Search Results (867)

Boaters use class ratings to describe whitewater difficulty on a scale from I to VI, with ratings assigned and refined through the judgment of experienced boaters. These practices are effective, but the addition of physical measurements could improve their reliability and facilitate whitewater comparisons across different rivers and flows. This exploratory study considers specific stream power (SSP), a physics-based metric describing energy transfer in rivers, as an indicator of whitewater difficulty. Data were collected at eight study sites on the Upper Deschutes River in Oregon using a camera-mounted DJI Phantom 4 RTK quadcopter. Sites were assessed at one or two flows and whitewater difficulty ranged from Class I flatwater to Class V cascading rapids. Stream slope and width data were derived from a combination of unmanned aerial vehicle (UAV) photogrammetry and aerial light detection and ranging (LiDAR), and SSP was calculated for each site. Whitewater class ratings were strongly associated (df = 6, p < 0.05) with site average SSP, r_s= 0.95, 95% CI [0.72, 1.00], site average slope, r_s = 0.95, 95% CI [0.72, 1.00], and within-site maximum SSP, r_s = 0.93, 95% CI [0.58, 1.00]. The within-site maximum slope, minimum width, and constriction ratio had significant but smaller relationships. Physical assessments of whitewater conditions may help support management decisions in dam removal, hydropower relicensing, or other instream flow negotiations. Full article

This paper investigates hazard assessment and mitigation measures for rainfall-induced debris flow at a highway tunnel portal in Guangdong, China. The tunnel is situated at the outlet of a steep gully with a channel length of 2.38 km, an elevation difference of 682 m, and a gradient of 23.4%. Under extreme rainfall conditions, the portal faces severe risks of scouring and inundation that threaten the structural safety and operational stability of the highway. A high-resolution digital elevation model was established via UAV oblique photogrammetry, and debris flow processes were simulated using HEC-RAS 6.4. The hydrologic behavior under 20-year, 50-year, and 100-year recurrence intervals is first investigated in the research area. After that, the Bingham flow model is used for the debris flow simulation. Results show that as the return period increases from 20 to 100 years, the maximum flow depth at the tunnel portal rises from 1.92 to 2.21 m and the maximum flow velocity rises from 5.8 to 7.8 m/s, indicating that flow velocity is more sensitive to rainfall intensity than flow depth. These simulated flow depths far exceed the 0.5 m flood level stipulated in the Chinese highway tunnel design code, indicating a serious threat to tunnel safety. Based on a quantitative comparison between single-dam and multi-dam schemes, a multi-dam combination with different heights at four positions along the gully is proposed for segmented interception. This multi-dam scheme successfully reduces the flow depth at the tunnel portal to zero without requiring any individual dam to exceed 10 m in height, demonstrating a favorable balance between engineering feasibility and disaster mitigation effectiveness. Full article

Climate-related and environmental hazards affect cultural heritage sites in markedly different inland, coastal, lacustrine and underwater settings, creating documentation requirements that cannot be addressed by a single sensing approach. This study presents the multi-sensor geometric documentation of eight cultural heritage sites. Unmanned aerial vehicle (UAV) photogrammetry was applied to six inland and coastal sites, while underwater photogrammetry, unmanned surface vehicles (USVs), acoustic sounding and a prototype green-wavelength flash LiDAR were used at three shallow-water sites. The campaigns produced orthomosaics, elevation models, dense point clouds, textured meshes, bathymetric maps and underwater LiDAR point clouds at scales appropriate to the conservation problem of each site. The resulting products document exposed architectural remains, excavation areas, cliffs and unstable slopes, lake-margin changes, submerged masonry, wooden structures and lakebed morphology. Their main contribution is the establishment of spatially explicit, site-specific baselines that provide measurable geometric and visual evidence for condition assessment, future repeat-survey comparisons and the spatial integration of environmental, archaeological and conservation information. The study demonstrates the operational and information complementarity of optical, acoustic and active ranging approaches, which address different documentation scales, environmental constraints and heritage targets, and provide distinct spatial evidence that can serve as potential inputs to subsequent digital twin and decision support applications. Full article

The 3D geometric documentation of cultural heritage monuments requires spatial datasets that are accurate, complete and suitable for conservation, monitoring, visualization and heritage management. However, complex geometries, occlusions, limited accessibility, vegetation and other field-acquisition constraints often prevent a single surveying technique from providing a complete and metrically reliable representation. In this context, photogrammetry and simultaneous localization and mapping (SLAM)-based mapping provide complementary capabilities, with each method offering advantages and limitations regarding metric accuracy, spatial coverage, detail representation, acquisition flexibility and operational efficiency. This work develops, applies and evaluates a reproducible end-to-end workflow for the metric 3D documentation of complex cultural heritage monuments through multi-sensor integration. The proposed approach combines the metric robustness and visual richness of photogrammetric reconstruction with the rapid acquisition and spatial coverage enabled by SLAM-based mapping, while producing reusable datasets for conservation planning, comparative studies, education and broader heritage applications. The workflow integrates unmanned aerial vehicle (UAV) and close-range photogrammetry, SLAM-based mapping and geodetic control within a common reference system and is demonstrated through the documentation of a historic monastery. Both datasets showed centimetre-level agreement with geodetic observations, while photogrammetry yielded fuller exterior coverage and higher-quality texture, and SLAM enabled rapid interior coverage. The CH-PhotoSLAM3D dataset is released to support reproducibility and further research. Full article

Traditional dwellings in humid subtropical China contain climate-adaptive spatial elements, yet their outdoor thermal-comfort performance and passive optimization potential remain insufficiently quantified. This study examined three traditional Minnan mansions in Quanzhou, Fujian Province, to evaluate how courtyards, alleyways, recessed entrance spaces, and peripheral vegetation regulate summer outdoor thermal environments. Field microclimate monitoring, UAV photogrammetry, and ENVI-met/BioMet simulations were combined, and baseline models were validated using measured air temperature and relative humidity data. Single-element scenarios were developed for ground albedo adjustment, courtyard shading, alleyway green pergolas, recessed entrance shading, increased fengshui woodland density, and optimized woodland layout, followed by multi-element combined strategies. The results indicate that shading and vegetation-related measures reduced daytime heat stress primarily by limiting solar radiation exposure, improving near-ground thermal and humidity conditions, and modifying local wind fields. Combined strategies produced more stable UTCI improvements than individual interventions, with a maximum UTCI reduction of 7.5 °C. In contrast, high-albedo paving reduced local air temperature but could worsen UTCI by increasing reflected short-wave radiation. These findings provide quantitative support for low-intervention thermal environment optimization and climate-adaptive renewal of traditional dwellings in humid–hot regions. Full article

Reliable stability assessment of structurally complex rock masses increasingly relies on advanced remote sensing techniques integrated with detailed geotechnical analysis. This study presents a combined remote geotechnical workflow applied to rock masses surrounding natural cavities, with the study area located in Greece, aiming to evaluate the stability of coupled cavity–slope systems under varying conditions. The methodology combines Unmanned Aerial Vehicle (UAV) photogrammetry and SLAM-based LiDAR surveying to acquire centimetre-scale surface and underground opening data. These datasets are fused into a geometrically consistent three-dimensional representation of the slope–portal–cavity system, enabling improved documentation of slope morphology, internal cave geometry and externally exposed discontinuity patterns. The fused spatial dataset was then used to extract a representative two-dimensional cavity–slope section for plane-strain finite element analysis. The numerical model was formulated as an equivalent-continuum model using the Hoek–Brown failure criterion, with stability assessed through the Shear Strength Reduction technique across multiple scenarios. Overall, the study demonstrates that integrated geotechnical and remote-sensing approaches improve geometric completeness and consistency, enhance reproducibility, and reduce geometry-related uncertainty in scenario-based stability assessments of complex rock masses with natural cavities and underground openings. Full article

The Buyeo Royal Tombs in Neungsan-ri represent a royal funerary complex of the Baekje Sabi period (A.D. 538–660) and form an important cultural landscape reflecting the spatial organization of the Sabi capital. As part of the Baekje Historic Areas inscribed on the World Heritage List, the site holds significant historical and spatial value. However, the present terrain differs substantially from its historical configuration due to extensive maintenance works conducted in 1966, including ground leveling, artificial embankment construction, and partial relocation of burial mounds. These modifications have obscured the original topographic context of the royal cemetery. In this study, we reconstruct the former terrain of the Buyeo Royal Tombs through the integration of historical maps, aerial photographs, archeological excavation data, and contemporary spatial datasets. To overcome methodological limitations regarding historical map accuracy, a rigorous three-stage backward georeferencing procedure utilizing Helmert and Thin-Plate Spline (TPS) transformations was applied. Airborne light detection and ranging (LiDAR) and unmanned aerial vehicle (UAV)-based photogrammetry were newly acquired primarily to permanently archive the current state of the heritage site and provide an absolute geometric baseline. The reconstructed terrain approximates the landscape prior to modern interventions and enables analysis of the spatial organization of the royal cemetery. The results indicate that the Neungsan-ri royal tombs were strategically located on visually prominent south-facing slopes outside the Sabi capital, reflecting deliberate spatial planning and funerary ideology. This study provides a methodological reference for digital cultural landscape research and supports future heritage conservation and reconstruction planning. Full article

Coastal plains are low-relief environments where subtle topographic variations govern sedimentary processes, landscape structure, and hydrological dynamics. Along the southeastern Brazilian coast, barrier–lagoon systems record Quaternary coastal evolution and sea-level oscillations; however, detailed mapping of these environments is constrained by the spatial resolution of conventional cartographic bases. This study presents high-resolution morphological mapping of the Maricá coastal plain (Rio de Janeiro State, Brazil) based on digital elevation models (DEMs) derived from UAV photogrammetry, combined with geomorphological interpretation following the IBGE classification framework. The DEM resolved subtle altimetric variations associated with beach ridges and relict lagoonal depressions not represented in conventional topographic maps, providing a surface proxy for the underlying stratigraphic architecture. UAV-derived elevation models significantly improve the identification of morphological units in low-relief coastal environments, establishing a spatial framework for future stratigraphic investigations along the southeastern Brazilian coast. Full article

Reservoir impoundment can reactivate pre-existing landslides and reorganize slope topography, thereby changing seepage conditions and subsequent deformation. However, crack mapping, geomorphic interpretation, and hydrodynamic diagnosis are still often treated as separate tasks. This study investigates the Hemenkou (HMK) landslide in the Wudongde Reservoir area, China, using multi-scale space–air–ground observations, including multi-temporal optical satellite images, unmanned aerial vehicle (UAV) photogrammetry, pyramid scene parsing network (PSPNet)-based crack segmentation, global navigation satellite system (GNSS) monitoring, and convergent cross mapping (CCM). The remote sensing record shows a progressive damage sequence: cracks were mainly restricted to the upper source area in 2012, crown cracking intensified and propagated downslope by December 2020, and the UAV survey of 10 June 2024 revealed a mature tension-crack network concentrated in Zone II. ResNet-50-PSPNet achieved the best crack-extraction performance among the tested models, with Precision = 0.9120, Recall = 0.9041, F1 = 0.9081, and IoU = 0.8316. The mapped cracks are dominated by short, narrow, northeast–southwest-oriented tension cracks. GNSS monitoring reveals strong spatial heterogeneity, with stepwise deformation concentrated in Zone II. CCM provides strong directional evidence for the influence of reservoir water-level fluctuation on Zone II deformation, whereas the weaker rainfall signal is consistent with a secondary reinforcing role. The apparent increase in the rainfall-related CCM signal from 2021 to 2023 is consistent with progressive crack expansion and potentially enhanced hydraulic connectivity in Zone II. Taken together, these observations support the interpretation that post-deformation topography, particularly the tension-crack network and disturbed toe, may organise preferential seepage pathways and increase the sensitivity of the landslide to reservoir drawdown. The study provides an integrated remote sensing and monitoring framework for process-based interpretation of reservoir landslides. Full article

Continental shale reservoirs exhibit pronounced multi-scale heterogeneity, with reservoir quality governed by the interplay of lamina assemblages, bedding continuity, and lithological spatial variability. Conventional digital outcrop modeling (DOM) primarily targets geometric reconstruction and three-dimensional (3D) visualization of sedimentary bodies, which is insufficient for the fine-scale structural characterization and quantitative modeling required for shale reservoirs. Here we present a Digital Shale Outcrop Modeling method (DSOM) tailored to continental shale reservoirs, exemplified by the Gulong Shale in the Qingshankou Formation (Upper Cretaceous) of the Songliao Basin, northeastern China. DSOM integrates six sequential modules: digital outcrop reconstruction, digital section interpretation, virtual well construction, virtual well correlation, 3D structural modeling, and parameter extraction. A high-precision digital outcrop model covering 0.369 km² was constructed from 1885 calibrated UAV images (DJI Mavic 3 Enterprise) using Structure-from-Motion (SfM) photogrammetry, yielding derived products including a digital outcrop model (DOM), digital surface model (DSM), digital elevation model (DEM), orthomosaic, and dense point cloud. Seven virtual wells were extracted along the outcrop strike, and a unified lithological classification comprising seven lithotypes was established. A regionally persistent rusty-yellow ferruginous siltstone layer served as a marker bed for virtual well correlation. Results reveal a distinct vertical lithological transition: the section above the marker bed is dominated by muddy deposits, with black mudstone and dark-gray silty mudstone collectively accounting for 52.84% of the total area, whereas the section below the marker bed exhibits a marked increase in silt-grade material, with gray siltstone reaching 32.78%. This vertical evolution reflects a depositional shift from relatively high-energy to low-energy conditions. Using the virtual wells as conditioning data, 3D lithological probability models for all seven lithotypes were constructed via Sequential Indicator Simulation (SIS), achieving quantitative representation of lithological spatial distribution and lateral variability under bedding constraints. Our results demonstrate that DSOM effectively converts outcrop digital information into reservoir structural data, providing reliable constraints for multi-scale structural characterization, 3D geological modeling, and heterogeneity evaluation of the Gulong Shale. More broadly, DSOM establishes a methodological framework for digital characterization of fine-grained sedimentary reservoirs, bridging the gap between outcrop-scale observations and subsurface reservoir modeling. Full article

Automated airport pavement inspection requires reliable instance segmentation models for detecting and quantifying thin cracks under real operating conditions. Building on a previously established UAV-AI workflow for airport pavement crack detection and quantification, and on an earlier investigation of sealed-crack class definition using YOLO11, the present study addresses a subsequent research question by comparing two recent model configurations based on fundamentally different computer vision paradigms. YOLO26 was selected for its deployment-oriented convolutional architecture, computational efficiency, and mechanisms aimed at improving small-target handling, whereas RF-DETR was selected for its transformer-based architecture and DINOv2-pretrained backbone; these provide fine-grained visual representations and exploit broader contextual information. The two configurations were assessed using the same dataset of 24,768 annotated images and compared in terms of computational demands, independent test-set performance, and field-based crack length reliability. Field validation was performed on two airport taxiways representing different surface conditions: taxiway Nibbio, mainly affected by active longitudinal and transverse cracks with limited interference from sealed cracks, and taxiway November, characterized by the coexistence of active and sealed cracking patterns. YOLO26 showed a lower computational demand, requiring approximately one hour and 20 compute units, compared with approximately six hours and 80 compute units for RF-DETR. RF-DETR achieved a higher mAP50 and recall on the test set and lower model error index values on both taxiways, indicating better crack length recovery. However, on taxiway November, it also showed higher hallucination index values, revealing greater sensitivity to visually ambiguous sealed cracks. These findings indicate that model selection should consider pavement surface conditions, computational constraints, and the operational consequences of missed cracks and false-positive detections. The specific contribution of the present study is therefore the extension of the previously established UAV-AI framework from workflow development and class definition analysis to the comparative evaluation of recent convolutional and transformer-based model configurations under real airport pavement conditions. Full article

Traditional rural landscape evaluations have generally relied on ground-level photographs or videos. However, these approaches have limitations in spatial continuity, depth cues, and interactivity. Unmanned Aerial Vehicle (UAV) photogrammetry and immersive virtual reality (VR) were integrated into a comparative rural landscape evaluation framework to assess landscape aesthetic quality. UAV-derived 3D village models were generated and deployed on PICO 4 headsets through Unity 3D and the Cesium plugin, providing evaluators with spatially continuous and 6DoF-enabled immersive representations of village scenes. The evaluation included ten landscape feature factors, including color harmony, vegetation richness, building layout harmony, openness of view, and sense of spatial depth. Ratings were collected from 75 valid participants across 17 villages, with village-level mean scores serving as the primary unit of inference. Paired-samples t-tests, subgroup sensitivity analysis, expert-only presentation-order sensitivity analysis, Pearson correlations, Steiger tests for dependent correlations, stepwise multiple linear regression, nested leave-one-village-out cross-validation (LOOCV), and bootstrap variable-selection stability analysis were conducted to examine differences between the 2D photo-based and VR-based conditions. The results showed that: (1) overall satisfaction was significantly higher in the VR-based condition than in the 2D photo-based condition (3.46 vs. 3.24); (2) the condition-specific regression models retained different landscape feature factors: sense of spatial depth and color harmony in the 2D photo-based model, and vegetation distribution pattern and environmental comfort in the VR-based model; and (3) the VR-based regression model had a higher condition-specific internal $R^2$ than the 2D photo-based model ($R^2=0.784$ vs. 0.569). Within the present dataset, the VR-based model also showed lower SD-normalized prediction error under nested LOOCV, while bootstrap resampling showed higher selection frequencies for the predictors retained in the VR-based model. Overall, the findings demonstrate the potential of UAV-derived immersive VR for rural landscape evaluation and provide new evidence on how presentation conditions influence landscape perception and evaluation. Full article

On 18 May 2026, a M5.2 double earthquake struck the Taiyangzhen area of Liunan District, Liuzhou City, Guangxi, China, triggering shallow surface collapses in this karst terrain. We conducted three UAV orthophoto surveys of the meizoseismal area on 20 May, 23 May, and 24 May, and interpreted 17 collapse monitoring units from the imagery. The total collapse area increased from 75.3 m² on 20 May to 499.1 m² on 23 May, and further to 553.9 m² on 24 May. On 20 May, only 7 of 17 units exhibited collapses; by 23 May, all 17 units were affected. Among them, 7 pre-existing collapse patches expanded, and 10 new collapses emerged between 20 and 23 May. Depth measurements revealed measurable depths of 0.18–7.60 m for 7 collapses, and all 6 units with bi-temporal depth data showed continued deepening from 23 to 24 May. Ponding water was observed in up to 10 units, consistent with the 98.7 mm of rainfall recorded during 18–24 May. Multi-temporal UAV surveys reveal that post-seismic surface collapse development in karst terrain extends well beyond the mainshock, with both rapid expansion of pre-existing failures and delayed emergence of new collapses driven by the coupled effects of seismic weakening and hydrologic forcing. Full article

The spatial distribution of ground control points (GCPs) is a critical factor affecting the accuracy of UAV photogrammetry in hilly terrain. In existing studies on GCP distribution, researchers have largely focused on planar uniformity metrics in flat terrain or on the effects of flight parameters in mountainous areas, with limited attention to the distinct roles of horizontal and vertical placement. In this study, we utilized a consumer-grade RTK-equipped UAV to acquire aerial imagery in a typical hilly area, with 27 high-precision GCPs deployed as a reference dataset. Four comparative experiments combining random/uniform distributions in both horizontal and vertical dimensions were designed to quantitatively analyze the impact of different distribution patterns on aerial triangulation and mapping accuracy. Our results demonstrate that the dual-uniform distribution strategy (i.e., uniform in both planimetric layout and elevation stratification) achieves the highest accuracy among the four tested configurations, with horizontal RMSE of 0.045 m and vertical RMSE of 0.039 m. Furthermore, we propose the Spatial Distribution Balance Index (SDBI), which integrates the Planar Uniformity Index (PUI) and Vertical Uniformity Index (VUI) with a terrain-adaptive weighting mechanism. The VUI weight, exemplified as β = 0.714 for this study area via a Sigmoid nonlinear amplification function (k = 15, x₀ = 0.15), enables the SDBI to adaptively reflect terrain sensitivity to vertical control. The enhanced SDBI exhibits a correlation coefficient of r = −0.93 with final accuracy, validating its effectiveness as a GCP layout evaluation tool. In this study, we establish the SDBI as a diagnostic metric that quantitatively links GCP distribution characteristics to photogrammetric accuracy outcomes, providing both theoretical insights into anisotropic error propagation and practical guidance for deployment design in hilly regions. Full article

Steep rock slopes are widely distributed in the karst mountainous regions of southwestern China, where structurally controlled rockfalls frequently threaten transportation infrastructure and human safety. Accurate identification of unstable rock blocks (URs) and quantitative assessment of their post-failure hazards remain major challenges because of complex discontinuity networks and fragmentation during rockfall motion. Taking the Zuojiaying steep rock slope in Guizhou Province as a representative case, this study integrates high-resolution UAV photogrammetry, automatic discontinuity identification, unstable rock block detection, and three-dimensional rockfall simulation to investigate the formation mechanisms and hazard characteristics of discontinuity-controlled rockfalls. A high-resolution three-dimensional terrain model was reconstructed from UAV imagery, and six dominant discontinuity sets were automatically identified using the I-MinPts-constrained DBSCAN algorithm. Combined with the Rock Occurrence Kinematic Analysis (ROKA) algorithm and Block Theory, 54 unstable rock blocks were identified, with wedge failure and toppling failure representing the dominant instability modes. The results indicate that discontinuity combinations govern both rock mass segmentation and unstable rock block geometry. Specifically, discontinuity sets J1, J3, and J5 mainly control wedge-shaped blocks, and J2 and J4 dominate columnar toppling blocks, whereas J6 further promotes the formation of isolated unstable rock blocks. Three-dimensional RockGIS simulations considering fragmentation reproduced the complete rockfall process from detachment to final deposition. The maximum travel distance, kinetic energy, and bounce height reached 395 m, 748.5 kJ, and 40.1 m, respectively. Fragmentation increased the number of rock blocks from 54 to 1013, substantially enlarging the potential impact area. A raster-based Rockfall Hazard Index (RHI) further revealed that the middle–lower slope and slope toe constitute the principal high-hazard zones, and under extreme scenarios, high-energy fragments may reach the G246 National Highway and adjacent infrastructure. This study revealed the formation mechanisms and hazard characteristics of unstable rock blocks controlled by discontinuity combinations in the study area, providing a case reference for rockfall hazard identification and mitigation on similar high-steep rock slopes in karst mountainous regions. Full article