Semi-Automated Counts on Drone Imagery of Breeding Seabirds Using Free Accessible Software

Corregidor-Castro, Alejandro; Valle, Roberto G.

doi:10.5253/arde.v110i1.a7

Cited by 4 publications

(6 citation statements)

References 42 publications

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“…Lastly, one of the most prominent disadvantages with UAVs is the timeconsuming data analysis process. Currently, there is an increased interest in supporting the use of automated counting methods using image recognition software, which if reliable, would mean a noticeable reduction in data analysis time [12,26,51]. Thus, it is important to work on methodologies that would allow for automatic ways of counting and processing the data, so the efficiency of UAVs outweighs traditional methods of surveying.…”

Section: Discussionmentioning

confidence: 99%

Monitoring Colonies of Large Gulls Using UAVs: From Individuals to Breeding Pairs

et al. 2022

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Measuring success or failure in the conservation of seabirds depends on reliable long-term monitoring. Traditionally, this monitoring has been based on line transects and total or point counts, all of which are sensitive to subjective interpretation. Such methods have proven to consistently record fewer individuals than intensive efforts, while requiring many hours of fieldwork and resulting in high disturbance. New technologies, such as drones, are potentially useful monitoring tools, as they can cover large areas in a short time, while providing high-resolution data about bird numbers and status. This study conducted two types of Uncrewed Aerial Vehicle (UAV) surveys in a big colony of multispecies breeding gulls. From a 25 m height, we photographed 30 circle plots where nests were also counted on the ground, showing that the number of occupied nests/breeding pairs could be estimated accurately by multiplying the number of counted individuals with a 0.7 conversion factor. A fixed-wing UAV was used to photograph the entire island to compare drone counts with counts conducted by traditional methods, were we counted a higher number of breeding pairs than the traditional count (1.7–2.2 times more individuals). It was concluded that UAVs provided improved estimates of colony size with much reduced monitoring effort.

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Section: Discussionmentioning

confidence: 99%

Monitoring Colonies of Large Gulls Using UAVs: From Individuals to Breeding Pairs

et al. 2022

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“…The recent development of uncrewed aerial vehicles (UAVs), commonly referred to as drones, has provided useful to overcome the aforementioned limitations (Anderson & Gaston 2013). Drones have proven to be efficient to monitor areas that are otherwise inaccessible, such as reedbeds (Afán et al 2018, Lachman et al 2020), at a lower cost (Canal & Negro 2018, Jones et al 2020) while spending less time (Valle 2021, Corregidor-Castro & Valle 2022). In addition, the data obtained from drones surveys has been shown to be as precise as traditional ground methods for colonial birds in coastal areas, with agreements between ground and drone counts ranging from 94–96% (Chabot et al 2015, Jones et al 2020), only with marked differences in some cases due to better results in the drone counts: 36 to 96% more birds detected (Hodgson et al 2016, Dundas et al 2021), especially when monitoring cryptic species i.e.…”

Section: Introductionmentioning

confidence: 99%

Faster and Better: Comparison between Traditional and Drone Monitoring in a Cryptic Species, the Purple Heron Ardea purpurea

Corregidor-Castro

Scarton

Panzarin³

et al. 2023

Acta Ornithologica

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Monitoring waterbirds is fundamental to understand the health status of wetland habitats. However, this monitoring has to be conducted by means of reliable data collection that can provide accurate information on population trends. Usually, waterbird monitoring is difficult, as nesting grounds are usually located in inaccessible reedbed, and by eye detection of cryptic species is hard. Drones have the capacity to overcome most of these problems, as they can provide with an aerial view of places otherwise unreachable, while reducing the disturbance and time spent in the field. The present study aims to compare the accuracy, disturbance levels, and managerial efficiency between ground (traditional) and drone counts of a cryptic species, the Purple Heron Ardea purpurea. Traditional monitoring methods were only capable of detecting 35% of the nesting pairs detected by the drone surveys (8.0 ± 11.8 versus 22.9 ± 38.2 nesting pairs in ground and drone surveys, respectively). Consequently, colony size estimates between methods showed poor agreement, to the point that traditional methods missed colonies otherwise detected by the drone. No apparent negative effects on nesting pairs where found when flying the drone. In addition, mean time spent to survey breeding sites with a drone was far less than with the traditional approach, down to a six-fold time reduction. This reduction, together with a lack of disturbance observed when conducting the drone monitoring, and an increasing monitoring precision and accuracy, supports the use of drones as the least invasive option for studies on population monitoring on hardly accessible sites.

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“…There are several successful cases of applications with uninhabited aerial systems used in wildlife surveying and monitoring (Wilson et al, 2022;Reckling et al, 2021;Rominger and Meyer, 2021;Schroder et al, 2021;Marzialetti et al, 2021), with many focusing in ornithology in particular (Ooi, 2020;Dulava et al, 2015;Valle and Scarton, 2019a;Corregidor-Castro and Valle, 2022;Bushaw et al, 2020). The use of UAS in ornithology is not a new concept, but recent advances in technology have made it possible to collect data with a higher quality and at a lower cost, leading to increased popularity.…”

Section: Ornithology Missions For Uasmentioning

confidence: 99%

“…With easier access to commercially available vehicles carrying powerful sensors, uninhabited aircraft have also become a powerful tool for researchers in many fields, specially as an effective and possibly low cost alternative to data collection. In the field of ecological research, drones have been successfully used in a variety of different applications (Dulava et al, 2015), perhaps most popularly in population tracking (Valle and Scarton, 2019a) and wildlife surveying (Corregidor-Castro and Valle, 2022) for a variety of different species (Schroder et al, 2021;Marzialetti et al, 2021;Wilson et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

“…In many ecological research drone missions, data is collected in the form of images and videos for the development of computer vision applications (Wilson et al, 2022;Corregidor-Castro and Valle, 2022), often employing deep learning models (Reckling et al, 2021;Rominger and Meyer, 2021;Richardson et al, 2021;Ooi, 2020). The success of deep learning applications with drone imagery is associated with the flexibility offered by lightweight aircraft carrying high resolution cameras that are capable of collecting large volumes of data from a bird's eye view perspective.…”

Section: Introductionmentioning

confidence: 99%

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Deep Learning and Synthetic Imagery for Migratory Bird Species Identification Using Drones

Costa¹

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Recent technology advancements have caused a significant increase in popularity and availability of uninhabited aerial systems (UAS). Commercially available platforms are often equipped with powerful sensors, and have become a tool for researchers in many fields. In ornithology, using drones for surveying and population monitoring of different bird species is a relatively lower cost and higher time efficiency approach, when compared to ground based alternatives. In this thesis work, the use of UAS in the study of migratory shorebird species in Canada is explored with the development of computer vision applications. More specifically, a deep learning classification model is trained to identify the presence of birds of a given species in an image. The species selected for the first iteration of the application is the Canada geese, which is not one of the migratory shorebird species of interest, but is used as a proxy due to its availability and similar melanin colours. Images

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Semi-Automated Counts on Drone Imagery of Breeding Seabirds Using Free Accessible Software

Cited by 4 publications

References 42 publications

Monitoring Colonies of Large Gulls Using UAVs: From Individuals to Breeding Pairs

Monitoring Colonies of Large Gulls Using UAVs: From Individuals to Breeding Pairs

Faster and Better: Comparison between Traditional and Drone Monitoring in a Cryptic Species, the Purple Heron Ardea purpurea

Deep Learning and Synthetic Imagery for Migratory Bird Species Identification Using Drones

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