Results 191 to 200 of about 1,910,400 (338)

Monitoring GPS‐collared moose by ground versus drone approaches: efficiency and disturbance effects

Wildlife Biology, EarlyView.
Efficient wildlife management requires precise monitoring methods, for example to estimate population density, reproductive success, and survival. Here, we compared the efficiency of drone (equipped with a RGB camera) and ground approaches to detect and observe GPS‐collared female moose Alces alces and their calves. We also quantified how drone (n = 42)
Martin Mayer, Erlend Furuhovde, Kristoffer Nordli, Giorgia Myriam Ausilio, Petter Wabakken, Ane Eriksen, Alina L. Evans, Karen Marie Mathisen, Barbara Zimmermann   +8 more
wiley   +1 more source

A smart energy management system for surface unmanned vehicles for border surveillance missions. [PDF]

Sci Rep
Fernandes JFP, Assunção M, Serrano D, Afonso P, Pinheiro P, Marques H, Neves J, Teodoro P, Póvoa R, Marat-Mendes R, Costa Branco PJ.   +10 more
europepmc   +1 more source

Saving Bambi from the mower? Using a drone with thermal camera to evaluate a low‐tech scaring technique to reduce roe deer fawn mortality during grass harvest

Wildlife Biology, EarlyView.
Roe deer is a species that hides their neonates as an anti‐predator strategy. This may prove efficient against mammalian predators, such as the red fox; however, it might be an ecological trap as large numbers of fawns are killed by tractors with harvesters each year during grass harvest.
Thomas Vogler, Neri H Thorsen, Simen Pedersen   +2 more
wiley   +1 more source

Trajectory Planning for Unmanned Vehicles on Airport Apron Under Aircraft-Vehicle-Airfield Collaboration. [PDF]

Sensors (Basel)
Yuan D, Zhong Y, Zhu X, Chen Y, Jin Y, Du X, Tang K, Huang T.   +7 more
europepmc   +1 more source

New Approaches to the Integration of Navigation Systems for Autonomous Unmanned Vehicles (UAV). [PDF]

Sensors (Basel), 2018
Konovalenko I, Kuznetsova E, Miller A, Miller B, Popov A, Shepelev D, Stepanyan K.   +6 more
europepmc   +1 more source

Evaluating machine learning models for multi‐species wildlife detection and identification on remote sensed nadir imagery in South African savanna

Wildlife Biology, EarlyView.
This research paper investigates the efficacy of leading machine learning (ML) models for detecting and identifying ungulate species in African savanna using nadir imagery from unmanned aerial vehicles (UAVs). Traditional aerial counting methods, while widely used, suffer from significant limitations in accuracy and precision, in part due to human ...
Paul Allin, Fadel Seydou, Radloff Frans, Andrew Davies, Alison Leslie   +4 more
wiley   +1 more source

Construction of dynamic trafficability map for unmanned vehicles considering multiple environmental factors and path planning. [PDF]

Sci Rep
Liu Q, You X, Zhang X, Zuo J.
europepmc   +1 more source

Formation Generation for Multiple Unmanned Vehicles Using Multi-Agent Hybrid Social Cognitive Optimization Based on the Internet of Things. [PDF]

Sensors (Basel), 2019
Yao Z, Wu S, Wen Y.
europepmc   +1 more source

Estimating red deer Cervus elaphus population density using drones in a steep and rugged terrain

Wildlife Biology, EarlyView.
Precise and accurate information about population density, crucial for wildlife management, is difficult to obtain for elusive species living in dense forests or steep and inaccessible terrain. Using unmanned aerial vehicles (UAVs), we developed a method for obtaining absolute population estimates of ungulates living in steep, rugged, and partly ...
Julie Bommerlund, Torbjørn Ergon, Simon Filhol, Atle Mysterud   +3 more
wiley   +1 more source

Study of Global Navigation Satellite System Receivers' Accuracy for Unmanned Vehicles. [PDF]

Sensors (Basel)
Miletiev R, Petkov PZ, Yordanov R, Brusev T.   +3 more
europepmc   +1 more source