Developing software, an R package, and workshop for robust and standardized drone-based photogrammetry
Abstract
Drones have recently enhanced opportunities for wildlife biologists to non-invasively collect morphological measurements of individuals via photogrammetry to estimate health and quantify population-level consequences of stressors (environmental and anthropogenic). For example, photogrammetry is critical for obtaining morphological measurements of marine megafauna, such as cetaceans, which areoften found in remote locations and are too large to safely capture and handle. Many researchers around the world, including Officeof Naval Research (ONR) funding recipients have utilized this technology to help assess the effects of noise exposure on marine mammals. However, several different drones and protocols are currently used across the scientific community in these efforts with no consistent framework for quantifying and incorporating measurement uncertainty. This lack of standardization restricts comparability across datasets, thus hindering our ability to effectively monitor populations and understand the drivers of variation (e.g., pollution, climate change, injury, noise). We propose to establish a standardized protocol to be consistently applied to different UAS platforms and data to allow unified analysis of marine mammal populations and offer trainings in how to incorporate measurement error through consistent reusable tools. Specifically, our objectives are to develop 1) software and an R package to assist researchers in obtaining accurate photogrammetric measurements and incorporating uncertainty into analysis, 2) create online tutorials and materialsto guide researchers with their analysis, and 3) host a workshop to help train and promote these methods to a fast-growing field ofresearchers interested in measuring the morphology of cetacean populations using drone-based photogrammetry. Our team, consisting of wildlife biologists, ecologists, statisticians, engineers, and programmers, has developed several unprecedented methods and tools to help obtain accurate morphological measurements of cetaceans from drone-based imagery. This includes open-source photogrammetry and database management software, as well as statistical models and workflows to incorporate uncertainty associated with different drones directly into analysis. Our collective expertise in photogrammetry, uncertainty analysis, Bayesian statistical modeling, and R and Python programming places us in a unique position to centralize these tools into a user-friendly software package that will greatly increase the accessibility of these methods to researchers around the world, including recipients of ONR funding. For instance, multiple ONR funded projects, such as behavioral response studies (BRS) and physiological response to multiple stressors, rely on the morphology and body condition of individuals in their analyses. Our proposed tools will enable ONR funding recipients that employ drone-based photogrammetry to conduct analyses more quickly, efficiently, and consistently, withresults that are more comparable across studies and research labs. By drawing from our ecological applications of these methods, we will offer a workshop to help researchers apply these methods to better monitor cetacean populations worldwide. Our goal is to develop innovative methods to non-invasively monitor wild cetacean populations and provide accessible tools and protocols to inspire, engage, and train researchers around the world.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- May 15, 2023
- Source ID
- N000142312422
Entities
People
- Kevin Bierlich
Organizations
- Office of Naval Research
- Oregon State University
- United States Navy