Estimating Distribution of Hidden Objects with Drones: From Tennis Balls to Manatees

Unmanned aerial vehicles (UAV), or drones, have been used widely in military applications, but more recently civilian applications have emerged (e.g., wildlife population monitoring, traffic monitoring, law enforcement, oil and gas pipeline threat detection). UAV can have several advantages over manned aircraft for wildlife surveys, including reduced ecological footprint, increased safety, and the ability to collect high-resolution geo-referenced imagery that can document the presence of species without the use of a human observer. We illustrate how geo-referenced data collected with UAV technology in combination with recently developed statistical models can improve our ability to estimate the distribution of organisms. To demonstrate the efficacy of this methodology, we conducted an experiment in which tennis balls were used as surrogates of organisms to be surveyed. We used a UAV to collect images of an experimental field with a known number of tennis balls, each of which had a certain probability of being hidden. We then applied spatially explicit occupancy models to estimate the number of balls and created precise distribution maps. We conducted three consecutive surveys over the experimental field and estimated the total number of balls to be 328 (95%CI: 312, 348). The true number was 329 balls, but simple counts based on the UAV pictures would have led to a total maximum count of 284. The distribution of the balls in the field followed a simulated environmental gradient. We also were able to accurately estimate the relationship between the gradient and the distribution of balls. Our experiment demonstrates how this technology can be used to create precise distribution maps in which discrete regions of the study area are assigned a probability of presence of an object. Finally, we discuss the applicability and relevance of this experimental study to the case study of Florida manatee distribution at power plants

Estimates of conditional probability of occurrence as a function of temperature, and the number of neighboring sites that are occupied.

<p>4A: Temperature gradient (light blue: lower temperatures; dark red: higher temperatures). 4B: Model 2, conditional probability of occupancy modeled as a function of temperature (light blue corresponds to lower probabilities; dark red represents higher values). 4C: Model 3, conditional probability of occurrence (spatial model). True locations of the objects are denoted by circles: yellow circles correspond to the objects available for detection on the first UAV survey, black circles correspond to the location of the hidden objects (i.e., those not available for detection).</p

Posterior distributions of the number of occupied cells obtained from three models.

<p>Model 1 (blue curve); Model 2 (grey curve); Model 3 (black curve); true abundance of balls (solid line); maximum count of balls after three surveys of the UAV (long dashed line); count after the first survey of the UAV (short dashed line).</p

Unmanned aerial vehicle (UAV).

<p>Unmanned aerial vehicle (UAV).</p

Relationship between the temperature gradient and the probability of occurrence.

<p>Solid line corresponds to the relationship between the temperature gradient and the probability of occurrence obtained from Model 2; dashed lines correspond to the 95% CI. Circles represent the relationship between the temperature gradient and the probability of occurrence based on the true locations of the balls, triangles indicate the relationship obtained from the maximum count.</p

Groups of Florida manatees at a power plant in Florida during a cold event.

<p>Groups of Florida manatees at a power plant in Florida during a cold event.</p

Alligator taken from the Nova UAV in Lake Okeechobee, FL.

<p>The alligator was estimated to be 1.7 m in total length. Flight altitude was 85 m.</p

Experimental setup taken from the unmanned aerial system (UAV) at an altitude of 200 m.

<p>Red circles indicate the corners of the grid; inset shows a section of the photograph enlarged. Blue circle indicates a tennis ball available for detection.</p