Using unmanned aerial vehicles with thermal‐image acquisition cameras for animal surveys: a case study on the Sichuan snub‐nosed monkey in the Qinling Mountains

Abstract

Following significant developments in technology, alternative devices have been applied in fieldwork for animal and plant surveys. Thermal‐image acquisition cameras installed on unmanned aerial vehicles (UAVs) have been used in animal surveys in the wilderness. This article demonstrates an example of how UAVs can be used in high mountainous regions, presenting a case study on the Sichuan snub‐nosed monkey with a detection rate of 65.19% for positive individual identification. It also presents a model that can prospectively predict population size for a given animal species, which is based on combined initial work using UAVs and traditional surveys on the ground. A great potential advantage of UAVs is significantly shortening survey procedures, particularly for areas with high mountains and plateaus, such as the Himalayas, the Qinghai–Tibet Plateau, Hengduan Mountains, the Yunnan‐Gui Plateau and Qinling Mountains in China, where carrying out a traditional survey is extremely difficult, so that species and population surveys, particularly for critically endangered animals, are largely absent. This lack of data has impacted the management of endangered animals as well as the formulation and amendment of conservation strategies.

Determination of optimal flight altitude to minimise acoustic drone disturbance to wildlife using species audiograms

“…Some of the variation in sound propagation between the horizontal and vertical planes was likely due to greater attenuation from grass during the horizontal measurements. However, the reduction in noise when standing next to, compared to standing below, a UAV for a given displacement is consistent with previous studies (He et al, 2020). UAVs will be loudest when directly overhead, so we present advisable altitudes derived from only the vertical recordings, which are sufficient even if flying over species with a horizontal offset.…”

“…blow samples from whales Acevedo-Whitehouse et al, 2010;Dominguez-Sanchez et al, 2018;Geoghegan et al, 2018;Pirotta et al, 2017), monitoring morphometric attributes (Burnett et al, 2019) and collecting behavioural data (Fiori et al, 2020;Graving et al, 2019). In addition UAVs have been used for census surveys (He et al, 2020;Linchant et al, 2018;Vermeulen et al, 2013;Ratcliffe et al, 2015), for anti-poaching surveillance (Marks, 2014;Mulero-Pazmany et al, 2014), for mapping species habitat use and distribution (Goebel et al, 2015;Koh & Wich, 2012;Perryman et al, 2014;Szantoi et al, 2017;van Andel et al, 2015), for locating radio-tagged animals (Muller et al, 2019), for assessing species body mass and condition (Christiansen et al, 2019;Krause et al, 2017), for relocating animals to mitigate human-wildlife conflict (Hahn et al, 2017;Schiffman, 2014) and for kinematic analysis (i.e. recording running giraffes; Basu et al, 2019).…”

“…There is a growing body of literature discussing the impact of UAV-generated disturbance on large mammals based primarily on visual observation of aberrant behaviour (Arona et al, 2018;Hodgson & Koh, 2016). Guidelines on advised flight altitudes based on visual observations are presented in several studies, for example, 25-40 m above water level (AWL) for bottlenose dolphins (Fettermann et al, 2019) and 80-100 m above-ground level (AGL) for snub-nosed monkeys (He et al, 2020). All guidelines require nuance as different UAV designs generate different sound profiles, and sound propagation loss (sound wave dissemination) is affected by numerous environmental and situational factors (e.g.…”

Iris Image Acquisition and Real-Time Detection System Using Convolutional Neural Network

“…The imaging equation of the camera can be expressed as follows. (8) Light field refocusing algorithm based on fractional Fourier transform: each dimension in the light field acquisition function is discretely processed. Then, x=x1 ∆x.…”

“…With the development of IT, more and more algorithms can be implemented through HW. At the same time, due to the specialization of the production line, the images generated or transmitted in the same environment contain similar and stable noise types, promoting the utilization of ASIC (Application Specific Integrated Circuit) [8]. However, due to the complexity and diversity of IPA (Image Processing Algorithms), only one structure can be adopted in a system, limiting the application of IPA.…”