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Drones
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Drone-Based Wildlife Protection, Monitoring, and Conservation Management
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Drone-Based Wildlife Protection, Monitoring, and Conservation Management

A special issue of Drones (ISSN 2504-446X). This special issue belongs to the section "Drones in Ecology".

Deadline for manuscript submissions: 15 May 2024 | Viewed by 22260

Special Issue Editors

Dr. Humberto L. Perotto-Baldivieso

E-Mail Website
Guest Editor
Department of Rangeland, Wildlife, and Fisheries Management, Texas A&M University, 305 Horticulture/Forest Science Building (HFSB), College Station, TX 77843-2138, USA
Interests: landscape ecology; remote sensing; spatial ecology; drones
Special Issues, Collections and Topics in MDPI journals
Dr. Aaron M. Foley

E-Mail Website
Guest Editor
Caesar Kleberg Wildlife Research Institute, Texas A&M University-Kingsville, 700 University Blvd, MSC 218, Kingsville, TX 78363, USA
Interests: wildlife management; population estimation; survey methods; large mammal ecology

Special Issue Information

Dear Colleagues,

This Special Issue focuses on the application of drones to aid in the protection and management of wildlife. The use and applications of drones for wildlife studies has increased significantly in the last decade. From detection to population estimation and habitat assessment, drones are now an integral part of the wildlife professional toolbox.

We welcome research that examines the use of drone technology to improve our understanding of wildlife research and wildlife management. This Special Issue welcomes a variety of topics including:

  1. Species detection protocols;
  2. Methodological approaches to estimate wildlife populations;
  3. Geospatial approaches to assess wildlife populations;
  4. Wildlife monitoring;
  5. Remote data collection using drones and other sensors in the field;
  6. Habitat wildlife relationships using data derived from drones;
  7. Sensors, wildife, and habitat.

Dr. Humberto L. Perotto-Baldivieso
Dr. Aaron M. Foley
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Drones is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • habitat monitoring
  • LiDAR
  • population estimation
  • thermal
  • wildlife conservation
  • wildlife management
  • wildlife monitoring
  • wildlife species detection

Published Papers (10 papers)

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Research

22 pages, 1971 KiB  
Article
Estimating Total Length of Partially Submerged Crocodylians from Drone Imagery
by Clément Aubert, Gilles Le Moguédec, Alvaro Velasco, Xander Combrink, Jeffrey W. Lang, Phoebe Griffith, Gualberto Pacheco-Sierra, Etiam Pérez, Pierre Charruau, Francisco Villamarín, Igor J. Roberto, Boris Marioni, Joseph E. Colbert, Asghar Mobaraki, Allan R. Woodward, Ruchira Somaweera, Marisa Tellez, Matthew Brien and Matthew H. Shirley
Drones 2024, 8(3), 115; https://0-doi-org.brum.beds.ac.uk/10.3390/drones8030115 - 21 Mar 2024
Viewed by 2275
Abstract
Understanding the demographic structure is vital for wildlife research and conservation. For crocodylians, accurately estimating total length and demographic class usually necessitates close observation or capture, often of partially immersed individuals, leading to potential imprecision and risk. Drone technology offers a bias-free, safer [...] Read more.
Understanding the demographic structure is vital for wildlife research and conservation. For crocodylians, accurately estimating total length and demographic class usually necessitates close observation or capture, often of partially immersed individuals, leading to potential imprecision and risk. Drone technology offers a bias-free, safer alternative for classification. We evaluated the effectiveness of drone photos combined with head length allometric relationships to estimate total length, and propose a standardized method for drone-based crocodylian demographic classification. We evaluated error sources related to drone flight parameters using standardized targets. An allometric framework correlating head to total length for 17 crocodylian species was developed, incorporating confidence intervals to account for imprecision sources (e.g., allometric accuracy, head inclination, observer bias, terrain variability). This method was applied to wild crocodylians through drone photography. Target measurements from drone imagery, across various resolutions and sizes, were consistent with their actual dimensions. Terrain effects were less impactful than Ground-Sample Distance (GSD) errors from photogrammetric software. The allometric framework predicted lengths within ≃11–18% accuracy across species, with natural allometric variation among individuals explaining much of this range. Compared to traditional methods that can be subjective and risky, our drone-based approach is objective, efficient, fast, cheap, non-invasive, and safe. Nonetheless, further refinements are needed to extend survey times and better include smaller size classes. Full article
(This article belongs to the Special Issue Drone-Based Wildlife Protection, Monitoring, and Conservation Management)
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13 pages, 7015 KiB  
Article
Evaluating the Use of a Thermal Sensor to Detect Small Ground-Nesting Birds in Semi-Arid Environments during Winter
by J. Silverio Avila-Sanchez, Humberto L. Perotto-Baldivieso, Lori D. Massey, J. Alfonso Ortega-S., Leonard A. Brennan and Fidel Hernández
Drones 2024, 8(2), 64; https://0-doi-org.brum.beds.ac.uk/10.3390/drones8020064 - 15 Feb 2024
Viewed by 2126
Abstract
Aerial wildlife surveys with fixed-wing airplanes and helicopters are used more often than on-the-ground field surveys to cover areas that are both extensive and often inaccessible. Drones with high-resolution thermal sensors are being widely accepted as research tools to aid in monitoring wildlife [...] Read more.
Aerial wildlife surveys with fixed-wing airplanes and helicopters are used more often than on-the-ground field surveys to cover areas that are both extensive and often inaccessible. Drones with high-resolution thermal sensors are being widely accepted as research tools to aid in monitoring wildlife species and their habitats. Therefore, our goal was to assess the feasibility of detecting northern bobwhite quail (Colinus virginianus, hereafter ‘bobwhite’) using drones with a high-resolution thermal sensor. Our objectives were (1) to identify the altitudes at which bobwhites can be detected and (2) compare the two most used color palettes to detect species (black-hot and isotherm). We achieved this goal by performing drone flights at different altitudes over caged tame bobwhites and capturing still images and video recordings at altitudes from 18 to 42 m. We did not observe or detect any obvious signs of distress, movement, or fluttering of bobwhites inside cages caused by the noise or presence of the drone during data acquisition. We observed the highest counts of individual bobwhites with the black-hot thermal palette at 18 m (92%; x¯ = 47 bobwhites; SE = 0.41) and at 24 m (81%; x¯ = 41 bobwhites; SE = 0.89). The isotherm thermal palette had lower count proportions. The use of video to count quail was not feasible due to the low resolution of the video and the species size. Flying drones with high-resolution thermal sensors provided reliable imagery to detect roosting bobwhite individuals in South Texas during the winter. Full article
(This article belongs to the Special Issue Drone-Based Wildlife Protection, Monitoring, and Conservation Management)
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19 pages, 1791 KiB  
Article
Detection Probability and Bias in Machine-Learning-Based Unoccupied Aerial System Non-Breeding Waterfowl Surveys
by Reid Viegut, Elisabeth Webb, Andrew Raedeke, Zhicheng Tang, Yang Zhang, Zhenduo Zhai, Zhiguang Liu, Shiqi Wang, Jiuyi Zheng and Yi Shang
Drones 2024, 8(2), 54; https://0-doi-org.brum.beds.ac.uk/10.3390/drones8020054 - 06 Feb 2024
Viewed by 1611
Abstract
Unoccupied aerial systems (UASs) may provide cheaper, safer, and more accurate and precise alternatives to traditional waterfowl survey techniques while also reducing disturbance to waterfowl. We evaluated availability and perception bias based on machine-learning-based non-breeding waterfowl count estimates derived from aerial imagery collected [...] Read more.
Unoccupied aerial systems (UASs) may provide cheaper, safer, and more accurate and precise alternatives to traditional waterfowl survey techniques while also reducing disturbance to waterfowl. We evaluated availability and perception bias based on machine-learning-based non-breeding waterfowl count estimates derived from aerial imagery collected using a DJI Mavic Pro 2 on Missouri Department of Conservation intensively managed wetland Conservation Areas. UASs imagery was collected using a proprietary software for automated flight path planning in a back-and-forth transect flight pattern at ground sampling distances (GSDs) of 0.38–2.29 cm/pixel (15–90 m in altitude). The waterfowl in the images were labeled by trained labelers and simultaneously analyzed using a modified YOLONAS image object detection algorithm developed to detect waterfowl in aerial images. We used three generalized linear mixed models with Bernoulli distributions to model availability and perception (correct detection and false-positive) detection probabilities. The variation in waterfowl availability was best explained by the interaction of vegetation cover type, sky condition, and GSD, with more complex and taller vegetation cover types reducing availability at lower GSDs. The probability of the algorithm correctly detecting available birds showed no pattern in terms of vegetation cover type, GSD, or sky condition; however, the probability of the algorithm generating incorrect false-positive detections was best explained by vegetation cover types with features similar in size and shape to the birds. We used a modified Horvitz–Thompson estimator to account for availability and perception biases (including false positives), resulting in a corrected count error of 5.59 percent. Our results indicate that vegetation cover type, sky condition, and GSD influence the availability and detection of waterfowl in UAS surveys; however, using well-trained algorithms may produce accurate counts per image under a variety of conditions. Full article
(This article belongs to the Special Issue Drone-Based Wildlife Protection, Monitoring, and Conservation Management)
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13 pages, 2415 KiB  
Article
Drone with Mounted Thermal Infrared Cameras for Monitoring Terrestrial Mammals
by Hanne Lyngholm Larsen, Katrine Møller-Lassesen, Esther Magdalene Ellersgaard Enevoldsen, Sarah Bøgh Madsen, Maria Trier Obsen, Peter Povlsen, Dan Bruhn, Cino Pertoldi and Sussie Pagh
Drones 2023, 7(11), 680; https://0-doi-org.brum.beds.ac.uk/10.3390/drones7110680 - 18 Nov 2023
Cited by 1 | Viewed by 2864
Abstract
This study investigates the use of a drone equipped with a thermal camera for recognizing wild mammal species in open areas and to determine the sex and age of red deer (Cervus elaphus) and roe deer (Capreolus capreoulus) in [...] Read more.
This study investigates the use of a drone equipped with a thermal camera for recognizing wild mammal species in open areas and to determine the sex and age of red deer (Cervus elaphus) and roe deer (Capreolus capreoulus) in a 13 km2 moor in Denmark. Two separate surveys were conducted: (1) To achieve drone images for the identification of mammals, the drone was tested around a bait place with a live wildlife camera that was often visited by European badger (Meles meles), stone marten (Martes foina), European hare (Lepus europaeus), roe deer and cattle (Bos taurus). The thermal images of wild animal species could be distinguished by their body measures when the drone filmed with the camera pointed perpendicular to the ground in an altitude range of 50–120 m. A PCA ordination showed nonoverlapping body characteristics and MANOVA showed that the combined body measures used were significantly distinctive F = 6.8, p < 0.001. The reactions and behavioral responses of the different species to the altitude and noise of the drone were also tested in this place. (2) On a 13 km2 moor, a drone was used for a population study of deer. Red deer and roe deer were counted and separated by body measures. Red deer individuals could, at the right altitude, be separated into adults and calves, and males and females. Body length was the most conclusive body measure, and therefore a reference measurement in the field is recommended. The frame thermal images were effective in species recognition and for use in population studies of deer, and are thought to be more time-efficient and less invasive than traditional methods. In autumn, the number of stags and the life stage of red deer, as well as the distribution of deer in different types of vegetation, could be determined. Full article
(This article belongs to the Special Issue Drone-Based Wildlife Protection, Monitoring, and Conservation Management)
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19 pages, 11534 KiB  
Article
A Novel Scouring Method to Monitor Nocturnal Mammals Using Uncrewed Aerial Vehicles and Thermal Cameras—A Comparison to Line Transect Spotlight Counts
by Peter Povlsen, Dan Bruhn, Cino Pertoldi and Sussie Pagh
Drones 2023, 7(11), 661; https://0-doi-org.brum.beds.ac.uk/10.3390/drones7110661 - 06 Nov 2023
Cited by 2 | Viewed by 1696
Abstract
Wildlife abundance surveys are important tools for making decisions regarding nature conservation and management. Cryptic and nocturnal mammals can be difficult to monitor, and methods to obtain more accurate data on density and population trends of these species are needed. We propose a [...] Read more.
Wildlife abundance surveys are important tools for making decisions regarding nature conservation and management. Cryptic and nocturnal mammals can be difficult to monitor, and methods to obtain more accurate data on density and population trends of these species are needed. We propose a novel monitoring method using an aerial drone with a laser rangefinder and high zoom capabilities for thermal imagery. By manually operating the drone, the survey area can be initially scanned in a radius of several kilometers, and when a point of interest is observed, animals could be identified from up to one kilometer away by zooming in while the drone maintains an altitude of 120 m. With the laser rangefinder, a precise coordinate of the detected animal could be recorded instantly. Over ten surveys, the scouring drone method recorded significantly more hares than traditional transect spotlight count surveys, conducted by trained volunteers scanning the same farmland area within the same timeframe (p = 0.002, Wilcoxon paired rank test). The difference between the drone method and the transect spotlight method was hare density-dependent (R = 0.45, p = 0.19, Pearson’s product–moment correlation); the larger the density of hares, the larger the difference between the two methods to the benefit of the drone method. There was a linear relation between the records of deer by the drone and by spotlight (R = 0.69, p = 0.027), while no relation was found between the records of carnivores by drone and spotlight counts. This may be due to carnivores’ speed and vigilance or lack of data. Furthermore, the drone method could cover up to three times the area within the same timeframe as the transect spotlight counts. Full article
(This article belongs to the Special Issue Drone-Based Wildlife Protection, Monitoring, and Conservation Management)
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15 pages, 3112 KiB  
Article
Impacts of Drone Flight Altitude on Behaviors and Species Identification of Marsh Birds in Florida
by Jeremy P. Orange, Ronald R. Bielefeld, William A. Cox and Andrea L. Sylvia
Drones 2023, 7(9), 584; https://0-doi-org.brum.beds.ac.uk/10.3390/drones7090584 - 16 Sep 2023
Cited by 1 | Viewed by 1404
Abstract
Unmanned aerial vehicles (hereafter drones) are rapidly replacing manned aircraft as the preferred tool used for aerial wildlife surveys, but questions remain about which survey protocols are most effective and least impactful on wildlife behaviors. We evaluated the effects of drone overflights on [...] Read more.
Unmanned aerial vehicles (hereafter drones) are rapidly replacing manned aircraft as the preferred tool used for aerial wildlife surveys, but questions remain about which survey protocols are most effective and least impactful on wildlife behaviors. We evaluated the effects of drone overflights on nontarget species to inform the development of a Florida mottled duck (MODU; Anas fulvigula fulvigula) survey. Our objectives were to (1) evaluate the effect of flight altitude on the behavior of marsh birds, (2) evaluate the effect of altitude on a surveyor’s ability to identify the species of detected birds, and (3) test protocols for upcoming MODU surveys. We flew 120 continuously moving transects at altitudes ranging from 12 to 91 m and modeled variables that influenced detection, species identification, and behavior of nontarget species. Few marsh birds were disturbed during drone flights, but we were unable to confidently detect birds at the two highest altitudes, and we experienced difficulties identifying the species of birds detected in video collected at 30 m. Our findings indicate that MODUs could be surveyed at altitudes as low as 12–30 m with minimal impact to adjacent marsh birds and that larger-bodied nontarget marsh species can be identified from videos collected during MODU drone surveys. Full article
(This article belongs to the Special Issue Drone-Based Wildlife Protection, Monitoring, and Conservation Management)
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11 pages, 48168 KiB  
Communication
Identifying Important Bird and Biodiversity Areas in Antarctica Using RPAS Surveys—A Case Study of Cape Melville, King George Island, Antarctica
by Katarzyna Fudala and Robert Józef Bialik
Drones 2023, 7(8), 538; https://0-doi-org.brum.beds.ac.uk/10.3390/drones7080538 - 20 Aug 2023
Cited by 1 | Viewed by 1048
Abstract
A remotely piloted aircraft system (RPAS) survey of an area containing the eastern extremity of King George Island, including Cape Melville and an extensive part of Destruction Bay, as well as small offshore islands, was undertaken in December 2022. Using RPAS, an inventory [...] Read more.
A remotely piloted aircraft system (RPAS) survey of an area containing the eastern extremity of King George Island, including Cape Melville and an extensive part of Destruction Bay, as well as small offshore islands, was undertaken in December 2022. Using RPAS, an inventory of the Destruction Bay area was performed. Chinstrap penguin and Antarctic shag nests were found on Cape Melville and on Trowbridge Island, Middle Island, and an unnamed area located between the Ørnen Rocks formation and Trowbridge Island. During the survey, 507 Antarctic shag nests and over 9000 chinstrap penguin nests were mapped in the investigated area; 458 Antarctic shag nests and 4960 ± 19 chinstrap penguin nests aggregated together on an 8.61 ha land section of Cape Melville were identified. The quantity of Antarctic shag nests found allows for the classification of the area of Cape Melville as an IBA. Among the 175 currently known colonies of Antarctic shags in Antarctica, this is the fifth largest. In this paper, we present the results of the survey, including orthophotos with mapped nest locations. We propose the following recommendations to policy makers and the scientific community: (1) the area of Cape Melville should be classified as an Antarctic Important Bird and Biodiversity Area; (2) based on the RPAS flight, a new boundary of the Cape Melville IBA is proposed; (3) the threshold value (based on >1% of species) to establish an IBA for Antarctic shags should be changed to 122 to reflect the increased estimate of the global population of Antarctic shags; and (4) an inventory of all areas, including previous IBAs that can be qualified as “major colonies of breeding native birds”, should be recommended at the Antarctic Treaty Consultative Meeting (ATCM). In logistically inaccessible bird breeding sites, such as the one presented here, RPASs should be used to carry out regular monitoring of Antarctic Important Bird and Biodiversity Areas. Full article
(This article belongs to the Special Issue Drone-Based Wildlife Protection, Monitoring, and Conservation Management)
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13 pages, 2769 KiB  
Article
Automatic Recognition of Black-Necked Swan (Cygnus melancoryphus) from Drone Imagery
by Marina Jiménez-Torres, Carmen P. Silva, Carlos Riquelme, Sergio A. Estay and Mauricio Soto-Gamboa
Drones 2023, 7(2), 71; https://0-doi-org.brum.beds.ac.uk/10.3390/drones7020071 - 18 Jan 2023
Cited by 3 | Viewed by 1672
Abstract
Ecological monitoring programs are fundamental to following natural-system populational trends. Drones are a new key to animal monitoring, presenting different benefits but two basic re-strictions First, the increase of information requires a high capacity of storage and, second, time invested in data analysis. [...] Read more.
Ecological monitoring programs are fundamental to following natural-system populational trends. Drones are a new key to animal monitoring, presenting different benefits but two basic re-strictions First, the increase of information requires a high capacity of storage and, second, time invested in data analysis. We present a protocol to develop an automatic object recognizer to minimize analysis time and optimize data storage. We conducted this study at the Cruces River, Valdivia, Chile, using a Phantom 3 Advanced drone with an HD-standard camera. We used a Black-necked swan (Cygnus melancoryphus) as a model because it is abundant and has a contrasting color compared to the environment, making it easy detection. The drone flew 100 m from water surface (correcting AGL in relation to pilot landing altitude) obtaining georeferenced images with 75% overlap and developing approximately 0.69 km2 of orthomosaics images. We estimated the swans’ spectral signature to build the recognizer and adjusted nine criteria for object-oriented classification. We obtained 140 orthophotos classified into three brightness categories. We found that the Precision, Sensitivity, Specificity, and Accuracy indicator were higher than 0.93 and a calibration curve with R2= 0.991 for images without brightness. The recognizer prediction decreases with brightness but is corrected using ND8-16 filter lens. We discuss the importance of this recognizer to data analysis optimization and the advantage of using this recognition protocol for any object in ecological studies. Full article
(This article belongs to the Special Issue Drone-Based Wildlife Protection, Monitoring, and Conservation Management)
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13 pages, 13261 KiB  
Article
Using Drones with Thermal Imaging to Estimate Population Counts of European Hare (Lepus europaeus) in Denmark
by Peter Povlsen, Anne Cathrine Linder, Hanne Lyngholm Larsen, Petar Durdevic, Daniel Ortiz Arroyo, Dan Bruhn, Cino Pertoldi and Sussie Pagh
Drones 2023, 7(1), 5; https://0-doi-org.brum.beds.ac.uk/10.3390/drones7010005 - 21 Dec 2022
Cited by 5 | Viewed by 3676
Abstract
Drones equipped with thermal cameras have recently become readily available, broadening the possibilities for monitoring wildlife. The European hare (Lepus europaeus) is a nocturnal mammal that is closely monitored in Denmark due to populations declining since the mid-1900s. The limitations of [...] Read more.
Drones equipped with thermal cameras have recently become readily available, broadening the possibilities for monitoring wildlife. The European hare (Lepus europaeus) is a nocturnal mammal that is closely monitored in Denmark due to populations declining since the mid-1900s. The limitations of current population-assessment methods, such as, spotlight counts and hunting game statistics, could be overcome by relying on drone surveys with thermal imaging for population counts. The aim of this study was to investigate the use of a DJI Mavic 2 Enterprise Advanced drone with thermal imaging as a tool for monitoring the Danish hare population. Multiple test flights were conducted over agricultural areas in Denmark in spring 2022, testing various flight altitudes, camera settings, and recording methods. The test flights were used to suggest a method for identifying and counting hares. The applied use of this methodology was then evaluated through a case survey that had the aim of identifying and counting hares over an agricultural area of 242 ha. Hares could be detected with thermal imaging at flight altitudes up to 80 m, and it was possible to fly as low as 40 m without observing direct behaviorial changes. Thermal images taken at these altitudes also provided enough detail to differentiate between species, and animal body size proved to be a good species indicator. The case study supported the use of thermal imaging-based drone surveys to identify hares and conduct population counts, thus indicating the suggested methodology as a viable alternative to traditional counting methods. Full article
(This article belongs to the Special Issue Drone-Based Wildlife Protection, Monitoring, and Conservation Management)
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12 pages, 2483 KiB  
Article
The Use of Drones to Determine Rodent Location and Damage in Agricultural Crops
by Dor Keshet, Anna Brook, Dan Malkinson, Ido Izhaki and Motti Charter
Drones 2022, 6(12), 396; https://0-doi-org.brum.beds.ac.uk/10.3390/drones6120396 - 05 Dec 2022
Cited by 4 | Viewed by 2138
Abstract
Rodent pests cause extensive damage to agricultural crops worldwide. Farmers’ ability to monitor rodent activity and damage within crops is limited due to their inability to simultaneously survey vast agricultural areas for rodent activity, the inability to enter certain fields, and the difficulty [...] Read more.
Rodent pests cause extensive damage to agricultural crops worldwide. Farmers’ ability to monitor rodent activity and damage within crops is limited due to their inability to simultaneously survey vast agricultural areas for rodent activity, the inability to enter certain fields, and the difficulty of monitoring rodent numbers, as well as using traps due to trap shyness and high labor costs. Drones can potentially be used to monitor rodent numbers and damage because they can cover large areas quickly without damaging crops and carry sensors that provide high-resolution imagery. Here, we investigated whether rodent activity (Levant voles Microtus guentheri and house mice Mus musculus) is related to vegetation health and biomass in Alfalfa (Medicago sativa) fields. We used a drone to photograph one hundred and twenty 10 × 10 m plots in nine fields and calculate the plots’ normalized difference vegetation index (NDVI) and biomass. On each plot, we also trapped rodents, counted rodent burrows, and evaluated the harvested dry crop yield. The number of burrows was positively related to the number of Levant voles trapped (F1,110 = 12.08, p < 0.01) and negatively related to the number of house mice trapped (F1,110 = 5.23, p < 0.05). Biomass extracted from drone images was positively related to the yield harvested by hand (F1,83 = 3.81, p < 0.05). Farmers, therefore, can use burrow counting in place of trapping Levant voles, and biomass estimates from drones can be used in place of manual yield calculations. NDVI (F1,95 = 73.14, p < 0.001) and biomass (F1,95 = 79.58, p < 0.001) were negatively related to the number of Levant voles trapped, and the number of burrows were not related to the number of house mice trapped. We demonstrate that drones can be used to assist farmers in determining the Levant vole presence and damage within crop fields to control rodents using precision agriculture methods, such as adding rodenticides in specific areas, thus increasing efficiency and decreasing the amount of pesticides used. Full article
(This article belongs to the Special Issue Drone-Based Wildlife Protection, Monitoring, and Conservation Management)
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