Of Course We Fly Unmanned—We’re Women!

Drones, Journal Year: 2021, Volume and Issue: 5(1), P. 21 - 21

Published: March 12, 2021

Striving to achieve a diverse and inclusive workplace has become major goal for many organisations around the world [...]

Language: Английский

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Evidence on the efficacy of small unoccupied aircraft systems (UAS) as a survey tool for North American terrestrial, vertebrate animals: a systematic map

Environmental Evidence, Journal Year: 2023, Volume and Issue: 12(1)

Published: Feb. 13, 2023

Small unoccupied aircraft systems (UAS) are replacing or supplementing occupied and ground-based surveys in animal monitoring due to improved sensors, efficiency, costs, logistical benefits. Numerous UAS sensors available have been used various methods. However, justification for selection methods not typically offered published literature. Furthermore, existing reviews do adequately cover past current applications monitoring, nor their associated UAS/sensor characteristics environmental considerations. We present a systematic map that collects consolidates evidence pertaining of animals.

Language: Английский

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The broad scale impact of climate change on planning aerial wildlife surveys with drone-based thermal cameras

Scientific Reports, Journal Year: 2023, Volume and Issue: 13(1)

Published: March 17, 2023

Abstract Helicopters used for aerial wildlife surveys are expensive, dangerous and time consuming. Drones thermal infrared cameras can detect wildlife, though the ability to individuals is dependent on weather conditions. While we have a good understanding of local conditions, do not broad-scale assessment ambient temperature plan drone surveys. Climate change will affect our conduct in future. Our objective was determine optimal annual daily periods We present case study Texas, (United States America [USA]) where acquired compared average monthly data from 1990 2019, hourly 2010 2019 projected 2021 2040 identify areas would commonly studied ungulate (white-tailed deer [ Odocoileus virginianus ]) during sunny or cloudy Mean temperatures increased when comparing 1990–2019 2010–2019 periods. above maximum which white-tailed be detected 72, 10, 24 254 Texas counties June, July, August, September, respectively. Future climate projections indicate that increase 32, 12, 15, 47 respectively with 2021–2040. This analysis assist planning, scheduling across year combined efficient flights.

Language: Английский

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Thermal Sensor Calibration for Unmanned Aerial Systems Using an External Heated Shutter

Drones, Journal Year: 2021, Volume and Issue: 5(4), P. 119 - 119

Published: Oct. 17, 2021

Uncooled thermal infrared sensors are increasingly being deployed on unmanned aerial systems (UAS) for agriculture, forestry, wildlife surveys, and surveillance. The acquisition of data requires accurate uniform testing equipment to ensure precise temperature measurements. We modified an uncooled sensor, specifically designed UAS remote sensing, with a proprietary external heated shutter as calibration source. performance the sensor standard (i.e., without shutter) was compared under both field modulated laboratory conditions. During trials blackbody source at 35 °C over 150 min period, unmodified produced ranges 34.3–35.6 33.5–36.4 °C, respectively. A experiment also included simulation flight conditions by introducing airflow rate 4 m/s. With held constant 25 introduction 2 air flow resulted in ’shock cooling’ event sensors, oscillating between 19–30 -15–65 Following initial ‘shock event, oscillated 22–27 5–45 conducted pine plantation, outperformed side-by-side comparison. found that use mounted improved measurements, producing more consistent mapping projects.

Language: Английский

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From Coastal to Montane Forest Ecosystems, Using Drones for Multi-Species Research in the Tropics

Drones, Journal Year: 2021, Volume and Issue: 6(1), P. 6 - 6

Published: Dec. 25, 2021

Biodiversity monitoring is crucial in tackling defaunation the Anthropocene, particularly tropical ecosystems. However, field surveys are often limited by habitat complexity, logistical constraints, financing and detectability. Hence, leveraging drones technology for species required to overcome caveats of conventional surveys. We investigated prospective methods wildlife using four surveyed waterbird populations Pulau Rambut, a community ungulates Baluran endemic non-human primates Gunung Halimun-Salak, Indonesia 2021 DJI Matrice 300 RTK Mavic 2 Enterprise Dual with additional thermal sensors. then, consecutively, implemented two survey at three sites compare efficacy against traditional ground each species. The results show that drone provide advantages over surveys, including precise size estimation, less disturbance broader area coverage. Moreover, heat signatures helped detect which were not easily spotted radiometric imagery, while detailed imagery allowed identification. Our research also demonstrates machine learning approaches relatively high performance detection. prove promising different ecosystems forests.

Language: Английский

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Blockchain-Aware Distributed Dynamic Monitoring: A Smart Contract for Fog-Based Drone Management in Land Surface Changes

Atmosphere, Journal Year: 2021, Volume and Issue: 12(11), P. 1525 - 1525

Published: Nov. 19, 2021

In this paper, we propose a secure blockchain-aware framework for distributed data management and monitoring. Indeed, images-based are captured through drones transmitted to the fog nodes. The main objective here is enable process schedule, investigate individual entity (records) analyze changes in blockchain storage with hash-encrypted (SH-256) consortium peer-to-peer (P2P) network. proposed mechanism also investigated analyzing fog-cloud-based stored information, which referred as smart contracts. These contracts designed deployed automate overall monitoring system. They include registration of UAVs (drones), day-to-day dynamic drone-based images, update transactions immutable future investigations. simulation results show merit our framework. extensive experiments, developed system provides good performances regarding tasks.

Language: Английский

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Controllable factors affecting accuracy and precision of human identification of animals from drone imagery

Ecosphere, Journal Year: 2023, Volume and Issue: 14(9)

Published: Sept. 1, 2023

Abstract Surveying animal populations using drones (unoccupied aircraft systems [UAS]) provides numerous advantages; however, few best practices exist to survey communities with drones. Among myriad factors that can affect human identification and counts of animals from drone images, we focused on three typically controlled in the study design or by pilot: flight altitude, camera angle, time day. Identifying interactions patterns among these variables represents an important first step determining practices. We used a known numbers eight decoy species, representing range body sizes colors, at four ground sampling distance (GSD) values (0.35, 0.70, 1.06, 1.41 cm/pixel) equivalent altitudes (15.2, 30.5, 45.7, 61.0 m) two angles (45° 90°) across times day (morning late afternoon). Expert observers identified counted images determine how controllable affected accuracy precision. Observer precision was high unaffected tested factors. However, results for observer revealed interaction all Increasing altitude resulted decreased overall; midday than during morning afternoon, when structure shadows were present more pronounced. Surprisingly, 45° enhanced 90° camera, but only most difficult identify count, such as higher early afternoon. provide recommendations improving identifying counting monitoring communities. These should be incorporated into addition considering funding, logistical, behavior constraints.

Language: Английский

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Evaluating the Efficacy of Drone‐Based Thermal Images for Measuring Wildlife Abundance and Physiology

Marine Mammal Science, Journal Year: 2025, Volume and Issue: unknown

Published: April 18, 2025

ABSTRACT Although drones are a promising alternative to traditional wildlife monitoring methods, validation efforts needed quantify the accuracy of abundance and distribution estimates obtained from using drones. We used equipped with high‐resolution Red‐Green‐Blue (RGB) thermal cameras, coupled machine learning techniques, assess physiology in northern elephant seals ( Mirounga angustirostris ). Aerial images 3415 measurements ambient air temperature, wind speed, time day were collected during nighttime daytime drone flights N = 24). Two‐dimensional polygons surface temperatures measured images. Machine algorithms applied detect imagery, model performance was evaluated. Detection more accurate RGB (machine averaged 6.8% lower than human counts) (16.6%). However, useful for determining that temperature (but not speed or body size) influenced seal external skin temperature. cameras have different strengths weaknesses should be considered when designing research studies. Our study demonstrates integrating drones, imaging, can promote faster, safer, cheaper, less disruptive, conservation efforts.

Language: Английский

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Drone Aided Thermal Mapping for Selective Irrigation of Localized Dry Spots

IEEE Access, Journal Year: 2023, Volume and Issue: 11, P. 7320 - 7335

Published: Jan. 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.

Language: Английский

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Flight speed and time of day heavily influence rainforest canopy wildlife counts from drone-mounted thermal camera surveys

Biodiversity and Conservation, Journal Year: 2022, Volume and Issue: 31(13-14), P. 3179 - 3195

Published: Oct. 22, 2022

Abstract The payload size and commercial availability of thermal infrared cameras mounted on drones has initiated a new wave in the potential for conservationists researchers to survey, count detect wildlife, even most complex habitats such as forest canopies. However, several fundamental design methodological questions remain be tested before standardized monitoring approaches can broadly adopted. We test impact both speed drone flights diel flight period tropical rainforest canopy wildlife detections. Detection identification rates differ between speeds time. Overall ~ 36% more detections were made during slower speeds, along with greater ability categorize taxonomic groups. Flights conducted at 3am resulted 67% compared 7am (the lowest detection rate). 112% could identified group – due types being assistance RGB camera. Although, this technology holds great promise carrying out surveys structurally poorly known ecosystems like canopies, there is do further testing, building automated post-processing systems. Our results suggest that studies same habitat types, animal densities, off by multiples if flown different times and/or speeds. difference an alarming 5-6x variation or depending changes these two factors alone.

Language: Английский

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