambient Air Quality Directive (2024/2881) introduces a daily NO2 limit to be met from 2030.
137. Tectonics on early Earth driven by Earth's changing shape during tidal recession of the Moon
Core Problem: Few fragments of Earth's earliest crust have survived, and so this formative period of our planet's history is shrouded in mystery.
Key Innovation: To leverage the limited data available, it is important to understand all the processes that could have shaped our young planet.
138. A random forest isoscape model of bioavailable Sr for South America: a focus on southern Brazil
Core Problem: A random forest isoscape model of bioavailable Sr for South America: a focus on southern Brazil Cinzia Scaggion, Tommaso Giovanardi, László Palcsu, Daniel Loponte, Mirian Carbonera, Sara Bernardini, Stefano Benazzi, Giulia Marciani, Marcos Cesar Pereira Santos, Eugenio Bortolini, Anna Cipriani, and Federico Lugli Earth Syst.
Key Innovation: Data, 18, 6925–6943, https://doi.org/10.5194/essd-18-6925-2026, 2026 In this work, we present a new dataset of strontium isotopes from leaves collected in Santa Catarina and Rio Grande do Sul (Brazil).
139. A simplified isoprene oxidation mechanism for fast formaldehyde-based emission inversion of isoprene
Core Problem: A simplified isoprene oxidation mechanism for fast formaldehyde-based emission inversion of isoprene Glenn-Michael Oomen, Jean-François Müller, Trissevgeni Stavrakou, Isabelle De Smedt, Vincent Huijnen, Flora Kluge, Antje Inness, and Johannes Flemming Geosci.
Key Innovation: Model Dev., 19, 8959–8975, https://doi.org/10.5194/gmd-19-8959-2026, 2026 We developed a strongly simplified mechanism for isoprene oxidation that reduces the computational cost of atmospheric chemistry while retaining the key processes controlling formaldehyde formation.
140. Simulation of Equatorial Plasma Bubble Signatures in GNSS TEC
Core Problem: Equatorial plasma bubbles (EPBs) are ionospheric plasma depletions that can disrupt Global Navigation Satellite System (GNSS) signals and degrade positioning at equatorial and low latitudes.
Key Innovation: This study develops a controlled forward modeling framework for simulating and detecting EPB signatures in GNSS slant TEC (sTEC).
141. Daily Lake-Surface NDVI Reconstruction Using Multi-Source Machine Learning Under Incomplete Optical Observations
Core Problem: Accurate and continuous monitoring of cyanobacterial blooms is essential for lake ecosystem management, but optical remote-sensing observations are frequently limited by cloud contamination and illumination conditions.
Key Innovation: To address this limitation, this study proposes a multi-source machine learning framework for daily lake-surface normalized difference vegetation index (NDVI) reconstruction under missing optical observations by integrating Cyclone Global Navigation Satellite System (CYGNSS) observations, ERA5-Land meteorological variables, geographic coordinates, and the CatBoost (version 1.2.10) regression algorithm.
142. Triple-Level Topology Awareness Using Hypergraph for Marine Ship Surveillance from SAR Imagery
Core Problem: Marine ship surveillance from synthetic aperture radar (SAR) imagery is extensively studied.
Key Innovation: To this end, we propose a triple-level topology awareness (TLTA) framework using hypergraphs for effective SAR marine ship surveillance.
143. Satellite-Based Seasonal Monitoring of PM2.5-Related Trace Gases and Aerosol Loading over the Lazio Region
Core Problem: Ground-based monitoring networks often provide uneven spatial coverage, limiting the characterization of air-quality in heterogeneous regions.
Key Innovation: This study proposes a data-driven framework that identifies spatially coherent atmospheric regimes from multi-gas satellite observations.
144. From Pixel Receptive Fields to Ground Spans: GSD-Conditioned Cross-Resolution Feature Alignment for Photovoltaic Detection and Segmentation
Core Problem: Photovoltaic (PV) inventories with explicit location and extent are needed for energy accounting, distribution-grid planning, and asset monitoring.
Key Innovation: To address this, this paper proposes CRFA-PVNet, a physically guided cross-resolution feature alignment network for PV detection and segmentation, which describes the receptive field in ground units rather than in pixels.
145. Investigation of gravity load effects on in-plane behavior of composite steel decks
Core Problem: Composite steel deck diaphragms play a critical role in transferring earthquake-induced inertial forces to the lateral force–resisting system while simultaneously supporting gravity loads.
Key Innovation: This study investigates the coupled effects of gravity load and connection detailing on the in-plane seismic response of concrete-filled steel deck diaphragms through a combined experimental and numerical approach.
146. Hydrogen-Dominated Iron Phase Stability and the Structure of the Earth's Inner Core
Core Problem: Abstract The crystal structure of Earth's inner core (IC) remains debated, with the free energy difference between hexagonal close‐packed (hcp) and body‐centered cubic (bcc) iron under IC conditions being very small.
Key Innovation: We use ab initio and machine learning force field molecular dynamics simulations to show that hydrogen can strongly influence the phase stability of inner‐core iron.
147. A radar-vision fusion approach for ship monitoring in bridge waterways using weakly supervised cross-modal representation learning
Core Problem: Title-level focus: identifies the problem signaled by: A radar–vision fusion approach for ship monitoring in bridge waterways using weakly supervised cross-modal representation learning.
Key Innovation: Title-signalled approach or contribution: The title identifies the study direction, but the available public metadata do not expose methods, validation or quantitative results. Methods, data and results could not be assessed because no reliable abstract was available.
148. Artificial Intelligence in Nuclear Emergency Response: A Systematic Gap Analysis and a Human-Artificial Intelligence Teaming Framework
Core Problem: Title-level focus: identifies the problem signaled by: Artificial Intelligence in Nuclear Emergency Response: A Systematic Gap Analysis and a Human-Artificial Intelligence Teaming Framework.
Key Innovation: Title-signalled approach or contribution: The title identifies the study direction, but the available public metadata do not expose methods, validation or quantitative results. Methods, data and results could not be assessed because no reliable abstract was available.
149. Uncertainties in optical remote sensing of plant diversity
Core Problem: Title-level focus: identifies the problem signaled by: Uncertainties in optical remote sensing of plant diversity.
Key Innovation: Title-signalled approach or contribution: The title identifies the study direction, but the available public metadata do not expose methods, validation or quantitative results. Methods, data and results could not be assessed because no reliable abstract was available.
150. Mapping rodent-induced disturbance of biological soil crusts using PlanetScope imagery and deep-learning-informed graph cut
Core Problem: Title-level focus: identifies the problem signaled by: Mapping rodent-induced disturbance of biological soil crusts using PlanetScope imagery and deep-learning-informed graph cut.
Key Innovation: Title-signalled approach or contribution: The title identifies the study direction, but the available public metadata do not expose methods, validation or quantitative results. Methods, data and results could not be assessed because no reliable abstract was available.
151. PatchFusion: Resilient LiDAR-camera fusion for point cloud semantic segmentation in autonomous driving
Core Problem: Title-level focus: identifies the problem signaled by: PatchFusion: Resilient LiDAR-camera fusion for point cloud semantic segmentation in autonomous driving.
Key Innovation: Title-signalled approach or contribution: The title identifies the study direction, but the available public metadata do not expose methods, validation or quantitative results. Methods, data and results could not be assessed because no reliable abstract was available.
152. SaKD: Lightweight infrared small target detection via Spatial-Aware Knowledge Distillation for edge deployment
Core Problem: Title-level focus: identifies the problem signaled by: SaKD: Lightweight infrared small target detection via Spatial-Aware Knowledge Distillation for edge deployment.
Key Innovation: Title-signalled approach or contribution: The title identifies the study direction, but the available public metadata do not expose methods, validation or quantitative results. Methods, data and results could not be assessed because no reliable abstract was available.
153. Resampling-free jitter-aware bundle adjustment for HiRISE multi-CCD stereo mapping on Mars
Core Problem: Title-level focus: identifies the problem signaled by: Resampling-free jitter-aware bundle adjustment for HiRISE multi-CCD stereo mapping on Mars.
Key Innovation: Title-signalled approach or contribution: The title identifies the study direction, but the available public metadata do not expose methods, validation or quantitative results. Methods, data and results could not be assessed because no reliable abstract was available.
154. Multi-angular assessment of early-season defoliation: Evaluating the sensitivity of vegetation indices to NPV visibility in temperate broadleaved forests
Core Problem: Title-level focus: identifies the problem signaled by: Multi-angular assessment of early-season defoliation: Evaluating the sensitivity of vegetation indices to NPV visibility in temperate broadleaved forests.
Key Innovation: Title-signalled approach or contribution: The title identifies the study direction, but the available public metadata do not expose methods, validation or quantitative results. Methods, data and results could not be assessed because no reliable abstract was available.
155. Unsupervised soft-min fusion of multi-sensor turbidity products using Gaussian mixture models
Core Problem: Title-level focus: identifies the problem signaled by: Unsupervised soft-min fusion of multi-sensor turbidity products using Gaussian mixture models.
Key Innovation: Title-signalled approach or contribution: The title identifies the study direction, but the available public metadata do not expose methods, validation or quantitative results. Methods, data and results could not be assessed because no reliable abstract was available.
156. A Targeted-Refined Framework for wind turbine detection integrating AlphaEarth Foundations and high-resolution multispectral satellite imagery
Core Problem: Title-level focus: identifies the problem signaled by: A Targeted–Refined Framework for wind turbine detection integrating AlphaEarth Foundations and high-resolution multispectral satellite imagery.
Key Innovation: Title-signalled approach or contribution: The title identifies the study direction, but the available public metadata do not expose methods, validation or quantitative results. Methods, data and results could not be assessed because no reliable abstract was available.
157. Network analysis and GMM-informed machine learning for scale-dependent soil quality assessment in a Mollisol watershed
Core Problem: Title-level focus: identifies the problem signaled by: Network analysis and GMM-informed machine learning for scale-dependent soil quality assessment in a Mollisol watershed.
Key Innovation: Title-signalled approach or contribution: The title identifies the study direction, but the available public metadata do not expose methods, validation or quantitative results. Methods, data and results could not be assessed because no reliable abstract was available.
158. Characteristics of saturated hydraulic conductivity in sloping farmland soils: interactive effects of rock fragments and enclosure walls
Core Problem: Title-level focus: identifies the problem signaled by: Characteristics of saturated hydraulic conductivity in sloping farmland soils: interactive effects of rock fragments and enclosure walls.
Key Innovation: Title-signalled approach or contribution: The title identifies the study direction, but the available public metadata do not expose methods, validation or quantitative results. Methods, data and results could not be assessed because no reliable abstract was available.
159. Modelling delayed smoke ventilation induced by jet fans for performance-based design of tunnel fire safety
Core Problem: Title-level focus: identifies the problem signaled by: Modelling delayed smoke ventilation induced by jet fans for performance-based design of tunnel fire safety.
Key Innovation: Title-signalled approach or contribution: The title identifies the study direction, but the available public metadata do not expose methods, validation or quantitative results. Methods, data and results could not be assessed because no reliable abstract was available.
160. Effect of altitude on the propagation of overpressure and temperature at explosion shock wave fronts in long straight tunnels
Core Problem: Title-level focus: identifies the problem signaled by: Effect of altitude on the propagation of overpressure and temperature at explosion shock wave fronts in long straight tunnels.
Key Innovation: Title-signalled approach or contribution: The title identifies the study direction, but the available public metadata do not expose methods, validation or quantitative results. Methods, data and results could not be assessed because no reliable abstract was available.
161. Numerical study on the ventilation performance of emergency ventilation strategies for platform fire at a subway transfer station
Core Problem: Title-level focus: identifies the problem signaled by: Numerical study on the ventilation performance of emergency ventilation strategies for platform fire at a subway transfer station.
Key Innovation: Title-signalled approach or contribution: The title identifies the study direction, but the available public metadata do not expose methods, validation or quantitative results. Methods, data and results could not be assessed because no reliable abstract was available.
162. A state-of-the-art review: structural performance of prefabricated underground facilities under blast and fire loads
Core Problem: Title-level focus: identifies the problem signaled by: A state-of-the-art review: structural performance of prefabricated underground facilities under blast and fire loads.
Key Innovation: Title-signalled approach or contribution: The title identifies the study direction, but the available public metadata do not expose methods, validation or quantitative results. Methods, data and results could not be assessed because no reliable abstract was available.
163. Decoupled quantification of heat release rate and longitudinal ventilation velocity in tunnel fires based on machine vision
Core Problem: Title-level focus: identifies the problem signaled by: Decoupled quantification of heat release rate and longitudinal ventilation velocity in tunnel fires based on machine vision.
Key Innovation: Title-signalled approach or contribution: The title identifies the study direction, but the available public metadata do not expose methods, validation or quantitative results. Methods, data and results could not be assessed because no reliable abstract was available.
164. Multi-objective optimization of best management practices in agricultural watersheds using single-step deep reinforcement learning
Core Problem: Title-level focus: identifies the problem signaled by: Multi-objective optimization of best management practices in agricultural watersheds using single-step deep reinforcement learning.
Key Innovation: Title-signalled approach or contribution: The title identifies the study direction, but the available public metadata do not expose methods, validation or quantitative results. Methods, data and results could not be assessed because no reliable abstract was available.
165. DEM investigation of geogrid location effects on the depth-dependent micromechanical behavior of loose railway ballast
Core Problem: Title-level focus: identifies the problem signaled by: DEM investigation of geogrid location effects on the depth-dependent micromechanical behavior of loose railway ballast.
Key Innovation: Title-signalled approach or contribution: The title identifies the study direction, but the available public metadata do not expose methods, validation or quantitative results. Methods, data and results could not be assessed because no reliable abstract was available.
166. Lithology-specific morphological characterization and constraint-based spherical harmonic generation of Chang’e-6 Lunar Regolith particles
Core Problem: Title-level focus: identifies the problem signaled by: Lithology-specific morphological characterization and constraint-based spherical harmonic generation of Chang’e-6 Lunar Regolith particles.
Key Innovation: Title-signalled approach or contribution: The title identifies the study direction, but the available public metadata do not expose methods, validation or quantitative results. Methods, data and results could not be assessed because no reliable abstract was available.
167. Development and seismic evaluation of ECC-CFRP composite concrete shear walls
Core Problem: Title-level focus: identifies the problem signaled by: Development and seismic evaluation of ECC–CFRP composite concrete shear walls.
Key Innovation: Title-signalled approach or contribution: The title identifies the study direction, but the available public metadata do not expose methods, validation or quantitative results. Methods, data and results could not be assessed because no reliable abstract was available.
168. Deployment of a damage diagnosis model for offshore jacket platforms in embedded systems
Core Problem: Title-level focus: identifies the problem signaled by: Deployment of a damage diagnosis model for offshore jacket platforms in embedded systems.
Key Innovation: Title-signalled approach or contribution: The title identifies the study direction, but the available public metadata do not expose methods, validation or quantitative results. Methods, data and results could not be assessed because no reliable abstract was available.
169. Methodology for the characterisation of a hydraulic flume using acoustic Doppler velocimetry
Core Problem: Title-level focus: identifies the problem signaled by: Methodology for the characterisation of a hydraulic flume using acoustic Doppler velocimetry.
Key Innovation: Title-signalled approach or contribution: The title identifies the study direction, but the available public metadata do not expose methods, validation or quantitative results. Methods, data and results could not be assessed because no reliable abstract was available.
170. A hybrid Fuzzy-PSO framework for across-track radiometric beam pattern extraction from multi-sector multibeam backscatter
Core Problem: Title-level focus: identifies the problem signaled by: A hybrid Fuzzy–PSO framework for across-track radiometric beam pattern extraction from multi-sector multibeam backscatter.
Key Innovation: Title-signalled approach or contribution: The title identifies the study direction, but the available public metadata do not expose methods, validation or quantitative results. Methods, data and results could not be assessed because no reliable abstract was available.
171. Spectrum-regularized deep learning with joint wave parameter prediction for sea state estimation from ship motions
Core Problem: Title-level focus: identifies the problem signaled by: Spectrum-regularized deep learning with joint wave parameter prediction for sea state estimation from ship motions.
Key Innovation: Title-signalled approach or contribution: The title identifies the study direction, but the available public metadata do not expose methods, validation or quantitative results. Methods, data and results could not be assessed because no reliable abstract was available.
172. Particle-Laden Flow Induced Erosion of a Subsea Contra-Rotating Compressor under Inlet Distortion
Core Problem: Title-level focus: identifies the problem signaled by: Particle-Laden Flow Induced Erosion of a Subsea Contra-Rotating Compressor under Inlet Distortion.
Key Innovation: Title-signalled approach or contribution: The title identifies the study direction, but the available public metadata do not expose methods, validation or quantitative results. Methods, data and results could not be assessed because no reliable abstract was available.
173. Ego-State-Guided Vision-Radar Fusion for Robust Water-Surface Object Detection in Unmanned Surface Vehicles
Core Problem: Title-level focus: identifies the problem signaled by: Ego-State-Guided Vision–Radar Fusion for Robust Water-Surface Object Detection in Unmanned Surface Vehicles.
Key Innovation: Title-signalled approach or contribution: The title identifies the study direction, but the available public metadata do not expose methods, validation or quantitative results. Methods, data and results could not be assessed because no reliable abstract was available.
174. Development of a partitioned Simulink-LS-DYNA co-simulation framework for dynamic response and plastic damage analysis of floating offshore wind turbines
Core Problem: Title-level focus: identifies the problem signaled by: Development of a partitioned Simulink–LS-DYNA co-simulation framework for dynamic response and plastic damage analysis of floating offshore wind turbines.
Key Innovation: Title-signalled approach or contribution: The title identifies the study direction, but the available public metadata do not expose methods, validation or quantitative results. Methods, data and results could not be assessed because no reliable abstract was available.
175. GeoMF: A Geographic Context-Aware Multimodal Framework for Fine-Grained Ship Classification
Core Problem: Title-level focus: identifies the problem signaled by: GeoMF: A Geographic Context-Aware Multimodal Framework for Fine-Grained Ship Classification.
Key Innovation: Title-signalled approach or contribution: The title identifies the study direction, but the available public metadata do not expose methods, validation or quantitative results. Methods, data and results could not be assessed because no reliable abstract was available.
176. LSOAF-YOLO: A Lightweight Small Object Detector with Attention Fusion for Aerial Remote Sensing Imagery
Core Problem: Title-level focus: identifies the problem signaled by: LSOAF-YOLO: A Lightweight Small Object Detector with Attention Fusion for Aerial Remote Sensing Imagery.
Key Innovation: Title-signalled approach or contribution: The title identifies the study direction, but the available public metadata do not expose methods, validation or quantitative results. Methods, data and results could not be assessed because no reliable abstract was available.
177. Road Debris Detection Using Differential Phase Contrast in W-band SAR
Core Problem: Title-level focus: identifies the problem signaled by: Road Debris Detection Using Differential Phase Contrast in W-band SAR.
Key Innovation: Title-signalled approach or contribution: The title identifies the study direction, but the available public metadata do not expose methods, validation or quantitative results. Methods, data and results could not be assessed because no reliable abstract was available.
178. A Scalable and Reproducible Framework for Per-Pixel Demographic Estimation in the Legal Brazilian Amazon Using Minimal Spatial Data
Core Problem: Title-level focus: identifies the problem signaled by: A Scalable and Reproducible Framework for Per-Pixel Demographic Estimation in the Legal Brazilian Amazon Using Minimal Spatial Data.
Key Innovation: Title-signalled approach or contribution: The title identifies the study direction, but the available public metadata do not expose methods, validation or quantitative results. Methods, data and results could not be assessed because no reliable abstract was available.
179. A Chromaticity Baseline Height Index and Sliding Window Iterative Thresholding for Automatic Harmful Algal Bloom Extraction
Core Problem: Title-level focus: identifies the problem signaled by: A Chromaticity Baseline Height Index and Sliding Window Iterative Thresholding for Automatic Harmful Algal Bloom Extraction.
Key Innovation: Title-signalled approach or contribution: The title identifies the study direction, but the available public metadata do not expose methods, validation or quantitative results. Methods, data and results could not be assessed because no reliable abstract was available.
180. A Growth-Prior-Informed Forest Age Estimation Method Using Overlapping ICESat/GLAS and GEDI Footprints with Reduced Dependence on Field Calibration Data
Core Problem: Title-level focus: identifies the problem signaled by: A Growth-Prior-Informed Forest Age Estimation Method Using Overlapping ICESat/GLAS and GEDI Footprints with Reduced Dependence on Field Calibration Data.
Key Innovation: Title-signalled approach or contribution: The title identifies the study direction, but the available public metadata do not expose methods, validation or quantitative results. Methods, data and results could not be assessed because no reliable abstract was available.
181. FD-MCNet: A Frequency-Decoupled Mamba-CNN Network for Infrared Small Target Detection
Core Problem: Title-level focus: identifies the problem signaled by: FD-MCNet: A Frequency-Decoupled Mamba-CNN Network for Infrared Small Target Detection.
Key Innovation: Title-signalled approach or contribution: The title identifies the study direction, but the available public metadata do not expose methods, validation or quantitative results. Methods, data and results could not be assessed because no reliable abstract was available.
182. LizardNet: Lizard Connectome-Inspired Network for Fast Few-shot Hyperspectral Classification
Core Problem: Title-level focus: identifies the problem signaled by: LizardNet: Lizard Connectome-Inspired Network for Fast Few-shot Hyperspectral Classification.
Key Innovation: Title-signalled approach or contribution: The title identifies the study direction, but the available public metadata do not expose methods, validation or quantitative results. Methods, data and results could not be assessed because no reliable abstract was available.