Burrow-Nesting Seabird Survey Using UAV-Mounted Thermal Sensor and Count Automation

Author:

Virtue Jacob1ORCID,Turner Darren1ORCID,Williams Guy2,Zeliadt Stephanie3,Walshaw Henry4,Lucieer Arko1ORCID

Affiliation:

1. School of Geography, Planning, and Spatial Sciences, University of Tasmania, Hobart, TAS 7001, Australia

2. First Institute of Oceanography, Ministry of Natural Resources, Qingdao 266016, China

3. Commonwealth Scientific and Industrial Research Organization, Hobart, TAS 7004, Australia

4. FloodMapp, Brisbane, QLD 4006, Australia

Abstract

Seabird surveys are used to monitor population demography and distribution and help us understand anthropogenic pressures on seabird species. Burrow-nesting seabirds are difficult to survey. Current ground survey methods are invasive, time-consuming and detrimental to colony health. Data derived from short transects used in ground surveys are extrapolated to derive whole-colony population estimates, which introduces sampling bias due to factors including uneven burrow distribution and varying terrain. We investigate a new survey technique for nocturnally active burrow-nesting seabirds using unoccupied aerial vehicles (UAVs) and thermal sensor technology. We surveyed a three-hectare short-tailed shearwater (Ardenna tenuirostris) colony in Tasmania, Australia. Occupied burrows with resident chicks produced pronounced thermal signatures. This survey method captured a thermal response of every occupied burrow in the colony. Count automation techniques were developed to detect occupied burrows. To validate the results, we compared automated and manual counts of thermal imagery. Automated counts of occupied burrows were 9.3% higher and took approximately 5% of the time needed for manual counts. Using both manual and automated counts, we estimated that there were 5249–5787 chicks for the 2021/2022 breeding season. We provide evidence that high-resolution UAV thermal remote sensing and count automation can improve population estimates of burrow-nesting seabirds.

Funder

UTAS Research Training Program

Australian Research Council

Winifred Violet Scott Trust

Publisher

MDPI AG

Subject

Artificial Intelligence,Computer Science Applications,Aerospace Engineering,Information Systems,Control and Systems Engineering

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