Aerial photography and machine learning for estimating extremely high flamingo numbers on the Makgadikgadi Pans, Botswana
Description
Sophie Yang, Roxane J. Francis, Mike Holding, Richard T. Kingsford, Aerial photography and machine learning for estimating extremely high flamingo numbers on the Makgadikgadi Pans, Botswana, Global Ecology and Conservation, 2024, e03011, ISSN 2351-9894, https://doi.org/10.1016/j.gecco.2024.e03011. (https://www.sciencedirect.com/science/article/pii/S2351989424002154) We developed a semi-supervised machine learning method for counting a large feeding concentration of flamingos (2 June 2019) in aerial photographs from northern Sua Pan of the Makgadikgadi Pans. We also analysed rainfall and flooding frequency and extent, using satellite imagery, estimating likely frequency of these flamingo concentrations. Our analysis successfully provided an estimate of 372,172 to 689,473 flamingos, with methods producing over 97% test accuracy. Uncertainty related primarily to data coverage and collection rather than methodology. Code from Google Earth Engine has been provided in a JavaScript file, along with an example collage. To use the code, please copy and paste into Google Earth Engine scripts and upload relevant images as assets to be analysed.
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Funding
Centre for Ecosystem Science, University of New South Wales
University of New South Wales
UGVC1056
Australian Research Council
LP180100159