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Trialing a real-time drone detection and validation protocol for the koala (Phascolarctos cinereus)
Abstract
Remotely piloted aircraft system (RPAS or drone) technology has emerged as a promising survey method for the cryptic koala. We demonstrate an in-field protocol for wild koala RPAS surveys which provides real-time validation of thermal signatures. During fifteen trial flights using a quadcopter drone (DJI Matrice 200 v2) we successfully detected and validated koala thermal signatures (n = 12) using two in-field approaches; validation by on-ground observer (n = 10) and validation using 4K footage captured and reviewed directly post-survey (n = 2). We also provide detectability considerations relative to survey-time, temperature, wildlife-RPAS interactions and detection of non-target species, which can be used to further inform RPAS survey protocols.
... These rely on evidence of occupancy and activity such as scratch marks, scats, citizen sightings, and bellows [3,20,22,24,25]. In contrast, the application of direct techniques, such as diurnal strip-width [10,26,27] and line-transects [10], nocturnal line-transects [3], and emerging remotely piloted aircraft system thermal imaging (RPAS, also known as drones) technologies [8,[28][29][30], require surveyors to physically sight koalas and this is preferable for density and population estimates [3]. ...
... For example, RPAS can be coupled with sensors and infrared detectors that capture high-resolution thermal images [41]. RPAS are particularly promising for surveying wildlife [42,43] and have been accurate and cost-effective in determining abundance [43] and for detecting a range of species including arboreal mammals such as monkeys [44] and koalas [8,[28][29][30]. ...
... In contrast, our recently published RPAS protocol offers real-time detection and validation of wild koalas by a combination of on-ground observation and the collection of 4K footage reviewed in the field [29]. We found that in the winter months a koala was on average 17.1 ± 2.7% brighter than the surrounding canopy vegetation [29]. ...
Koalas (Phascolarctos cinereus) are cryptic and currently face regional extinction. The direct detection (physical sighting) of individuals is required to improve conservation management strategies. We provide a comparative assessment of three survey methods for the direct detection of koalas: systematic spotlighting (Spotlight), remotely piloted aircraft system thermal imaging (RPAS), and the refined diurnal radial search component of the spot assessment technique (SAT). Each survey method was repeated on the same morning with independent observers (03:00–12:00 hrs) for a total of 10 survey occasions at sites with fixed boundaries (28–76 ha) in Port Stephens (n = 6) and Gilead (n = 1) in New South Wales between May and July 2019. Koalas were directly detected on 22 occasions during 7 of 10 comparative surveys (Spotlight: n = 7; RPAS: n = 14; and SAT: n = 1), for a total of 12 unique individuals (Spotlight: n = 4; RPAS: n = 11; SAT: n = 1). In 3 of 10 comparative surveys no koalas were detected. Detection probability was 38.9 ± 20.03% for Spotlight, 83.3 ± 11.39% for RPAS and 4.2 ± 4.17% for SAT. Effective detectability per site was 1 ± 0.44 koalas per 6.75 ± 1.03 hrs for Spotlight (1 koala per 6.75 hrs), 2 ± 0.38 koalas per 4.35 ± 0.28 hrs for RPAS (1 koala per 2.18 hrs) and 0.14 ± 0.14 per 6.20 ± 0.93 hrs for SAT (1 koala per 43.39 hrs). RPAS thermal imaging technology appears to offer an efficient method to directly survey koalas comparative to Spotlight and SAT and has potential as a valuable conservation tool to inform on-ground management of declining koala populations.
... As a sedentary cryptic species, koala populations are generally spatially fragmented (White, 1999). Hence, drone based surveying has been a vital conservation tool in capturing the distribution and abundance of koalas (e.g., Beranek et al., 2020;Corcoran et al., 2021). Due to their dietary specialisation on Eucalyptus leaves (Seabrook et al., 2011), which are poor sources of proteins, koalas have developed several adaptations to conserve energy and can rest 20 h per day (Benesch et al., 2010). ...
... In conclusion, our study provides additional insights into the behavioural and physiological responses of a terrestrial species to drone surveys (Ditmer et al., 2015;Bennitt et al., 2019;Brunton et al., 2019;Headland et al., 2021). Current methods for monitoring koala populations are inconsistent across Australiaranging from indirect surveys (such as faecal pellet surveys; McAlpine et al., 2006), diurnal or spotlight searches (Wilmott et al., 2019), physical tagging of individuals (Duka and Masters, 2005;Dexter et al., 2016Dexter et al., , 2018 to drone monitoring (Beranek et al., 2020;Corcoran et al., 2021) -which can confound the management of the species (Adams-Hosking et al., 2016;Wilmott et al., 2019). It is therefore vital to implement a more consistent monitoring method across states. ...
... В качестве платформы использовали квадрокоптер DJI Matrice 200 v2 с установленным приемником GNSS L1/L2 [14]. Дрон с пыле-и влагозащитой способен осу ществлять полеты при скорости ветра до 20 м/с, что актуально при работе в поле на открытой местности [15][16]. ...
... The paper was submitted to the Editorial Office on 16 ...
The authors showed that it is possible to quickly collect up-to-date information on the agricultural land condition using an unmanned aerial vehicle. It was noted that the use of ground control points increases the accuracy of project measurements, helps to compare the project post-processing results with the real measurements. (Research purpose) To compare the results of standard and high-precision post-processing of aerial survey data using ground control points. (Materials and methods) Aerial photography was carried out on a 1.1- hectare breeding field. The authors used DJI Matrice 200 v2 unmanned aerial vehicle with a GNSS L1/L2 receiver and a modified DJI X4S camera, five control points sized 50 × 50 centimeters and an EMLID Reach RS2 multi-frequency GNSS receiver. The results of scientific research into the use of ground control points during aerial photography were studied. (Results and discussion) It was found out that the error of georeferencing images obtained by an unmanned aerial vehicle without control points is significantly higher during the standard data processing compared to the high-precision one. The project error when using five control points is 3.9 times higher during the standard data processing. (Conclusions) It was shown that using ground control points it is possible to improve the project measurement accuracy, as well as compare the project post-processing results with the measurements on the ground. It was detected that the high-precision monitoring enables the use of fewer ground control points. It was found out that in order to obtain data with the accuracy of 2-4 centimeters in plan and height, at least 3 ground control points need to be used during the high-precision post-processing.
... Feral horse [69] Penguin [70] White-tailed deer [71] Sumatran orangutan [72] Sea Lion [73] Sea turtles [74] Shark [75] Koala [76] Behaviour Research ...
... After the bushfires, finding surviving koalas in burned and unburned areas became an urgent problem. To solve this problem, Australian ecologists presented an infield protocol for wild koala surveillance UAVs, which provides real-time validation of high-resolution thermal signatures of koalas [76]. The authors also provided detectability considerations relative to wildlife-UAV interactions, temperature, survey time, and detection of non-target species, which can be used to further inform UAV survey protocols. ...
As a typical cyber-physical system, networked unmanned aerial vehicles (UAVs) have received much attention in recent years. Emerging communication technologies and high-performance control methods enable networked UAVs to operate as aerial sensor networks to collect more complete and consistent information with significantly improved mobility and flexibility than traditional sensing platforms. One of the main applications of networked UAVs is surveillance and monitoring, which constitute essential components of a well-functioning public safety system and many industrial applications. Although the existing literature on surveillance and monitoring UAVs is extensive, a comprehensive survey on this topic is lacking. This article classifies publications on networked UAVs for surveillance and monitoring using the targets of interest and analyzes several typical problems on this topic, including the control, navigation, and deployment optimization of UAVs. The related research gaps and future directions are also presented.
... Drones equipped with thermal sensors have been used to monitor mammal species such as grey seals (Halichoerus grypus) (Seymour et al. 2017) and common hippopotami (Hippopotamus amphibius). In Australia, drones have been used to monitor the arboreal koala (Phascolarctos cinereus) (Witt et al. 2020;Beranek et al. 2021). Importantly, these studies show that drone-based thermal surveys can improve the detection and quantification of less conspicuous and inaccessible animal populations. ...
Context: Accurate and precise monitoring practises are key for effective wildlife conservation management; providing reliable estimates of spatiotemporal changes in species abundance on which sound decision-making can be based. Advancements in drone and satellite technology are providing new standards for survey accuracy and precision and have great potential for enhancing population monitoring of numerous difficult to survey species. Flying-foxes (Pteropus spp.) are large bats that roost in groups of a few hundred to many thousands in the canopies of trees, where they are difficult to census accurately and precisely by human observers. Globally, 35 of the 64 flying-fox species are listed as threatened under the IUCN Red List of Threatened Species, and reliable monitoring methods are needed for the effective management of this ecologically important group.
Aims: Recently, we showed that drone-acquired thermal imagery can be used to count flying-foxes in their roost with high accuracy and precision. In the present study, we aimed to assess the accuracy and precision of whole colony counts derived from ground-based counting methods against reference counts derived from drone-acquired thermal imagery.
Methods: We evaluated the relationship between ground-based counts by two groups of human observers to highly accurate and precise counts derived from drone-acquired thermal orthomosaics for 25 counts conducted across seven flying-fox roosts throughout the Greater Sydney region, Australia.
Key results: We found that ground-based counts by human observers were positively correlated with those obtained from concurrent drone-acquired thermal imagery. However, drone-acquired estimates of colony size were 2.05 and 1.92 times higher than ground-based counts by the experimenter and Australian government counters respectively. When compared against drone-acquired reference counts, the precision (coefficient of variation) of ground-based counts was 26.3% when conducted by a single counter and 55.1% when conducted by multiple counters.
Conclusions: Our research indicates that ground-based counting methods underestimate true population sizes by substantial margins and have limited precision. Drone-based monitoring provides highly accurate and precise population estimates, and thus is expected to yield more reliable information on flying-fox abundance and allow for trends to be established over shorter timescales.
Implications: Using ground counting methods alone, population trends can only be established with significance after protracted periods of monitoring. Incorporating the use of thermal drones into current monitoring practises would enhance the capacity to detect population trends earlier and more accurately, so that conservation management can more effectively respond.
... Researchers and land managers are increasingly using dronebased sensors that enable flexible spatial and temporal data collection, to attain unique perspectives on wildlife and their habitats (Chabot and Bird 2015;López and Mulero-Pázmány 2019;Lyons et al. 2019) and to develop innovative wildlife survey techniques (Pirotta et al. 2017;Brien et al. 2020;Beranek et al. 2021). This includes using drones to radio-track tagged animals (Cliff et al. 2015;Tremblay et al. 2017). ...
Radio-tracking tagged wildlife remains a critical research technique for understanding the movements, behaviours and survival of many species. However, traditional hand-held tracking techniques on the ground are labour intensive and time consuming. Therefore, researchers are increasingly seeking new technologies to address these challenges, including drone radio-tracking receivers. Following the implementation of drone radio-tracking techniques for five different threatened species projects within different habitat and landscape types, we identified the need to quantify the relative spatial extent of surveys using both drone and hand-held techniques for each project. This was undertaken using viewshed analyses. These analyses demonstrated that survey coverage with drone-based radio-tracking was substantially greater than that of hand-held radio-tracking for all species and landscapes examined. Within mountainous landscapes, drone radio-tracking covered up to four times the area of hand-held tracking, whereas in flat to undulating landscapes, drone surveys covered up to 11.3 times the area that could be surveyed using hand-held techniques from the same locations on the ground. The viewshed analyses were also found to be a valuable visualisation tool for identifying areas for targeted surveys to reduce the risk of 'losing' tagged animals, which has traditionally been one of the biggest radio-tracking challenges.
... These platforms can carry various sensors, including multi-or hyperspectral cameras, LiDAR, or thermal imagers, which increases their utility for ecological research (Anderson & Gaston, 2013). For example, UAVs have been used to detect koalas (Beranek et al., 2020) and map herbivore feeding habitat (Olsoy et al., 2020) using thermal and multispectral imagery, respectively. While hyperspectral sensors fit for UAVs can be costly and may require larger and heavier platforms, newer generation multispectral sensors are a fraction of the cost and can be readily integrated into small commercial UAVs that can be operated without specialist knowledge or certification (see CASA, 2019). ...
Herbivore foraging decisions are closely related to plant nutritional quality. For arboreal folivores with specialized diets, such as the vulnerable greater glider (Petauroides volans), the abundance of suitable forage trees can influence habitat suitability and species occurrence. The ability to model and map foliar nitrogen would therefore enhance our understanding of folivore habitat use at finer scales. We tested whether high-resolution multispectral imagery, collected by a lightweight and low-cost commercial unoccupied aerial vehicle (UAV), could be used to predict total and digestible foliar nitrogen (N and digN) at the tree canopy level and forest stand-scale from leaf-scale chemistry measurements across a gradient of mixed-species Eucalyptus forests in southeastern Australia. We surveyed temperate Eucalyptus forests across an elevational and topographic gradient from sea level to high elevation (50–1200 m a.s.l.) for forest structure, leaf chemistry, and greater glider occurrence. Using measures of multispectral leaf reflectance and spectral indices, we estimated N and digN and mapped N and favorable feeding habitat using machine learning algorithms. Our surveys covered 17 Eucalyptus species ranging in foliar N from 0.63% to 1.92% dry matter (DM) and digN from 0.45% to 1.73% DM. Both multispectral leaf reflectance and spectral indices were strong predictors for N and digN in model cross-validation. At the tree level, 79% of variability between observed and predicted measures of nitrogen was explained. A spatial supervised classification model correctly identified 80% of canopy pixels associated with high N concentrations (≥1% DM). We developed a successful method for estimating foliar nitrogen of a range of temperate Eucalyptus species using UAV multispectral imagery at the tree canopy level and stand scale. The ability to spatially quantify feeding habitat using UAV imagery allows remote assessments of greater glider habitat at a scale relevant to support ground surveys, management, and conservation for the vulnerable greater glider across southeastern Australia.
... Conversely, several of these factors significantly impacted on ground-based detection by experts and even on manual detection of koalas in drone-derived thermal imagery. This is significant in light of recent work that has proposed using drone thermal imagery for the detection of koalas in the absence of automated imagery (Beranek et al., 2020). The results of the current study suggest that attempts to detect koalas without machine learning approaches may yield significant biases. ...
Abstract Drones and machine learning‐based automated detection methods are being used by ecologists to conduct wildlife surveys with increasing frequency. When traditional survey methods have been evaluated, a range of factors have been found to influence detection probabilities, including individual differences among conspecific animals, which can thus introduce biases into survey counts. There has been no such evaluation of drone‐based surveys using automated detection in a natural setting. This is important to establish since any biases in counts made using these methods will need to be accounted for, to provide accurate data and improve decision‐making for threatened species. In this study, a rare opportunity to survey a ground‐truthed, individually marked population of 48 koalas in their natural habitat allowed for direct comparison of the factors impacting detection probability in both ground observation and drone surveys with manual and automated detection. We found that sex and host tree preferences impacted detection in ground surveys and in manual analysis of drone imagery with female koalas likely to be under‐represented, and koalas higher in taller trees detected less frequently when present. Tree species composition of a forest stand also impacted on detections. In contrast, none of these factors impacted on automated detection. This suggests that the combination of drone‐captured imagery and machine learning does not suffer from the same biases that affect conventional ground surveys. This provides further evidence that drones and machine learning are promising tools for gathering reliable detection data to better inform the management of threatened populations.
... Drones with thermal imaging mounts have been increasingly used to improve detection rates of rare and cryptic animals such as the koala (Beranek et al. 2020b), and this technology appears useful for wetland birds (e.g. Afán et al. 2018). ...
Some of the most difficult to detect Australian wetland birds include bitterns and snipes. Here I present novel nocturnal observations of the Australian Painted-snipe Rostratula australis and the Australian Little Bittern Ixobrychus dubius on Kooragang Island, NSW and discuss possible alternative survey methods based on these observations, in hopes of stimulating ideas for methods that increase the detection probability for these birds. The site contained 2.6 ha of wetlands which were surveyed for birds almost weekly (once during the day and once at night) from September to March during 2016 – 2019. During this time, a female Australian Painted-snipe was observed on three separate nights in September 2017, and a female Australian Little Bittern was observed once at night with certainty in November 2018. A male Australian Little Bittern was flushed during the day on 22/10/2019. There were several similarities for these observations: they all occurred within the same wetland, they occurred in spring when the wetlands had been charged with water for ~7 months and were in the process of drying, and most of the birds (with one exception) were observed at night. The snipe was detected from its eye-shine while the bittern was detected during a nocturnal reed search. Both species did not flush immediately when found in close-quarters at night time. I hypothesise that nocturnal visual encounter surveys in drying ephemeral wetlands during spring will lead to a higher detection probability of these species compared to traditional survey methods.
Unmanned aircraft find successful applications across various fields and continue to see increasing demand in numerous sectors. Modern flight control systems empower the creation and programming of unmanned vehicles for a diverse range of tasks.
(Research purpose) This study aims to retrospectively analyze the evolution of drone control systems, tracing their development from the early unmanned aerial vehicles to the flight controllers of modern multifunctional drones. (Materials and methods) The study employs the historical-analytical method for data collection and processing. This encompasses a thorough examination of original works by both domestic and foreign authors, including literary references, scientific journal articles, monographs, conference materials, museum exhibitions, photographic archives, and open-access software source code. (Results and discussion) The historical process of unmanned aerial vehicle development has led to the emergence of many types of designs that provide better flight performance and new functions through the creation of flight control systems. Designers integrated worldwide aviation expertise and the latest advancements in science, engineering, and technology to enhance unmanned systems. The miniaturization of flight control systems has facilitated the widespread adoption and application of unmanned aerial vehicle in many domains. The introduction of intelligent flight control modes has ensured a high level of autonomy in drone operations. (Conclusions) In the course of the research into the historical development of control systems for unmanned aerial vehicles, block diagrams illustrating these control systems were created. Additionally, a block diagram was constructed outlining the evolution of these systems, with a periodization of individual stages. The block diagram includes nine stages; with the current emphasis primarily directed towards the advancement of intelligent control systems. The findings confirm that the extensive diversification of unmanned aerial vehicle applications and functionalities is closely linked to the continuous development and enhancement of micro-electromechanical systems technologies. The study identifies the key flight controllers that have significantly influenced the enhancement of unmanned aircraft and have outlined potential directions for the future development of flight controllers.
The paper shows the possibility of using unmanned aerial vehicles with additional outboard equipment for aerial photography. It is noted that some parameters of the drone and additional suspension equipment are not taken into account by the software when calculating the drone flight time for one battery charge. ( Research purpose ) To develop an algorithm for calculating the flight time of an unmanned aerial vehicle with installed outboard equipment. ( Materials and methods ) The technical characteristics of DJI Phantom 4 pro and DJI Matrice 200v2 were studied, as well as the specifications of Parrot Sequoia, MicaSense Altum multispectral cameras mounted on the drone. The existing research results are used to calculate the flight mission time depending on the route length and the battery capacity. ( Results and discussion ) It is found that the maximum flight time of a drone with additional outboard equipment is reduced due to the additional equipment mass, increased power consumption, the preflight preparation time, the need to return to the take-off point and the necessity to preserve the battery life and save the flight load. The maximum flight time calculated for DJI Phantom 4 pro and DJI Matrice 200v2 with multispectral cameras Parrot Sequoia, MicaSense Altum is 8 minutes and 18 minutes, respectively, with a minimum flight load. A method for calculating the number of batteries for aerial photography with additional outboard equipment is determined. ( Conclusions ) An algorithm for calculating the flight time of an unmanned aerial vehicle with additional outboard equipment is developed, the parameters ignored by the standard software in the flight time calculation are taken into account.
A breeder’s job is a creative process that requires the routine collection and painstaking personal analysis of many types of data. This information is often subjective and cannot be statistically processed, relying only on the intuition of a scientist. One of these criteria for evaluating the source material is the visual assessment of overwintering varieties and breeding lines of winter crops. Overwintering expressed in points is approximate, and it is impossible to reliably compare breeding lines using it, especially when the points are approximately equal. For the first time in Russia, in the fields of FSBSI “Federal Scientific Center of Legumes and Groat Crops” (FSBSI FSC LGC) located in the Oryol region, elements of the developed method of remote sensing of small areas in the breeding process were tested based on “winter hardiness” of winter wheat, reliably expressed by vegetation indices. To assess breeding lines and crop varieties for winter hardiness, data were collected using unmanned vehicles at an altitude of 50 m and multispectral cameras with a resolution of 2 cm/pix. of Federal Scientific Agroengineering Center VIM. Previously, to determine the date of photography, an analysis of the weather conditions of the region for 20 years was carried out. It was revealed that regardless of the date of snow melting, the time of resumption of the spring vegetation of winter crops is located around the date of April 12. Accordingly, the third decade of April is recommended for optimal remote sensing of awakening crops in the region. Comparison of the data of vegetation indices (NDVI, NDRE, ClGreen) with the traditional results of visual scoring showed high reliability of the obtained digital data (correlation coefficient r > 0.7) for all three indices. It was noted that the NDVI index is more informative since it carries additional information not only about the preservation but also about the diversity of crops, i.e. on the presence of areas with fully or partially fallen out vegetation. The focal sparseness of crops was maximally characterized by the standard deviation of the NDVI index, increasing by 10…15% in the “dropped out” areas (correlation coefficient r = −0.55) in comparison to the other two. An objective statistical assessment of digital information from small areas (plot area of 8 sq. m.) on 29 variants made it possible to additionally identify 6 cultivars (with a score of overwintering, comparable to the reference cultivar for the region) and compare the 18 variants that stood out among them. This would be impossible with traditional visual methods. In general, remote assessment of winter crops overwintering using vegetation indices based on comparison to an adapted reference variety allows you to quickly and without the involvement of a highly specialized and highly qualified specialist in the field of plant growing accumulate objective information from year to year on the overwintering of a characteristic collection of winter crops. Accumulation of such objective structured digital information for different years, tied to the data of the reference variety, will allow the formation of data arrays for further machine learning of specialized neural networks.KeywordsWinter wheatUnmanned aerial vehicles (UAV)BreedingAerial dataVegetation indicesBig data
Drones or unoccupied aerial vehicles are rapidly being used for a spectrum of applications, including replacing traditional occupied aircraft as a means of approaching wildlife from the air. Though less intrusive to wildlife than occupied aircraft, drones can still cause varying levels of disturbance. Policies and protocols to guide lowest-impact drone flights are most likely to succeed if considerations are derived from knowledge from scientific literature. This study examines trends in the scientific literature on using drones to approach wildlife between 2000 and 2020, specifically in relation to the type of publications, scientific journals works are published in, the purposes of drone flights reported, taxa studied, and locations of studies. From 223 publications, we observed a large increase in relevant scientific literature, the majority of which were peer-reviewed articles published across 87 scientific journals. The largest proportions of peer-reviewed research articles related to aquatic mammals or aquatic birds, and the use or trial of drone flights for conducting population surveys, animal detection or investigations of animal responses to drone flights. The largest proportion of articles were studies conducted in North America and Australia. Since animal responses to drone flights vary between taxa, populations, and geographic locations, we encourage further growth in the volume of relevant scientific literature needed to inform policies and protocols for specific taxa and/or locations, particularly where knowledge gaps exist.
Context Drones, or remotely piloted aircraft systems, equipped with thermal imaging technology (RPAS thermal imaging) have recently emerged as a powerful monitoring tool for koala populations. Before wide uptake of novel technologies by government, conservation practitioners and researchers, evidence of greater efficiency and cost-effectiveness than with other available methods is required. Aims We aimed to provide the first comprehensive analysis of the cost-effectiveness of RPAS thermal imaging for koala detection against two field-based methods, systematic spotlighting (Spotlight) and the refined diurnal radial search component of the spot-assessment technique (SAT). Methods We conducted various economic comparisons, particularly comparative cost-effectiveness of RPAS thermal imaging, Spotlight and SAT for repeat surveys of a low-density koala population. We compared methods on cost-effectiveness as well as long-term costs by using accumulating cost models. We also compared detection costs across population density using a predictive cost model. Key results Despite substantial hardware, training and licensing costs at the outset (>A$49 900), RPAS thermal imaging surveys were cost-effective, detecting the highest number of koalas per dollar spent. Modelling also suggested that RPAS thermal imaging requires the lowest survey effort to detect koalas within the range of publicly available koala population densities (~0.006–18 koalas ha−1) and would provide long-term cost reductions across longitudinal monitoring programs. RPAS thermal imaging would also require the lowest average survey effort costs at a landscape scale (A$3.84 ha−1), providing a cost-effective tool across large spatial areas. Conclusions Our analyses demonstrated drone thermal imaging technology as a cost-effective tool for conservation practitioners monitoring koala populations. Our analyses may also form the basis of decision-making tools to estimate survey effort or total program costs across any koala population density. Implications Our novel approach offers a means to perform various economic comparisons of available survey techniques and guide investment decisions towards developing standardised koala monitoring approaches. Our results may assist stakeholders and policymakers to confidently invest in RPAS thermal imaging technology and achieve optimal conservation outcomes for koala populations, with standardised data collection delivered through evidence-based and cost-effective monitoring programs.
One of the biggest challenges is to determine the deployment and navigation of the drones to benefit the most for different applications. Many research questions have been raised about this topic. For example, drone-enabled wildlife monitoring has received much attention in recent years. Unfortunately, this approach results in significant disturbance to different species of wild animals. Moreover, with the capability of rapidly moving communication supply towards demand when required, the drone equipped with a base station, i.e., drone-cell, is becoming a promising solution for providing cellular networks to victims and rescue teams in disaster-affected areas. However, few studies have investigated the optimal deployments of multiple drone-cells with limited backhaul communication distances. In addition, the use of autonomous drones as flying interactors for many real-life applications has not been sufficiently discussed. With superior maneuverability, drone-enabled autonomous aerial interacting can potentially be used on shark attack prevention and animal herding. Nevertheless, previous studies of autonomous drones have not dealt with such applications in much detail. This report explores the solutions to all the mentioned research questions, with a particular focus on the deployment and navigation of the drones. Simulations have been conducted to verify the effectiveness of the proposed approaches. We believe that our findings in this report shed new light on the fundamental benefits of autonomous civilian drones.
This study developed and tested the efficacy of a real-time thermography technique to improve survey methods for Australian arboreal mammal species, with a focus on the greater glider. Development involved the use of thermal imaging cameras combined with spotlight transect surveys of an endangered greater glider population at Seven Mile Beach National Park. Over 30h of nocturnal spotlight transect surveys were undertaken over 14 (1km) transects within 70ha of dry sclerophyll forest. A protocol for the use of thermography to survey greater gliders was developed. The efficacy of the thermography protocol was then experimentally tested in comparison to traditional spotlighting. Overall, thermography was better at detecting arboreal mammals than spotlighting (P<0.05). However, the effect was not significant for greater gliders (P=0.79), even though there was a trend towards improved detection of the species using thermal cameras. Thermography is a novel approach to undertaking arboreal mammal surveys and future studies should consider its relevance, effectiveness and associated costs to improve survey designs, especially for threatened species.
Effective wildlife management relies on the accurate and precise detection of individual animals. These can be challenging data to collect for many cryptic species, particularly those that live in complex structural environments. This study introduces a new automated method for detection using published object detection algorithms to detect their heat signatures in RPAS-derived thermal imaging. As an initial case study we used this new approach to detect koalas (Phascolarctus cinereus), and validated the approach using ground surveys of tracked radio-collared koalas in Petrie, Queensland. The automated method yielded a higher probability of detection (68–100%), higher precision (43–71%), lower root mean square error (RMSE), and lower mean absolute error (MAE) than manual assessment of the RPAS-derived thermal imagery in a comparable amount of time. This new approach allows for more reliable, less invasive detection of koalas in their natural habitat. This new detection methodology has great potential to inform and improve management decisions for threatened species, and other difficult to survey species.
Unmanned aircraft systems (UAS; i.e. 'drones') provide new opportunities for data collection in ecology, wildlife biology and conservation. Yet, several studies have documented behavioral or physiological responses to close-proximity UAS flights. We experimentally tested whether American black bears (Ursus americanus) habituate to repeated UAS exposure and whether tolerance levels persist during an extended period without UAS flights. Using implanted cardiac biologgers, we measured heart rate (HR) of five captive bears before and after the first of five flights each day. Spikes in HR, a measure of stress, diminished across the five flights within each day and over the course of 4 weeks of twice-weekly exposure. We halted flights for 118 days, and when we resumed, HR responses were similar to that at the end of the previous trials. Our findings highlight the capacity of a large mammal to become and remain habituated to a novel anthropogenic stimulus in a relatively short time (3-4 weeks). However, such habituation to mechanical noises may reduce their wariness of other human threats. Also, whereas cardiac effects diminished, frequent UAS disturbances may have other chronic physiological effects that were not measured. We caution that the rate of habituation may differ between wild and captive animals: while the captive bears displayed large initial spikes in HR change (albeit not as large as wild bears), these animals were accustomed to regular exposure to humans and mechanical noises that may have hastened habituation to the UAS.
Animals of the rainforest canopies are often endangered by deforestation or hunting but are difficult to survey and study because of the inaccessibility of the treetops, combined with the visual camouflage of many species. Drone-based thermal sensors have the potential to overcome these hurdles by rapidly scanning large forested areas from above, detecting and mapping wildlife based on the contrast between their warm body temperatures and the cool tree canopies. We tested this concept by flying a drone-mounted thermal infrared radiometric sensor over the wildlife-rich rainforests of Barro Colorado Island, Panama. Arboreal mammals had body temperatures around 27°C and were conspicuous in the thermal infrared imagery at night and early morning when the forest canopy was cool (23–25°C), but were difficult to detect by mid-morning, by which time the direct sunshine had heated up canopy vegetation to over 30°C. Species were difficult to identify from thermal infrared imagery alone, but could be recognized from synchronized visual images taken during the daytime. Simultaneous drone and ground-based surveys of the same area proved that the aerial thermal camera did detect high-canopy species missed by the terrestrial observer, but that substantially more animals were detected by the human than by the drone. Because animal detection was so much better at night, when species ID was difficult, we suggest that future work could combine automated detection of animals from thermal infrared imagery with flash photography or IR illumination to enable species ID during nocturnal surveys. We conclude by discussing various logistical challenges that limit the utility of drone-based thermal infrared today, but that could be overcome by continued improvement of technology and collaboration with permitting agencies.
Retention forestry aims to mitigate impacts of native forestry on biodiversity, but data are limited on its effectiveness for threatened species. We used acoustics to investigate the resilience of a folivorous marsupial, the koala Phascolarctos cinereus, to timber harvesting where a key mitigation practice is landscape exclusion of harvesting. We deployed acoustic recorders at 171 sites to record male bellows (~14,640 hours) for use in occupancy modelling and for comparisons of bellow rate (bellows night⁻¹). Surveys targeted modelled medium-high quality habitat, with sites stratified by time since logging and logging intensity, including old growth as a reference. After scanning recordings with software to identify koala bellows, we found a high probability of detection (~0.45 per night), but this varied with minimum temperature and recorder type. Naïve occupancy was ~ 64% across a broad range of forests, which was at least five times more than expected based on previous surveys using alternative methods. After accounting for imperfect detection, probability of occupancy was influenced by elevation (-ve), cover of important browse trees (+ve), landscape NDVI (+ve) and extent of recent wildfire (-ve, but minor effect). Elevation was the most influential variable, though the relationship was non-linear and low occupancy was most common at tableland elevations (> 1000 m). Neither occupancy nor bellow rate were influenced by timber harvesting intensity, time since harvesting or local landscape extent of harvesting or old growth. Extrapolation of occupancy across modelled habitat indicates that the hinterland forests of north-east NSW support a widespread, though likely low density koala population that is considerably larger than previously estimated. Retention forestry has a significant role to play in mitigating harvesting impacts on biodiversity, including for forest specialists, but localised studies are needed to optimise prescriptions for koalas.
Koalas (Phascolarctos cinereus) are difficult to detect due to their cryptic nature, occurrence at low densities and broad distribution. We compare the relative effectiveness of two common, direct survey techniques used to detect koalas: spotlighting and diurnal searches. Seventy-six 2-ha sites were surveyed using both spotlighting and diurnal searching. Each site was surveyed for 0.5 person-hours, such that search area and effort were equal. In this study, spotlighting was found to be 3.25 times more effective at detecting koalas than day searches. Therefore, where access and terrain allows, spotlighting surveys offer a significant advantage over diurnal searches in the detection of koalas.
Drones are rapidly becoming a key part of the toolkit for a range of scientific disciplines, as well as a range of management and commercial applications. This presents challenges in the context of how drone use might impact on nearby wildlife, especially birds as they might share the airspace. This paper presents observations (from 97 flight hours) and offers preliminary guidance for drone-monitoring exercises and future research to develop guidelines for safe and effective monitoring with drones. Our study sites spanned a range of arid, semi-arid, dunefield, floodplain, wetland, woodland, forest, coastal heath and urban environments in south-eastern and central Australia. They included a nesting colony of >200 000 Straw-necked Ibis Threskiornis spinicollis, the largest drone-based bird-monitoring exercise to date. We particularly focused on behavioural changes towards drones during the breeding season, interactions with raptors, and effects on birds nesting in large colonies—three areas yet to be explored in published literature. Some aggressive behaviour was encountered from solitary breeding birds, but several large breeding bird colonies were surveyed without such issues. With multi-rotor drones, we observed no incidents that posed a threat to birds, but one raptor attacked and took down a fixed-wing drone. In addition to providing observations of interactions with specific bird species, we detail our procedures for flight planning, safe flying and avoidance of birds, and highlight the need for more research into bird–drone interactions, most notably with respect to territorial breeding birds, safety around large raptors, and the effects of drones on the behaviour of birds in large breeding colonies.
Drones and unmanned aerial vehicles are increasingly used in research on wildlife. Their wide applications can also give interesting insights into habitat use and population distribution. However, the disturbance they might be responsible for, on species and especially in protected areas has yet to be investigated. We assessed and compared the behavioural response of 11 southern seabird species at the Crozet Islands, Southern Indian Ocean, to drone approaches at specific altitudes. We first show that the behavioural response differed between species depending on the altitude of the drone approach. At 50 m of altitude, only one of the studied species showed a detectable reaction, whereas at 10 m, most species showed strong behavioural postures of stress. Adult penguins breeding in large colonies, and some albatross species showed little behavioural response even when the drone was as close as 3 m, whereas other species such as giant petrels or cormorants appeared highly sensitive to drone approaches. Among King Penguins, although incubating adults showed little signs of behavioural stress, non-breeding adults and fledglings in crèches exhibited strong behavioural responses to the drone approach. Monitoring heart rate allowed us to investigate the link between behavioural and physiological response to that specific potential stressor in king penguins. Whereas we confirmed the expected link between physiological and behavioural response in chicks, breeding adults showed no behavioural sign of stress but had a significant increase in heart rate, the relative increase being higher than in chicks. All together these results have important implications for the conservation of species and should be helpful for future legislations on the use of drones.
Tropical deforestation continues to be a major driver of biodiversity loss and greenhouse gas emissions. Remote sensing technology is increasingly used to assess changes in forest cover, species distributions and carbon stocks. However, satellite and airborne sensors can be prohibitively costly and inaccessible for researchers in developing countries. Here, we describe the development and use of an inexpensive (<$2,000) unmanned aerial vehicle for surveying and mapping forests and biodiversity (referred to as ‘Conservation Drone’ hereafter). Our prototype drone is able to fly pre-programmed missions autonomously for a total flight time of ~25 minutes and over a distance of ~15 km. Non-technical operators can program each mission by defining waypoints along a flight path using an open-source software. This drone can record videos at up to 1080 pixel resolution (high definition), and acquire aerial photographs of <10 cm pixel resolution. Aerial photographs can be stitched together to produce real-time geo-referenced land use/cover maps of surveyed areas. We evaluate the performance of this prototype Conservation Drone based on a series of test flights in Aras Napal, Sumatra, Indonesia. We discuss the further development of Conservation Drone 2.0, which will have a bigger payload and longer range. Initial tests suggest a flight time of ~50 minutes and a range of ~25 km. Finally, we highlight the potential of this system for environmental and conservation applications, which include near real-time mapping of local land cover, monitoring of illegal forest activities, and surveying of large animal species.
In principle, conservation planning relies on long-term data; in reality, conservation decisions are apt to be based upon limited data and short-range goals. For the koala (Phascolarctos cinereus), frequently reliance is made on the assumption that indirect signs can be used to indicate behavioural preferences, such as diet choice. We examined the relationship between the use of trees by koalas and the presence of scats beneath those trees. Tree use was associated with scat presence on 49% of occasions when koalas were radio-tracked in both central Queensland (n = 10 koalas) and south-east Queensland (n = 5 koalas), increasing to 77% of occasions when trees were rechecked the following day. Koala densities were correlated with scat abundance at sites with koala density between ~0.2 and 0.6 koalas per hectare. Our results confirm that scat searches are imprecise indicators of tree use by koalas, but demonstrate that these searches can be used, with caveats, to estimate koala population densities. We discuss how errors in estimating or applying predictive model parameters can bias estimates of occupancy and show how a failure to validate adequately the assumptions used in modelling and mapping can undermine the power of the products to direct rational conservation and management efforts.
Establishing species distribution and population trends are basic requirements in conservation biology, yet acquiring this fundamental information is often difficult. Indirect survey methods that rely on fecal pellets (scats) can overcome some difficulties but present their own challenges. In particular, variation in scat detectability and decay rate can introduce biases. We studied how vegetation communities affect the detectability and decay rate of scats as exemplified by koalas Phascolarctos cinereus: scat detectability was highly and consistently dependent on ground layer complexity (introducing up to 16% non-detection bias); scat decay rates were highly heterogeneous within vegetation communities; exposure of scats to surface water and rain strongly accelerated scat decay rate and finally, invertebrates were found to accelerate scat decay rate markedly, but unpredictably. This last phenomenon may explain the high variability of scat decay rate within a single vegetation community. Methods to decrease biases should be evaluated when planning scat surveys, as the most appropriate method(s) will vary depending on species, scale of survey and landscape characteristics. Detectability and decay biases are both stronger in certain vegetation communities, thus their combined effect is likely to introduce substantial errors in scat surveys and this could result in inappropriate and counterproductive management decisions.
Regional and national surveys provide a broadscale description of the koala's present distribution in Australia. A detailed understanding of its distribution is precluded, however, by past and continuing land clearing across large parts of the koala's range. Koala population density increased in some regions during the late 1800s and then declined dramatically in the early 1900s. The decline was associated with habitat loss, hunting, disease, fire, and drought. Declines are continuing in Queensland and New South Wales. In contrast, dense koala populations in habitat isolates in Victoria and South Australia are managed to reduce population size and browse damage. Current understanding of koala distribution and abundance suggests that the species does not meet Australian criteria as endangered or vulnerable fauna. Its conservation status needs to be reviewed, however, in light of the extensive land clearing in New South Wales and Queensland since the last (1980s) broadscale surveys. Consequently, we recommend that broadacre clearing by curtailed in New South Wales and Queensland and that regular, comprehensive, standardized, national koala surveys be undertaken. Given the fragmentation of koala habitat and regional differences in the status of the koala, we recommended that studies on regional variation in the koala be intensified and that koala ecology in fragmented and naturally restricted habitats be developed. More generally, the National Koala Conservation Strategy should be implemented.
Infrared thermography is an increasingly used technology in veterinary science and in mammal physiology. However, its employment as a quantitative method to accurately determine mammal surface temperatures requires knowledge of the emissivity of that individual’s pelage. To-date, few researchers have measured emissivity of their study animal’s pelage, or determined the relationship between fur metrics and emissivity. Instead, studies have relied on historic values generated from a single study on arctic fauna. Therefore, this study aimed to determine pelage emissivity for a range of mammal species and to establish the putative correlation between emissivity and fur metrics. Emissivity was measured at different sites of the body for 22 species. In addition, hair length and hair diameter were measured from hairs collected at the same sites that emissivity was measured. The mean pelage emissivity of sampled specimens was 0.86 ± 0.01, which was lower than the range (0.95–1.00) reported previously. Emissivity was neither related to taxonomy nor to hair metrics but may be related to other factors not measured in this study. Contrary to common practice, a single (0.98) or a narrow range (0.95–1.00) of emissivity values is unlikely to be appropriate for obtaining accurate surface temperature readings in quantitative IRT studies on mammals.
Management actions designed to mitigate development or anthropogenic impacts on species of conservation concern are often implemented without quantifying the benefit to the species. It is often unclear what combinations and intensities of management actions are required to achieve meaningful conservation outcomes. We investigate whether disease and predator control can reverse population declines of koalas ( Phascolarctos cinereus ).
Based on longitudinal monitoring of the epidemiological and demographic status of over 500 animals over 4 years, coupled with an intensive disease and predator management programme, we use survival analyses to estimate annual age‐specific survival rates and population growth, and simulations to quantify the benefit of these actions.
Predation and disease accounted for 63% and 29% of mortality, respectively, across all years, with wild dog (dingoes or dingo‐hybrids: Canis dingo , C. dingo × Canis familiaris ), carpet pythons ( Morelia spilota ) and domestic dogs ( C. familiaris ) accounting for 82%, 14% and 4% of confirmed predation mortalities, respectively. In the first 2 years, before disease and dog control had major impact, the population was declining rapidly with annual growth rates of 0.66 and 0.90. In the third and fourth years, after interventions had been fully implemented, the population growth rate had increased to 1.08 and 1.20. The intrinsic survival rate of joeys was 71.2% (excluding deaths resulting from the death of the mother). Adult survival rates varied as a function of sex, age and year.
Even in a declining koala population, management actions can achieve meaningful conservation outcomes (population growth rates greater than one). However, benefits may be short‐lived in the absence of longer term strategies to manage threats. This work also identifies wild dogs as a major threat to koalas, highlighting the need to better understand how wild dog impacts vary in space and time.
Policy implications . Offsetting policy that addresses habitat loss alone may achieve little or no meaningful benefit to declining koalas populations. Management must address suites of threats affecting these populations and ensure that the cumulative effects of these actions achieve positive population growth rates.
Unmanned aerial vehicles (UAVs) have the potential to revolutionize the way research is conducted in many scientific fields [1, 2]. UAVs can access remote or difficult terrain [3], collect large amounts of data for lower cost than traditional aerial methods, and facilitate observations of species that are wary of human presence [4]. Currently, despite large regulatory hurdles [5], UAVs are being deployed by researchers and conservationists to monitor threats to biodiversity [6], collect frequent aerial imagery [7-9], estimate population abundance [4, 10], and deter poaching [11]. Studies have examined the behavioral responses of wildlife to aircraft [12-20] (including UAVs [21]), but with the widespread increase in UAV flights, it is critical to understand whether UAVs act as stressors to wildlife and to quantify that impact. Biologger technology allows for the remote monitoring of stress responses in free-roaming individuals [22], and when linked to locational information, it can be used to determine events [19, 23, 24] or components of an animal's environment [25] that elicit a physiological response not apparent based on behavior alone. We assessed effects of UAV flights on movements and heart rate responses of free-roaming American black bears. We observed consistently strong physiological responses but infrequent behavioral changes. All bears, including an individual denned for hibernation, responded to UAV flights with elevated heart rates, rising as much as 123 beats per minute above the pre-flight baseline. It is important to consider the additional stress on wildlife from UAV flights when developing regulations and best scientific practices.
Copyright © 2015 Elsevier Ltd. All rights reserved.
Presence–absence surveys are a commonly used method for monitoring broad-scale changes in wildlife distributions. However, the lack of power of these surveys for detecting population trends is problematic for their application in wildlife management. Options for improving power include increasing the sampling effort or arbitrarily relaxing the type I error rate. We present an alternative, whereby targeted sampling of particular habitats in the landscape using information from a habitat model increases power. The advantage of this approach is that it does not require a trade-off with either cost or the Pr{type I error} to achieve greater power. We use a demographic model of koala ( Phascolarctos cinereus ) population dynamics and simulations of the monitoring process to estimate the power to detect a trend in occupancy for a range of strategies, thereby demonstrating that targeting particular habitat qualities can improve power substantially. If the objective is to detect a decline in occupancy, the optimal strategy is to sample high-quality habitats. Alternatively, if the objective is to detect an increase in occupancy, the optimal strategy is to sample intermediate-quality habitats. The strategies with the highest power remained the same under a range of parameter assumptions, although observation error had a strong influence on the optimal strategy. Our approach specifically applies to monitoring for detecting long-term trends in occupancy or abundance. This is a common and important monitoring objective for wildlife managers, and we provide guidelines for more effectively achieving it.
Distance sampling using line transects has not been previously used or tested for estimating koala abundance. In July 2001, a pilot survey was conducted to compare the use of line transects with strip transects for estimating koala abundance. Both methods provided a similar estimate of density. On the basis of the results of the pilot survey, the distribution and abundance of koalas in the Pine Rivers Shire, south-east Queensland, was determined using line-transect sampling. In total, 134 lines (length 64 km) were used to sample bushland areas. Eighty-two independent koalas were sighted. Analysis of the frequency distribution of sighting distances using the software program DISTANCE enabled a global detection function to be estimated for survey sites in bushland areas across the Shire. Abundance in urban parts of the Shire was estimated from densities obtained from total counts at eight urban sites that ranged from 26 to 51 ha in size. Koala abundance in the Pine Rivers Shire was estimated at 4584 (95% confidence interval, 4040-5247). Line-transect sampling is a useful method for estimating koala abundance provided experienced koala observers are used when conducting surveys.
Hot monkey, cold reality: surveying rainforest canopy mammals using drone-mounted thermal infrared sensors
- R Kays
- J Sheppard
- K Mcclean
- C Welch
- C Paunescu
- V Wang
- G Kravit
- M Crofoot
Kays, R., Sheppard, J., McClean, K., Welch, C., Paunescu, C., Wang, V.,
Kravit, G., and Crofoot, M. (2019). Hot monkey, cold reality: surveying
rainforest canopy mammals using drone-mounted thermal infrared
sensors. International Journal of Remote Sensing 40, 407-419. doi:10.
1080/01431161.2018.1523580
Monitoring Threatened Species and Ecological Communities
- S Legge
- D B Lindenmayer
- N M Robinson
- B C Scheele
- D M Southwell
- B A Wintle
Legge, S., Lindenmayer, D. B., Robinson, N. M., Scheele, B. C., Southwell,
D. M., and Wintle, B. A. (2018). 'Monitoring Threatened Species and
Ecological Communities.' (CSIRO Publishing: Melbourne.)