Area-Wide Prediction of Vertebrate and Invertebrate Hole Density and Depth across a Climate Gradient in Chile Based on UAV and Machine Learning

Burrowing animals are important ecosystem engineers affecting soil properties, as their burrowing activity leads to the redistribution of nutrients and soil carbon sequestration. The magnitude of these effects depends on the spatial density and depth of such burrows, but a method to derive this type...

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Bibliografiska uppgifter

Huvudupphov:	Paulina Grigusova, Annegret Larsen, Sebastian Achilles, Alexander Klug, Robin Fischer, Diana Kraus, Kirstin Übernickel, Leandro Paulino, Patricio Pliscoff, Roland Brandl, Nina Farwig, Jörg Bendix
Materialtyp:	Artigo
Språk:	Inglês
Utgiven:	MDPI AG 2021-08-01
Serie:	Drones
Ämnen:	UAV machine learning burrowing animals climate gradient Chile vegetation patterns
Länkar:	https://www.mdpi.com/2504-446X/5/3/86
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