Search Results (401)

This research aims to develop a novel technique to acquire a large amount of high-density, high-precision 3D point cloud data for plant phenotyping using photogrammetry technology. The complexity of plant structures, characterized by overlapping thin parts such as leaves and stems, makes it difficult to reconstruct accurate 3D point clouds. One challenge in this regard is occlusion, where points in the 3D point cloud cannot be obtained due to overlapping parts, preventing accurate point capture. Another is the generation of erroneous points in non-existent locations due to image-matching errors along object outlines. To overcome these challenges, we propose a 3D point cloud reconstruction method named closed-loop coarse-to-fine method with multi-masked matching (CLCFM3). This method repeatedly executes a process that generates point clouds locally to suppress occlusion (multi-matching) and a process that removes noise points using a mask image (masked matching). Furthermore, we propose the closed-loop coarse-to-fine method (CLCFM) to improve the accuracy of structure from motion, which is essential for implementing the proposed point cloud reconstruction method. CLCFM solves loop closure by performing coarse-to-fine camera position estimation. By facilitating the acquisition of high-density, high-precision 3D data on a large number of plant bodies, as is necessary for research activities, this approach is expected to enable comparative analysis of visible phenotypes in the growth process of a wide range of plant species based on 3D information. Full article

Accurate stockpile volume estimation is essential for industries that manage bulk materials across various stages of production. Conventional ground-based methods such as walking wheels, total stations, Global Navigation Satellite Systems (GNSSs), and Terrestrial Laser Scanners (TLSs) have been widely used, but often involve significant safety risks, particularly when accessing hard-to-reach or hazardous areas. Unmanned Aerial Systems (UASs) provide a safer and more efficient alternative for surveying irregularly shaped stockpiles. This study evaluates UAS-based methods for estimating the volume of coal stockpiles at a storage facility near Cadiz, Ohio. Two sensor platforms were deployed: a Freefly Alta X quadcopter equipped with a Real-Time Kinematic (RTK) Light Detection and Ranging (LiDAR, active sensor) and a WingtraOne UAS with Post-Processed Kinematic (PPK) multispectral imaging (optical, passive sensor). Three approaches were compared: (1) LiDAR; (2) Structure-from-Motion (SfM) photogrammetry with a Digital Surface Model (DSM) and Digital Terrain Model (DTM) (SfM–DTM); and (3) an SfM-derived DSM combined with a kriging-interpolated DTM (SfM–intDTM). An automated boundary detection workflow was developed, integrating slope thresholding, Near-Infrared (NIR) spectral filtering, and Canny edge detection. Volume estimates from SfM–DTM and SfM–intDTM closely matched LiDAR-based reference estimates, with Root Mean Square Error (RMSE) values of 147.51 m³ and 146.18 m³, respectively. The SfM–intDTM approach achieved a Mean Absolute Percentage Error (MAPE) of ~2%, indicating strong agreement with LiDAR and improved accuracy compared to prior studies. A sensitivity analysis further highlighted the role of spatial resolution in volume estimation. While RMSE values remained consistent (141–162 m³) and the MAPE below 2.5% for resolutions between 0.06 m and 5 m, accuracy declined at coarser resolutions, with the MAPE rising to 11.76% at 10 m. This emphasizes the need to balance the resolution with the study objectives, geographic extent, and computational costs when selecting elevation data for volume estimation. Overall, UAS-based SfM photogrammetry combined with interpolated DTMs and automated boundary extraction offers a scalable, cost-effective, and accurate approach for stockpile volume estimation. The methodology is well-suited for both the high-precision monitoring of individual stockpiles and broader regional-scale assessments and can be readily adapted to other domains such as quarrying, agricultural storage, and forestry operations. Full article

Lump charcoal is used in various applications, with combustion performance reliant on physical properties including apparent density. Currently, apparent density is measured by liquid displacement using Archimedes’ principle, which can yield inconsistent results for porous, irregular materials. This study investigates structure-from-motion (SfM) photogrammetry as a non-destructive alternative for estimating the apparent density of lump charcoal. Ninety fragments from 15 commercial samples were analyzed. Mass was measured using an analytical balance, and volume was estimated independently via Archimedes’ method and photogrammetry. Apparent density was calculated as the ratio of mass to volume. Results showed strong agreement between the two methods. Mean density values ranged from 284.2 to 751.6 kg/m³ for photogrammetry and from 267.2 to 765.7 kg/m³ for Archimedes. No significant differences were found (Wilcoxon test, p > 0.05), and a strong correlation was observed (Spearman’s ρ = 0.94, p < 0.001). Photogrammetry also demonstrated low estimation errors, with a mean absolute error of 38.8 kg/m³, a percentage error of 9.9%, and a root mean squared error of 50.2 kg/m³. Beyond methodological innovation, this approach strengthens sustainability by supporting accurate fuel properties control, allowing better use of the resource and maximizes combustion efficiency. In this way, it contributes to United Nations Sustainable Development Goal 7 (SDG7) on affordable, reliable, and sustainable energy. Full article

Soil erosion is a critical ecological challenge in semi-arid regions of China, particularly in the Yellow River Basin, where Pisha sandstone slopes undergo rapid degradation. Rill erosion, driven by rainfall and overland flow, destabilizes slopes and accelerates ecosystem degradation. To address this, we developed a multi-view stereo observation system that integrates Structure-from-Motion (SFM) and multi-view stereo (MVS) for high-precision, dynamic monitoring of rill erosion. Laboratory rainfall simulations were conducted under four inflow rates (2–8 L/min), corresponding to rainfall intensities of 30–120 mm/h. The erosion process was divided into four phases: infiltration and particle rolling, splash and sheet erosion, incipient rill incision, and mature rill networks, with erosion concentrated in the middle and lower slope sections. The SFM-MVS system achieved planimetric and vertical errors of 3.1 mm and 3.7 mm, respectively, providing approximately 25% higher accuracy and nearly 50% faster processing compared with LiDAR and UAV photogrammetry. Infiltration stabilized at approximately 6.2 mm/h under low flows (2 L/min) but declined to less than 4 mm/h under high flows (≥6 L/min), leading to intensified rill incision and coarse-particle transport (up to 21.4% of sediment). These results demonstrate that the SFM-MVS system offers a scalable and non-invasive method for quantifying erosion dynamics, with direct implications for field monitoring, ecological restoration, and soil conservation planning. Full article

River-ice, a significant element of the cryosphere, plays a crucial role in hydrological processes. However, the effectiveness of current river-ice monitoring techniques on the Qinghai–Tibet Plateau is limited due to the complex interplay of environmental and topographical factors in this extensively ice-covered region. To overcome the inadequacies of traditional monitoring approaches in plateau settings, this research introduces a 4D-SfM photogrammetry method for river-ice monitoring. Experimental measurements of river-ice thickness were conducted on the upper reaches of the Heihe River in the Qilian Mountains during the freezing period of 2023–2024. The study evaluated accuracy variations across three different shooting distances: close-range (0.5 m–1.5 m), mid-range (3 m–10 m), and long-range (25 m–60 m). In this study, 4D-SfM photogrammetry not only accurately represents the nonlinear processes of river-ice formation and melting but also sensitively detects abrupt changes in thickness. Between 6 February and 4 April 2024, river-ice underwent a cumulative melt of 77.8 cm, followed by a cumulative growth of 72.2 cm between 26 November and 26 December 2024. Notably, between 24 and 25 December 2024, 4D-SfM photogrammetry successfully captured an extreme event in which river-ice thickness surged by approximately 30 cm. Measurement accuracy decreased with increasing shooting distance, as indicated by an increase in RMSE from 0.43 cm to 3.97 cm. Additionally, factors such as image brightness and ice surface irregularities significantly impact measurement precision. Moreover, the measurement area expanded from 11.38 m² to 2642 m² with increased shooting distances. Therefore, achieving a balance between shooting distance and measurement accuracy is essential when employing 4D-SfM photogrammetry for river-ice monitoring. This study provides a valuable resource for utilizing 4D-SfM photogrammetry to monitor river-ice thickness on the Qinghai–Tibet Plateau. Full article

The Oymaağaç Höyük Project (2005–today) investigates a 6,500-year-oldmulti-period settlement in the district of Vezirköprü at the southern edge of the Black Sea province of Samsun in northern Türkiye. According to cuneiform texts, the site can be associated with the Hittite cult city of Nerik (17th–12th century BC). Automatic multi-image photogrammetry, also known as Structure from Motion (SfM), has proven to be a powerful and flexible means for the three-dimensional documentation of objects and finds of different shapes and sizes. Data products were created in the form of 3D point clouds, textured surface models, orthophotos, sections, and 3D prints (physical 3D models). Visualization of 3D data was realized via an internet browser (Potree Viewer, Babylon.js) and virtual reality (VR) techniques. Photogrammetry is very flexible in its application because the accuracy depends essentially on the scale of the images. On the other hand, the constantly growing volume of data as a result of the evolving technical possibilities requires sustainable data management, which is difficult to realize in practice due to limited financial resources. The article provides an overview of the use of photogrammetry in the project. Full article

Structural traits of vegetation, derived from the three-dimensional distribution of plant elements, are closely linked to ecosystem functions such as productivity and habitat provision. While extensively studied in forest ecosystems, these traits remain understudied in low-stature systems such as Mediterranean-type shrublands. In this study we explore the use of structural metrics derived from small unmanned aerial system (UAS)-based 3D point clouds, generated using the structure-from-motion (SfM) photogrammetry technique, to assess post-fire vegetation structure and biodiversity in the fynbos biome of the Cape Floristic Region (CFR), South Africa. Fynbos is a fire-adapted shrubland that represents nearly 80% of plant species in the CFR, making post-disturbance monitoring critical for conservation. We extracted three structural metrics—canopy height, top rugosity, and surface gap ratio—and achieved ~85% accuracy in classifying 5 × 5 m subplots by burn year using a Multi-Layer Perceptron (MLP), with canopy height as the strongest predictor. Additionally, top rugosity and gap ratio significantly contributed to modeling percentage cover-based species diversity. Our findings demonstrate that UAS-derived structural metrics provide valuable information for characterizing vegetation recovery and biodiversity patterns in low-stature, fire-prone ecosystems. This approach can support ecological monitoring and inform conservation strategies in Mediterranean-type shrublands. Full article

The ecological impact of crown-of-thorns starfish (CoTS; Acanthaster spp.) on coral reefs is intrinsically linked to their feeding behaviour. Management thresholds designed to mitigate coral loss driven by elevated densities of crown-of-thorns starfish rely on accurate estimates of individual feeding rates. In this study, structure-from-motion photogrammetry and intensive tracking of adult Pacific CoTS over an extended survey period were used to generate three-dimensional, high-resolution estimates of daily feeding rates. Our findings revealed substantial variation in the areal extent of coral consumed, both across consecutive days and among individuals. Notably, CoTS did not feed consistently; feeding occurred on 65% of observation days, with 2–3 days periods of inactivity common. Despite this variability, mean daily feeding rates aligned with previous studies (1.35 coral colonies d⁻¹; 198.4 cm² day⁻¹ planar area, and 998.83 cm² day⁻¹ three-dimensional surface area). Across all tracked individuals (n = 8), feeding was recorded on 17 coral genera; however, Acropora alone accounted for 51% of colonies consumed and contributed 82% of the total three-dimensional surface area ingested during the survey period. This highlights the disproportionately large feeding yield derived from Acropora-dominated diets and raises important questions about how future declines in Acropora cover may impact CoTS feeding success and energetic intake. Full article

This study presents a critical evaluation of image-based 3D reconstruction techniques for small archaeological artifacts, focusing on a quantitative comparison between Neural Radiance Fields (NeRF), its recent Gaussian Splatting (GS) variant, and traditional Structure-from-Motion (SfM) photogrammetry. The research targets artifacts smaller than 5 cm, characterized by complex geometries and reflective surfaces that pose challenges for conventional recording methods. To address the limitations of traditional methods without resorting to the high costs associated with laser scanning, this study explores NeRF and GS as cost-effective and efficient alternatives. A comprehensive experimental framework was established, incorporating ground-truth data obtained using a metrological articulated arm and a rigorous quantitative evaluation based on root mean square (RMS) error, Chamfer distance, and point cloud density. The results indicate that while NeRF outperforms GS in terms of geometric fidelity, both techniques still exhibit lower accuracy compared to SfM, particularly in preserving fine geometric details. Nonetheless, NeRF demonstrates strong potential for rapid, high-quality 3D documentation suitable for visualization and dissemination purposes in cultural heritage. These findings highlight both the current capabilities and limitations of neural rendering techniques for archaeological documentation and suggest promising future research directions combining AI-based models with traditional photogrammetric pipelines. Full article

Mangrove forests are vital blue carbon (BC) ecosystems that significantly contribute to climate change mitigation through carbon sequestration. Accurate, scalable, and cost-effective methods for estimating carbon stocks in these environments are essential for conservation planning. In this study, we assessed the potential of drones, also known as unmanned aerial vehicles (UAVs), for estimating above-ground biomass (AGB) and BC in Avicennia marina stands by integrating drone-based canopy measurements with field-measured tree heights. Using structure-from-motion (SfM) photogrammetry and a consumer-grade drone, we generated a canopy height model and extracted structural parameters from individual trees in the Melgonze mangrove patch, southern Iran. Field-measured tree heights served to validate drone-derived estimates and calibrate an allometric model tailored for A. marina. While drone-based heights differed significantly from field measurements (p < 0.001), the resulting AGB and BC estimates showed no significant difference (p > 0.05), demonstrating that crown area (CA) and model formulation effectively compensate for height inaccuracies. This study confirms that drones can provide reliable estimates of BC through non-invasive means—eliminating the need to harvest, cut, or physically disturb individual trees—supporting their application in mangrove monitoring and ecosystem service assessments, even under challenging field conditions. Full article

Significant morphological transformations resulting from open-pit mining activities always present major problems with site safety and slope stability. This study investigates an active marble quarry in Dinar, Türkiye by combining geospatial analysis and photogrammetry based on unmanned aerial vehicles (UAV). Acquired in 2024 and 2025, high-resolution images were combined with dense point clouds produced by Structure from Motion (SfM) methods. Iterative Closest Point (ICP) registration (RMSE = 2.09 cm) and Multiscale Model-to-Model Cloud Comparison (M3C2) analysis was used to quantify the surface changes. The study found a volumetric increase of 7744.04 m³ in the dump zones accompanied by an excavation loss of 8359.72 m³, so producing a net difference of almost 615.68 m³. Surface risk factors were evaluated holistically using a variety of morphometric criteria. These measures covered surface variation in several respects: their degree of homogeneity, presence of any unevenness or texture, verticality, planarity, and linearity. Surface variation > 0.20, roughness > 0.15, and verticality > 0.25 help one to identify zones of increased instability. Point cloud modeling derived from UAVs and GIS-based spatial analysis were integrated to show that morphological anomalies are spatially correlated with possible failure zones. Full article

Photogrammetry can be a valuable tool for understanding landscape evolution and natural hazards such as landslides. However, factors such as vegetation cover, shadows, and unstable ground can limit its effectiveness. Using photos across time to monitor an area with unstable or changing ground conditions results in fewer tie points between images across time, and often leads to low comparative accuracy if single-epoch (i.e., classical) photogrammetric processing approaches are used. This paper presents a study evaluating the co-alignment approach applied to fixed terrestrial timelapse photos at an active landslide site. The study explores the comparative accuracy of reconstructed surface models and the location and behavior of tie points over time in relation to increasing levels of global change due to landslide activity and rockfall. Building upon previous work, this study demonstrates that high comparative accuracy can be achieved with a relatively low number of inter-epoch tie points, highlighting the importance of their distribution across stable ground, rather than the total quantity. High comparative accuracy was achieved with as few as 0.03 percent of the overall co-alignment tie points being inter-epoch tie points. These results show that co-alignment is an effective approach for conducting change detection, even with large degrees of global changes between surveys. This study is specific to the context of geoscience applications like landslide monitoring, but its findings should be relevant for any application where significant changes occur between surveys. Full article

Coarse-grained beaches consisting of gravel, pebbles, and cobbles play a crucial role in coastal protection. On the Croatian Adriatic coast, there are artificial gravel pocket beaches created for recreational and protective purposes. However, these beaches are subject to constant morphological changes due to natural forces and human intervention. This study investigates the morphodynamics of artificial gravel pocket beaches, focusing on berm formation and crest build-up processes characteristic for low to moderate wave conditions. Despite mimicking natural formations, artificial beaches require regular maintenance due to sediment shifts dominantly caused by wave action and storm surges. Structure-from-Motion (SfM) photogrammetry and UAV-based surveys were used to monitor morphological changes on the artificial gravel pocket beach Ploče (City of Rijeka). The XBeach-Gravel model, originally adapted to simulate the effects of high-energy waves, was calibrated and validated to analyze low to moderate wave dynamics on gravel pocket beaches. The calibration includes adjustments to the inertia coefficient (ci), which influences sediment transport by shear stress at the bottom; the angle of repose (ϕ), which controls avalanching and influences sediment transport on sloping beds; and the bedload transport calibration coefficient (γ), which scales the transport rates linearly. By calibrating XBeach-G for low to moderate wave conditions, this research improves the accuracy of the model for the cases of morphological responses “berm formation” and “crest build-up”. Full article

Nighttime terrain mapping has remained a significant challenge in photogrammetry due to the absence of visible light required by conventional imaging systems. This study evaluates the feasibility of generating Digital Surface Models (DSMs) from nighttime aerial thermal imagery using structure-from-motion photogrammetry. A DJI Mavic 3 Enterprise Thermal Unmanned Aerial Vehicle (UAV) captured 1746 images at 35 m altitude over a 9.4-hectare campus environment. Reflective aluminum sheets served as ground control points, ensuring visibility in thermal imagery under nocturnal conditions. The resulting thermal DSM achieved a point density of 0.117 points/cm². Statistical analysis of four independent checkpoints yielded a root mean square error (RMSE) of 0.0522 m, a mean error (ME) of −0.052 m, and a standard deviation (SD) of 0.0054 m, indicating high vertical accuracy with minimal scatter around the systematic bias. Comparison with a reference RGB-based DSM revealed a correlation coefficient of 0.975, demonstrating strong spatial agreement. These results establish that high-quality DSMs can be generated solely from nighttime thermal imagery, providing a viable alternative for applications requiring 24-h operational capability, including emergency response, post-disaster assessment, and nocturnal environmental monitoring where traditional photogrammetry is impractical. Full article

Intrinsic parameter estimation by self-calibration is commonly used in Unmanned aerial vehicle (UAV)-based photogrammetry with Structure from Motion (SfM). However, obtaining stable estimates of these parameters from image-based SfM—which relies solely on images, without auxiliary data such as ground control points (GCPs)—remains challenging. Aerial imagery acquired with the constant-pitch (CP) flight pattern often exhibits non-linear deformations, highly unstable intrinsic parameters, and even alignment failures. We hypothesize that CP flights form a “critical configuration” that renders certain intrinsic parameters indeterminate. Through numerical experiments, we confirm that a CP flight configuration does not provide sufficient constraints to estimate focal length (f) and the principal point coordinate (cy) in image-based SfM. Real-world CP datasets further demonstrate the pronounced instability of these parameters. As a remedy, we show that by introducing intermediate strips into the CP flight plan—what we call a CP-Plus flight—can effectively mitigate the indeterminacy of f and cy in simulations and markedly improve their stability in all tested cases. This approach enables more effective image-only SfM workflows without auxiliary data, simplifies data acquisition, and improves three-dimensional reconstruction accuracy. Full article