A method to interpret fracture aperture of rock slope using adaptive shape and unmanned aerial vehicle multi-angle nap-of-the-object photogrammetry

Journal of Rock Mechanics and Geotechnical Engineering, Год журнала: 2023, Номер 16(3), С. 924 - 941

Опубликована: Сен. 12, 2023

The aperture of natural rock fractures significantly affects the deformation and strength properties masses, as well hydrodynamic fractured masses. conventional measurement methods are inadequate for collecting data on high-steep slopes in complex mountainous regions. This study establishes a high-resolution three-dimensional model slope using unmanned aerial vehicle (UAV) multi-angle nap-of-the-object photogrammetry to obtain edge feature points fractures. Fracture opening morphology is characterized coordinate projection transformation. central axis determined vertical measuring lines, allowing interpretation adaptive fracture shape. feasibility reliability new method verified at construction site railway southeast Tibet, China. shows that has significant interval effect size effect. optimal sampling length approximately 0.5–1 m, results can be achieved when line spacing 1% length. Tensile area generally have larger apertures than shear fractures, their tendency increase with height also greater tensile positively correlated trace length, while correlation between appears weak. Fractures different orientations exhibit certain differences distribution aperture, but follow forms normal, log-normal, gamma distributions. provides essential support stability evaluation, which practical importance.

Язык: Английский

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Proposition of UAV multi-angle nap-of-the-object image acquisition framework based on a quality evaluation system for a 3D real scene model of a high-steep rock slope

International Journal of Applied Earth Observation and Geoinformation, Год журнала: 2023, Номер 125, С. 103558 - 103558

Опубликована: Ноя. 18, 2023

The 3D real scene model of high-steep rock slope established based on UAV image provides convenience for non-contact identification and interpretation mass structures. quality models directly influences the interpretability However, quantitative studies relationship between these two aspects are scarce. Therefore, this study investigates influence indicators such as photography distance (D), brightness (l), angle optical axis discontinuity to be interpreted (θd), texture distortion area ratio (tdp), among others, models. Furthermore, it delves into relationships their practical application effects in complex slopes. On foundation, a novel multi-indicator evaluation method constructed using photogrammetry is introduced first time. This method, composite index incorporating empirical approaches, classifies five levels. Guided by results taking account terrain development geometric characteristics discontinuities, technical framework supporting acquisition high-quality proposed, known multi-angle nap-of-the-object (MNIA). research indicates that MNIA exhibit significantly reduced distortion, leading substantial improvement recognizability, with goodness rate 79.98%, far surpassing oblique (41.18%). crucial guidance obtaining environments holds significant engineering value fine structures

Язык: Английский

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Drivers of Three Most Charismatic Mammalian Species Distribution across a Multiple-Use Tropical Forest Landscape of Sumatra, Indonesia

Animals, Год журнала: 2022, Номер 12(19), С. 2722 - 2722

Опубликована: Окт. 10, 2022

Tropical Rainforest Heritage sites of Sumatra are some the most irreplaceable landscapes in world for biodiversity conservation. These harbor many endangered Asiatic mammals all suffering multifaceted threats due to anthropogenic activities. Three charismatic Sumatra: Elephas maximus sumatranus, Pongo abelii, and Panthera tigris sumatrae protected listed as Critically Endangered (CR) within IUCN Red List. Nevertheless, their current geographic distribution remains unclear, impact environmental factors on these species mostly unknown. This study predicts potential range those island using anthropogenic, biophysical, topographic, climatic parameters based ensemble machine learning algorithms. We also investigated effects habitat loss from land use, ecosystem availability, importance Indonesian areas. Our predictive model had relatively excellent performance (Sørensen: 0.81-0.94) can enhance knowledge distributions. The critical predictors three conservation status temperature seasonality. revealed that more than half distributions occurred non-protected areas, with proportional coverage being 83%, 72%, 54% E.m. P. P.t. sumatrae, respectively. further provides reliable information places where efforts must be prioritized, both inside outside area networks, safeguard ongoing survival large mammals.

Язык: Английский

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Drone Aided Thermal Mapping for Selective Irrigation of Localized Dry Spots

IEEE Access, Год журнала: 2023, Номер 11, С. 7320 - 7335

Опубликована: Янв. 1, 2023

We report a smart irrigation system that allows selective of localized dry spots in an agricultural field. The proposed uses quadcopter drone equipped with Thermal Infrared (TIR) camera and GPS module to generate georeferenced thermal images indicate the area location survey area. Drones navigate acquire aerial images, which are then processed by onboard edge intelligence along flight data (GPS coordinates, altitude, direction). Smart sprinklers deployed on field able wirelessly receive coordinates so they can be irrigated selectively. A terrestrial unit generates pattern for using pre-trained machine learning (ML) model varying head rotation angle ( $\theta$ ) water flow control valve angle( notation="LaTeX">$\emptyset$ sprinkler.

Язык: Английский

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The first use of a photogrammetry drone to estimate population abundance and predict age structure of threatened Sumatran elephants

Scientific Reports, Год журнала: 2023, Номер 13(1)

Опубликована: Дек. 3, 2023

Wildlife monitoring in tropical rainforests poses additional challenges due to species often being elusive, cryptic, faintly colored, and preferring concealable, or difficult access habitats. Unmanned aerial vehicles (UAVs) prove promising for wildlife surveys different ecosystems forests can be crucial conserving inaccessible biodiverse areas their associated species. Traditional that involve infiltrating animal habitats could adversely affect the habits behavior of elusive cryptic response human presence. Moreover, collecting data through traditional simultaneously estimate abundance demographic rates communities is prohibitively time-intensive expensive. This study assesses scope drones non-invasively Bukit Tigapuluh Landscape (BTL) Riau-Jambi, Indonesia, detect individual elephants interest. A rotary-wing quadcopter with a vision-based sensor was tested elephant population size age structure. We developed hierarchical modeling deep learning CNN Drones successfully observed 96 distinct individuals at 8 locations out 11 sampling areas. obtained an 151 (95% CI [124, 179]) within area predicted more adult animals than subadults juvenile population. Our calculations may serve as vital spark innovation future UAV survey designs large complex topographies while reducing operational effort.

Язык: Английский

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Evaluating Thermal Infrared Drone Flight Parameters on Spider Monkey Detection in Tropical Forests

Sensors, Год журнала: 2024, Номер 24(17), С. 5659 - 5659

Опубликована: Авг. 30, 2024

Geoffroy's spider monkeys, an endangered, fast-moving arboreal primate species with a large home range and high degree of fission-fusion dynamics, are challenging to survey in their natural habitats. Our objective was evaluate how different flight parameters affect the detectability monkeys videos recorded by drone equipped thermal infrared camera examine level agreement between coders. We used generalized linear mixed models impact speed (2, 4, 6 m/s), height (40, 50 m above ground level), angle (-45°, -90°) on monkey counts closed-canopy forest Yucatan Peninsula, Mexico. results indicate that none three affected number detected monkeys. Agreement coders "substantial" (Fleiss' kappa coefficient = 0.61-0.80) most cases for thermal-contrast zones. study contributes development standardized protocols, which essential obtain accurate data presence abundance wild populations. Based our results, we recommend performing surveys other medium-sized mammals small commercial at 4 m/s speed, 15 canopy height, -90° angle. However, these recommendations may vary depending size noise produced model.

Язык: Английский

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Developing a new method using thermal drones for population surveys of the world's rarest great ape species, Pongo tapanuliensis

Global Ecology and Conservation, Год журнала: 2025, Номер unknown, С. e03463 - e03463

Опубликована: Янв. 1, 2025

Язык: Английский

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Unmanned Aerial Vehicle Remote Sensing for Monitoring Fractional Vegetation Cover in Creeping Plants: A Case Study of Thymus mongolicus Ronniger

Agriculture, Год журнала: 2025, Номер 15(5), С. 502 - 502

Опубликована: Фев. 26, 2025

Fractional vegetation cover (FVC) is a key indicator of plant growth. Unmanned aerial vehicle (UAV) imagery has gained prominence for FVC monitoring due to its high resolution. However, most studies have focused on single phenological stages or specific crop types, with limited research the continuous temporal creeping plants. This study addresses this gap by focusing Thymus mongolicus Ronniger (T. mongolicus). UAV-acquired visible light and multispectral images were collected across stages: green-up, budding, early flowering, peak fruiting. estimation models developed using four algorithms: multiple linear regression (MLR), random forest (RF), support vector (SVR), artificial neural network (ANN). The SVR model achieved optimal performance during green-up (R2 = 0.87) flowering 0.91), while ANN excelled budding 0.93), 0.95), fruiting 0.77). predictions best-performing consistent ground truth values, thereby effectively capturing dynamic changes in FVC. growth rates exhibited distinct variations stages, indicating consistency between predicted actual trends. highlights feasibility UAV-based T. indicates potential tracking

Язык: Английский

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Artificial Intelligence in Aquatic Biodiversity Research: A PRISMA-Based Systematic Review

Biology, Год журнала: 2025, Номер 14(5), С. 520 - 520

Опубликована: Май 8, 2025

Freshwater ecosystems are increasingly threatened by climate change and anthropogenic activities, necessitating innovative scalable monitoring solutions. Artificial intelligence (AI) has emerged as a transformative tool in aquatic biodiversity research, enabling automated species identification, predictive habitat modeling, conservation planning. This systematic review follows the PRISMA framework to analyze AI applications freshwater studies. Using structured literature search across Scopus, Web of Science, Google Scholar, we identified 312 relevant studies published between 2010 2024. categorizes into assessment, ecological risk evaluation, strategies. A bias assessment was conducted using QUADAS-2 RoB 2 frameworks, highlighting methodological challenges, such measurement inconsistencies model validation. The citation trends demonstrate exponential growth AI-driven with leading contributions from China, United States, India. Despite growing use this field, also reveals several persistent including limited data availability, regional imbalances, concerns related generalizability transparency. Our findings underscore AI’s potential revolutionizing but emphasize need for standardized methodologies, improved integration, interdisciplinary collaboration enhance insights efforts.

Язык: Английский

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New records of the southern muriqui (Brachyteles arachnoides) in Serra da Mantiqueira through thermal drones

Primates, Год журнала: 2025, Номер unknown

Опубликована: Май 16, 2025

Язык: Английский

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