Overview

Animal and aircraft collisions pose a significant risk for both animals and humans. Thousands of animal/aircraft collisions occur annually that costs aviation millions of dollars. Comprehensive airport wildlife monitoring and hazard mitigation relies heavily on having accurate information regarding diverse wildlife species habitats and land coverage, including both natural features and human structures. Although airport biologist and personnel attempt to mitigate these risks by deterring certain species from airports by habitat modification (fencing, translocation, auditory and visual deterrents, and population control), identifying areas used by wildlife and prioritizing management actions can be difficult. Wildlife monitoring is routinely conducted by many airports; however, frequent monitoring is sometimes unattainable due to the amount of area needing covered, time constraints, and lack of funding. Small Unmanned Aircraft Systems (sUAS) have recently emerged as a potential solution for safely conducting accurate airport animal surveys among multiple human observers. The goal of this project is to standardized methodology and develop best practices (flying drones, capturing images, and identifying animals without disturbance) for using sUAS in wildlife monitoring at airports.

The primary objectives of this project include:

1. Calibrate sUAS flight altitude, image overlay preferences, and selected sensors relative to representative wildlife and domestic mammal species to standardize image collection among surveyed land coverages representing those found within and near airport environments.


2. Conduct controlled field experiments designed to assess bias in estimating numbers (via imagery from sUAS) of available mammal species and broad species groups common to airport environments.


3. Develop imagery collection protocols according to focal species or species groups of birds and mammals, recommended equipment, and survey conditions for airport personnel to assist with building a test image repository for developing automated image processing.


4. Develop recommendation for image analysis tools, a deep neural network or similar pattern classification-based system for automatic target recognition/abundance estimation, which can eventually serve as one component of a web application tool for airport personnel or airport contractors interested in using UAS for wildlife monitoring.


5. Make recommendations regarding sUAS-based survey design for mammal surveys on airport properties.

Project Collaborators

USDA National Wildlife Research Center - The National Wildlife Research Center (NWRC) is the research unit of the USDA-APHIS Wildlife Services program. Scientists and support staff are dedicated to finding solutions to challenging wildlife damage management problems related to agriculture, natural resources, property, and human health and safety. Human-wildlife conflicts, wildlife damage, nuisance and pest animals, wildlife disease, invasive species, overabundant wildlife, and overall ecosystem health are just some of the topics studied by researchers at the National Wildlife Research Center.

Funding

This work is supported by the U.S. Department of Agriculture Animal and Plant Health Inspection Service (USDA-APHIS) and Federal Aviation Administration (FAA).

Period of Performance

August 1, 2020 - July 30, 2023