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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
1,
Humberto L. Perotto-Baldivieso
1,2,*,
Lori D. Massey
1,3,
J. Alfonso Ortega-S.
1,
Leonard A. Brennan
1 and
Fidel Hernández
1
1
Caesar Kleberg Wildlife Research Institute, Texas A&M University-Kingsville, Kingsville, TX 78363, USA
2
Department of Rangeland, Wildlife, and Fisheries Management, Texas A&M university, College Station, TX 77843, USA
3
Chaparral Wildlife Management Area, Texas Parks and Wildlife Department, Cotulla, TX 78014, USA
*
Author to whom correspondence should be addressed.
Drones 2024, 8(2), 64; https://doi.org/10.3390/drones8020064
Submission received: 2 January 2024 / Revised: 6 February 2024 / Accepted: 10 February 2024 / Published: 15 February 2024
(This article belongs to the Special Issue Drone-Based Wildlife Protection, Monitoring, and Conservation Management)
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Versions Notes

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 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.

1. Introduction

Wildlife surveys are systematic efforts to collect data about wildlife species’ presence, abundance, distribution, and behavior [1]. Wildlife surveys play a crucial role in informing conservation actions, managing ecosystems, and supporting sustainable management strategies [2,3,4]. Methods to estimate wildlife abundance have been studied extensively and depend on the biology of the species of interest [5,6,7]. Some of the most used approaches are point transects [8], camera traps [9], spotlight surveys [10], aerial wildlife surveys using helicopters [11], and fixed-wing airplanes [12,13,14,15,16].
Aerial wildlife surveys are used more often than on-the-ground field surveys to cover areas that are both extensive and often inaccessible [17,18,19]. The most common platforms that meet these needs for aerial wildlife surveys are fixed-wing airplanes and helicopters [11,19,20,21,22,23]. Fixed-wing airplanes are used to survey open, large extents of rangelands. Airplanes are commonly used to survey pronghorn (Antilocapra americana) in Wyoming and the Texas Panhandle [24,25]. Helicopters are often used when lower speeds and hovering are required and vegetation cover and topography become limiting factors [21,26,27]. Helicopters are useful when conducting surveys for bighorn sheep (Ovis canadensis) and mule deer (Odocoileus hemionus). Helicopters are also used for white-tailed deer (Odocoileus virginianus) and northern bobwhite quail (Colinus virginianus, hereafter ‘bobwhite’) surveys in arid and semi-arid rangelands with brush cover [11,17,20,23].
Helicopters are some of the most used survey platforms for bobwhites in South Texas [28]. Helicopter surveys are considered more reliable than morning covey calls [29]. Helicopter surveys used to estimate population density, which incorporate a distance sampling framework, consist of flying low (i.e., ~10 m above ground level) and slow (i.e., ~37 km·h−1) to flush coveys using the disturbance of the helicopter [28]. These aerial surveys rely on species flushing or running away as a means to detect them [20,28,29]. Data collected during these surveys include covey locations, the distance from the observer to covey locations, and individuals per covey, which are then used to estimate the bobwhite density for a certain area extent. Data collected during surveys aid managers in regulating harvest rates and reserving enough bobwhite recruits for the breeding season [30,31]. Unfortunately, while the pilots and wildlife biologists who perform these aerial surveys are trained and experienced, they are exposed to significant risks. The leading causes of death for wildlife workers and biologists in general are airplane and helicopter accidents [32,33]. Between 2000 and 2020, 66% of the 32 wildlife-job-related deaths were due to airplane and helicopter accidents. Therefore, there is a need to find alternatives to the current aerial wildlife survey methods than can provide similar or better estimates and lower the risk of fatal accidents.
As technology improves, drones with high-resolution thermal sensors are being widely accepted as research tools to aid in monitoring wildlife species and their habitats [34,35]. Drones and thermal sensors have been used to detect ungulates [36,37,38,39], primates [40,41,42], and birds [43,44]. Research in detecting large mammals with drones and thermal sensors is more common because of their body size and distinguishable body features compared to small-bodied species. The thermal reflectance of small-bodied species can cause them to easily be confused with surrounding substrates or be difficult to differentiate from other small-bodied individuals during flights [45]. There are studies that have reported the detection of small-bodied species using drones and thermal sensors, such as the northern lapwing (Vanellus vanellus) [46], brown hare (Lepus europaeus) [47], European nightjar (Caprimulgus europaeus) [45], and bobwhites [48]. To our knowledge, Martin et al. [48] was the only study to report bobwhite detections at civil twilight in the morning hours in Mississippi using drones with high-resolution thermal sensors.
There is very little research on how to conduct drone aerial surveys for small ground-dwelling birds in North America, specifically bobwhites. Martin et al. [48] reported detection rates of 60.5% in shrub cover, 56.2% in forest cover, and 40.3% in grass cover when flying a drone equipped with a thermal sensor at 30 m above ground level (AGL) at civil twilight in the morning hours. However, there is no research that has evaluated different flying altitudes or tested different color palettes to optimize bobwhite detection using thermal sensors. We chose to work with bobwhites because of the significant biological information available and their ecological, cultural, and economic importance throughout the United States [49,50,51,52,53,54]. Bobwhites are considered an umbrella species because of their association with other grassland and shrubland bird species of conservation concern [55]. They are also an indicator species for rangeland ecosystems [51,56]. Therefore, our goal was to assess the feasibility of detecting bobwhites using high-resolution thermal sensors. Our objectives were (1) to identify the altitudes at which bobwhites can be detected and (2) to compare the two most used color palettes to detect bobwhites. We achieved these objectives by performing flights at different altitudes over restrained tame bobwhites (i.e., within a wire cage) using a drone with a high-resolution thermal sensor and capturing still images and video recordings. We hypothesized that (1) we would have a greater number of bobwhite detections at altitudes lower than 30 m and (2) detection would be improved when using the black-hot color palette compared to the isotherm thermal color palette.

2. Materials and Methods

2.1. Study Site

The study was performed at the Duane Leach Research Aviary, Caesar Kleberg Wildlife Research Institute, at Texas A&M University–Kingsville (Kingsville, TX, USA). The climate in this area is categorized as humid subtropical, with hot, humid summers and mild to cool winters. Kingsville’s temperature ranges from 15.6 °C to 28.4 °C, with average annual precipitation of 736 mm [57]. The study was performed in February of 2023, after sunset, when bobwhite coveys are expected to form a roosting disk or huddle in a circular formation [53,58,59,60]. Weather conditions were measured with a handheld Skywatch meteos anemometer (JDC Instruments, Switzerland). Temperatures ranged between 5.5 °C and 11.3 °C and wind speeds ranged between 1.0 and 2.2 m·s−1 (Table 1).
We acquired 51 pen-raised bobwhites from a breeding facility in Quail Covey Run LLC (Brenham, TX, USA). The bobwhites were a mix of adult male and female birds of similar size. We transported the bobwhites to the Duane Leach Research Aviary in Kingsville, TX, where they were kept, maintained, and cared for in 3 separate aviary cages (1.2 × 1.8 × 2.4 m). From 6 February until 21 February, we provided the bobwhites with bird feed twice a day and ample water was always available. Bobwhites’ lengths range from 240 to 275 mm, and the average weight is 162 g in South Texas [58]. During the test and experimental trials, cages were placed along a gas pipeline right-of-way approximately 120 m from the aviary and drone launch site, which were within a buffer of approximately 4 m from the edges of other vegetation. Vegetation on the pipeline was a mix composed of low-stature mowed dormant Bermuda grass (Cynodon dactylon) of 5 cm maximum height and bare ground. This provided areas with no visual obstruction to evaluate the potential of drone–thermal cameras to detect bobwhites. Cages were free of aerial vertical obstruction from surrounding mesquite trees (Prosopis glandulosa) and brush. Once the flights were completed, we released the bobwhites into their exclosures inside the aviary until the next trial was performed.

2.2. Licenses and Permits

The management and handling of birds were approved by the Institutional Animal Care and Use Committee (IACUC) at Texas A&M University–Kingsville under protocol numbers 2022-10-31 and 2020-01-08A. Remote Pilot in Command (RPIC) had a valid remote pilot license for drones (Part 107) through the Federal Aviation Administration. We had an aerial wildlife and exotic animal management permit through the Texas Parks and Wildlife Department (permit number M-3725) to photograph and quantify wildlife using drones. To operate on Texas A&M University–Kingsville property, we used a Landowners Authorization (LOA) to manage wildlife or exotic animals by aircraft (LOA# M-3725-48888), through the Texas Parks and Wildlife Department.

2.3. Data Collection

We performed test flights and experimental trials to acquire thermal data from bobwhites in February 2023. We performed test flights on 9 February to assess the initial camera settings, optimal flight altitude, and recording method for the subsequent experimental trials. We also determined the behavior of bobwhites at each altitude by observing bobwhite movement to minimize stress. Experimental trials were performed with two flights on 11 February (first trial) and three flights on 18 February (second trial). We used a DJI Matrice 210 RTK rotary-wing quadcopter weighing 6.14 kg at takeoff, with an estimated flight time of 24 to 33 min. The drone unfolded, with the propellers and payload connected, measured 89 × 88 × 38 cm. We did not record the drone’s noise level; however, in other studies, the DJI M200 series drone noise level ranged from 51.4 to 59.3 dB during takeoff and landing [61]. We used a high-resolution FLIR XT2 thermal sensor (FLIR XT2, Teledyne FLIR LLC, Wilsonville, OR, USA). The thermal camera had a 19 mm sensor, able to capture 640 × 512 pixel images with a field of view of 32° × 26° at a frame rate of 30 Hz. The temperature scene range for the thermal sensor was from −25 °C to 135 °C.
We compared the black-hot and the customized isotherm thermal palettes to assess the visual detection of bobwhites (Figure 1).
The black-hot thermal palettes display a grayscale image where cooler objects are displayed in white and hotter objects are displayed in black [62]. Isotherms highlight a customized temperature range from yellow to red over a grayscale image; this temperature range is set by the user (i.e., drone pilot) before the flight initiates [63]. The isotherm interval temperature thresholds used for bobwhites were set to a specific upper, middle, and low range threshold depending on the bobwhites’ external temperature reading (Table 1 and Figure 1). Images were saved in a JPEG-Radiometric (JPG-R) format, and the pixel size from the thermal sensor images was calculated to determine the ground sampling distance and image footprint area for each altitude interval (Table 2). We used these two thermal color palettes because of their clear distinction of the target species’ contour and shape in the images.
Once the images were acquired, we used FLIR thermal studio (Teledyne FLIR LLC, Wilsonville, OR, USA) to convert the isotherm images to the black-hot thermal palette.

2.4. Flight Procedures

2.4.1. Test Flights: 9 February 2023

We distributed 51 bobwhites into cages with 12, 11, 8, 8, 6, and 6 bobwhites (Table 3), placed along the pipeline right-of-way.
We waited 20 min for the bobwhites to settle and recorded the weather variables (Table 1). We took image samples of bobwhites’ reflectance inside the cages at an altitude of 6 m to determine the shape and color of individual bobwhite quail (Figure 1). We then flew the drone at an altitude of 91 m above ground level (AGL) and hovered over the cages with bobwhites. We captured nadir (−90° camera angle) thermal reflectance images of the bobwhite cages by descending and capturing images in 6 m intervals from 91 to 18 m AGL (13 altitudes) and repeated the process by ascending from 18 to 91 m AGL (total of 26 images at 13 different altitudes). We returned the drone to the launch pad and waited 20 min before we repeated the same flight procedure one more time. Once we had completed the capture of the imagery, we recorded video in a line transect with nadir (−90°) and oblique (−45°) camera angles at set altitudes of 36, 30, 24, and 18 m AGL. The flying speed was 3m/s as we did not have any baseline from previous studies to select a different speed. We selected this speed based on the image quality and altitude at the time of the initial tests. For each flight, we observed the behavior of the bobwhites to assess whether the drones would cause disturbance to roosting coveys. Once we had compared the imagery and the video, we discarded the video due to motion blur even at 18 m AGL. Our initial results from the test flights showed that images ≥48 m AGL would not provide a sufficient resolution to count bobwhites. We decided to conduct experimental trials using imagery ranging altitudes between 18 and 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 for the test flights or experimental trials.

2.4.2. Experimental Trials: 11 and 18 February 2023

Bobwhites were distributed into cages with 14, 13, 12, and 12 bobwhites per cage (Table 2) and placed along the pipeline right-of-way. We waited 20 min for the bobwhites to settle and recorded the weather variables (Table 1). We launched the drone to an altitude of 42 m AGL and hovered over the cages with bobwhites. We then captured nadir thermal reflectance images of the bobwhites at different altitudes; we did this by descending and capturing images in 6 m intervals (5 altitudes) from 42 to 18 m AGL and repeated the process by ascending from 18 to 42 m AGL (total of 10 images at 5 different altitudes). Following the flight, we returned the drone to the launch pad, randomized and repositioned the cages in the pipeline right-of-way, and waited 20 min for the bobwhites to settle, to repeat the previous process of descending and ascending flight. We conducted two flights on 11 February (Trial 1) and three flights on 18 February (Trial 2). This resulted in 4 and 6 images per altitude for each date, respectively. In total, we had 50 images, with 10 images at each altitude of 18, 24, 30, 36, and 42 m.

2.5. Data Analysis

After downloading the imagery to the computer, the RPIC reviewed the images to confirm the identification of individual bobwhites. The process involved enlarging the view of the image beyond its original size on a 34″ curved monitor with WQHD 3440 × 1440 resolution. For each image captured, we identified and counted bobwhite individuals for each altitude and thermal color palette (Figure 2 and Figure 3).
We used a Chi-square goodness-of-fit test to assess differences in covey size counts at each altitude between the observed bobwhites and the actual bobwhites in the cages (α = 0.05) [64,65]. For each experimental trial and thermal color palette, we used a Kruskal–Wallis non-parametric test to determine whether there were differences between altitudes [66,67]. We used the Kruskal–Wallis test because the data did not meet the assumptions required by a parametric test [66,67]. We used the non-parametric multiple pairwise comparison approach using Dunn’s test to determine which altitudes differed from each other and used Dunn’s test with Bonferroni correction to adjust the p-value according to the number of multiple pairwise comparisons [68]. We then performed a Mann–Whitney U test to determine differences in bobwhite covey size counts between thermal color palettes; we used a Mann–Whitney U test because the data did not meet the assumptions required by a parametric test [69,70].

3. Results

We observed the highest counts of bobwhites with the black-hot thermal palette at 18 m AGL (92%; x ¯ = 47 bobwhites; SE = 0.41) and at 24 m AGL (81%; x ¯ = 41 bobwhites; SE = 0.89). Detections at 30 m AGL and higher altitudes were ≤55% (Figure 4) of known counts. Detections with the isotherm thermal color palette were below 64% for all altitudes (Figure 4).
There were no differences between the observed and expected counts of the black-hot thermal color palette images at an altitude of 18 m (χ2 = 3.27; p = 0.95) (Table 4).
There were differences between the number of counted and the total number of bobwhite individuals at altitudes ranging from 24 to 42 m for the black-hot thermal palette and for all altitudes with the isotherm thermal color palette (p < 0.05) (Table 4). For both the black-hot and isotherm thermal color palettes, the multiple pairwise comparison results showed that the detections were similar with altitudes within 6 m, but there were differences at altitudes ≥ 12 m (Figure 4).
The shape and color of bobwhites from the black-hot thermal color palette included light gray teardrop-shaped bodies, dark grey to black circular heads, and black “V-shaped” beaks (Figure 1A). For the isotherm thermal color palette, bobwhites had a yellow teardrop-shaped silhouette filled with a darker gray center (Figure 1B). The number of individual bobwhites detected between the black-hot and isotherm thermal color palettes was also different at all altitudes from 18 to 42 m (p < 0.05). For all altitudes, the black-hot thermal color palette was better at detecting individual bobwhites, detecting 58% more bobwhites on average than the isotherm thermal color palette.

4. Discussion

Flying drones with high-resolution thermal sensors provided reliable imagery to detect roosting bobwhite individuals in South Texas during the winter at approximately 90 min after sunset and with grass heights of 0 to 5 cm. Our results showed that we could count 92% and 81% of bobwhites using the black-hot thermal color palette at 18 and 24 m without causing disturbance to the bobwhites. Our findings contradict Rebolo-Ifran’s [71] concerns regarding disturbances to wildlife by drones, as we did not detect any disturbance to pen-raised bobwhites while conducting drone night flights during winter in South Texas. The inactivity of the bobwhites due to the drone’s presence may be attributed to the lack of predator awareness among the tame pen-raised bobwhites used in this study [72,73]. However, Reyna and Newman [74] found that pen-reared bobwhites flushed upon simulated raptor approaches. The limited movement of bobwhites at night may also be due to their low night-time visual capabilities [75]. Thus, drones may potentially provide an advantage by not requiring disturbance during surveys, compared to helicopter surveys, which consist of actively flushing bobwhites to record detections.
Our hypothesis was supported by the greater number of bobwhites counted at altitudes lower than 30 m. Our results showed that the observed counts of bobwhites from images with the black-hot thermal color palette at 18 m and 24 m had 92% and 81% detections, respectively. To our knowledge, this is the first published study that focuses on assessing individual detections rather than bobwhite covey detections using thermal cameras mounted on a drone in the Southern United States. Martin et al. [48] conducted a study to detect different covey sizes within three different vegetation covers using a similar drone and sensor in Mississippi. Their operations were conducted at 30 m AGL at civil twilight and they reported covey detection rates of 40.3%. The results of Martin et al. [48] and our study provide useful information on the development of night operations to assess covey and covey size detection in future studies. Thus far, our results are consistent with the height and pixel resolution to identify the target species recommended by Burke et al. [41].
The use of the black-thermal color palette improved the detection rates when using drones in South Texas. The isotherm thermal color palette provided less than 58% of individual detections on average at any altitude, whereas the detections of individual bobwhites were 92% at 18 m and 81% at 24 m. Therefore, our second hypothesis was supported by the greater number of individual bobwhite detections with the black-hot than the isotherm thermal color palette. Kays et al. [76] suggested the use of custom isotherm thresholds from FLIR thermal sensors (Teledyne FLIR LLC, Wilsonville, OR, USA) over the white-hot or black-hot thermal palettes to improve the ability to detect primates. Our study showed that this does not work for smaller individuals such as bobwhites. The isotherm method highlights the external temperature of the subject and any other surrounding object with similar temperatures [63]. Since bobwhites are relatively smaller, the isotherm palette combined individual bobwhites’ reflectance signatures together and produced unwanted reflectance from smaller surrounding objects, losing the ability to detect individual bobwhites.
Still imagery provided a better resolution than video in the detection of bobwhites. The video resolution on all line transect flights with nadir and oblique camera angles was too coarse to count individual bobwhites within a roosted covey; additionally, the video recording shutter speed was slow and it contained a larger amount of “motion blur”, making the detection of bobwhites low even at lower altitudes of 18 m. Burke et al. [41] suggested that an angled camera setup (oblique imagery) would work better for smaller-bodied animals. However, in our study, we obtained poor results when detecting bobwhite individuals with oblique imagery, which was consistent with suggestions from Havens and Sharp [77], stating that angles greater than 45° can cause signal attenuation and thermal scattering. Because bobwhites are social birds, they tend to form coveys during fall and winter and will huddle and roost in groups of 7 to 15 individuals from dusk to dawn to alleviate and survive the colder winter temperatures [53,58,59,60]. The huddling of bobwhites is a very distinguishable feature, where they gather in a circle, pointing their tails to the inside and heads outward; their bodies touch side to side, with their wings slightly raised, which seals the top to trap their body heat [58]. Bobwhites prefer to roost in bare ground or litter within herbaceous vegetation with low, sparse, open canopies [78]. Therefore, oblique angles at altitudes of 30 m or lower would result in herbaceous vegetation obstructing the thermal signatures of bobwhites [79]. The approaches used in this study to determine the optimal heights for the detection of bobwhites can be used for other species, such as ring-necked pheasants (Phasianus colchicus), scaled quail (Callipepla squamata), or Montezuma quail (Cyrtonyx montezumae).

5. Conclusions

Our study suggests that drones provide high-resolution thermal imagery to identify bobwhite individuals in South Texas rangelands during winter. Using the black-hot thermal color palette and flying at lower altitudes of 18 m improves the detection rates of smaller individuals, such as the bobwhites in this study. However, imagery provides good quality up to 24 m with this specific thermal sensor to count 81% of bobwhites. A higher altitude of 24 m compared to 18 m would provide a larger image footprint to cover more area and maximize the distance between the drone and subject of interest, to decrease the disturbance probability during flyover. The time and effort to survey large areas, the traveling speed, and the battery life of the drone are factors to consider for future research. We recommend that future studies consider open rangelands with different altitudes in herbaceous vegetation cover to observe their effects on detection. Conducting data collection in the early morning before dawn may also provide a greater contrast to avoid the surrounding substrate’s thermal noise and improve bobwhite detection. The approaches used in this study can be used to detect and estimate the abundance of other ground-dwelling birds, with minimal disturbance, where distinguishing roosting features are known.

Author Contributions

Conceptualization, J.S.A.-S. and H.L.P.-B.; methodology, J.S.A.-S., L.D.M. and H.L.P.-B.; software, J.S.A.-S., L.D.M. and H.L.P.-B.; validation, J.S.A.-S. and H.L.P.-B.; formal analysis, J.S.A.-S. and H.L.P.-B.; resources, H.L.P.-B., L.A.B. and J.A.O.-S.; data curation, J.S.A.-S.; writing—original draft preparation, J.S.A.-S. and H.L.P.-B.; writing—review and editing, H.L.P.-B., L.A.B., J.A.O.-S. and F.H.; supervision, H.L.P.-B.; funding acquisition, L.A.B., J.A.O.-S. and H.L.P.-B. All authors have read and agreed to the published version of the manuscript.

Funding

This research was supported by the Hildebrand Foundation, Ken Leonard Fund for Livestock Interactions Research, Harvey Weil Foundation, Comision Nacional de Ciencia y Tecnologia (CONACYT), Houston Safari Club, South Texas Quail Coalition Chapter, Hill Country Quail Coalition, and Mr. Rob Stacy from Houston, TX.

Data Availability Statement

Please contact the authors for data requests.

Acknowledgments

We wish to thank A. Foley and D.A. Woodard for the comments and suggestions during the internal review process and the 4 anonymous reviewers who helped to improve this manuscript. This is manuscript number 24–101 from the Caesar Kleberg Wildlife Research Institute at Texas A&M University–Kingsville.

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. Representation of the shape and color of bobwhites under different thermal color palettes: (A) is black-hot and (B) is isotherm color palette. Images were taken at an altitude of 6 m on 18 February 2023, at the Duane Leach aviary in Kingsville, TX, USA.
Figure 1. Representation of the shape and color of bobwhites under different thermal color palettes: (A) is black-hot and (B) is isotherm color palette. Images were taken at an altitude of 6 m on 18 February 2023, at the Duane Leach aviary in Kingsville, TX, USA.
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Figure 2. Representation of nadir thermal images with black-hot palette at different altitudes. (A) 18 m, (B) 24 m, (C) 30 m, and (D) 36 m. Images taken on 18 February 2023, at the Duane Leach aviary in Kingsville, TX, USA.
Figure 2. Representation of nadir thermal images with black-hot palette at different altitudes. (A) 18 m, (B) 24 m, (C) 30 m, and (D) 36 m. Images taken on 18 February 2023, at the Duane Leach aviary in Kingsville, TX, USA.
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Figure 3. Representation of nadir thermal images with isotherm threshold settings at different altitudes. (A) 18 m, (B) 24 m, (C) 30 m, and (D) 36 m. Images taken on 18 February 2023, at the Duane Leach aviary in Kingsville, TX, USA.
Figure 3. Representation of nadir thermal images with isotherm threshold settings at different altitudes. (A) 18 m, (B) 24 m, (C) 30 m, and (D) 36 m. Images taken on 18 February 2023, at the Duane Leach aviary in Kingsville, TX, USA.
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Figure 4. Average number of bobwhites counted per image at each altitude with different thermal color palettes and standard errors. Dunn’s multiple pairwise comparison for each thermal color palette between altitudes. Different letters indicate differences between altitudes (adjusted p < 0.05).
Figure 4. Average number of bobwhites counted per image at each altitude with different thermal color palettes and standard errors. Dunn’s multiple pairwise comparison for each thermal color palette between altitudes. Different letters indicate differences between altitudes (adjusted p < 0.05).
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Table 1. Weather conditions, flight start times, and isotherm thermal color palette settings. (Test) denotes the flights conducted to determine the flight and altitude settings for subsequent experimental flights on 6 February 2023. (1) and (2) denote the order of the experimental flights conducted to gather data on 11 and 18 February 2023, respectively. Temperature data of Kingsville were collected through [57], and the study site weather conditions were collected with a handheld Skywatch meteos anemometer (JDC Instruments, Switzerland).
Table 1. Weather conditions, flight start times, and isotherm thermal color palette settings. (Test) denotes the flights conducted to determine the flight and altitude settings for subsequent experimental flights on 6 February 2023. (1) and (2) denote the order of the experimental flights conducted to gather data on 11 and 18 February 2023, respectively. Temperature data of Kingsville were collected through [57], and the study site weather conditions were collected with a handheld Skywatch meteos anemometer (JDC Instruments, Switzerland).
Date (Trial)Temperature Kingsville, TX. NAS Weather StationStudy Site (°C)Wind Speed (m/s)Sunset (h)Start Time (h)Isotherm Interval Threshold (°C)
High (°C)Low (°C)UpperMiddleLower
(Test)24.43.95.5<2.218:1920:0026.220.515.1
(1)19.41.18.9<2.618:2119:4526.220.515.1
(2)20.02.811.3<1.018:2619:5031.725.520.0
Table 2. Estimated pixel size at 6 m altitude intervals acquired from the FLIR XT2 thermal sensor (640 × 512 p and 32° × 26° FOV).
Table 2. Estimated pixel size at 6 m altitude intervals acquired from the FLIR XT2 thermal sensor (640 × 512 p and 32° × 26° FOV).
Drone Altitude (m)Pixel Size (cm)Image Footprint (m2)# Images Required to Cover One Hectare
615.321012.0810
554.80822.2113
494.28653.9016
423.66479.6021
363.14352.1629
302.62244.9841
242.09156.7064
181.5788.35114
Table 3. Number of bobwhites introduced into each cage at each flight during test and experimental flights.
Table 3. Number of bobwhites introduced into each cage at each flight during test and experimental flights.
CageNumber of Bobwhites
Test FlightsExperimental Flights 1Experimental Flights 2
A121414
B111313
C81212
D81212
E6--
F6--
Table 4. Chi-square test results of observed and expected quail counts from black-hot and isotherm thermal color palette images at altitudes of 18 to 42 m during experimental flights 1 and 2.
Table 4. Chi-square test results of observed and expected quail counts from black-hot and isotherm thermal color palette images at altitudes of 18 to 42 m during experimental flights 1 and 2.
Drone Altitude (m)Black-HotIsotherm
Chi-Square (df = 9)p-ValueChi-Square (df = 9)p-Value
183.270.95268.10<0.001
2419.860.019145.65<0.001
30111.47<0.001272.35<0.001
36233.29<0.001415.14<0.001
42399.06<0.001510.00<0.001
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Avila-Sanchez, J.S.; Perotto-Baldivieso, H.L.; Massey, L.D.; Ortega-S., J.A.; Brennan, L.A.; Hernández, F. Evaluating the Use of a Thermal Sensor to Detect Small Ground-Nesting Birds in Semi-Arid Environments during Winter. Drones 2024, 8, 64. https://doi.org/10.3390/drones8020064

AMA Style

Avila-Sanchez JS, Perotto-Baldivieso HL, Massey LD, Ortega-S. JA, Brennan LA, Hernández F. Evaluating the Use of a Thermal Sensor to Detect Small Ground-Nesting Birds in Semi-Arid Environments during Winter. Drones. 2024; 8(2):64. https://doi.org/10.3390/drones8020064

Chicago/Turabian Style

Avila-Sanchez, J. Silverio, Humberto L. Perotto-Baldivieso, Lori D. Massey, J. Alfonso Ortega-S., Leonard A. Brennan, and Fidel Hernández. 2024. "Evaluating the Use of a Thermal Sensor to Detect Small Ground-Nesting Birds in Semi-Arid Environments during Winter" Drones 8, no. 2: 64. https://doi.org/10.3390/drones8020064

APA Style

Avila-Sanchez, J. S., Perotto-Baldivieso, H. L., Massey, L. D., Ortega-S., J. A., Brennan, L. A., & Hernández, F. (2024). Evaluating the Use of a Thermal Sensor to Detect Small Ground-Nesting Birds in Semi-Arid Environments during Winter. Drones, 8(2), 64. https://doi.org/10.3390/drones8020064

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