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

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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Bibliographic Details
Main Authors: Paulina Grigusova, Annegret Larsen, Sebastian Achilles, Alexander Klug, Robin Fischer, Diana Kraus, Kirstin Übernickel, Leandro Paulino, Patricio Pliscoff, Roland Brandl, Nina Farwig, Jörg Bendix
Format: Article
Language:English
Published: MDPI AG 2021-08-01
Series:Drones
Subjects:
UAV
machine learning
burrowing animals
climate gradient
Chile
vegetation patterns
Online Access:https://www.mdpi.com/2504-446X/5/3/86

Internet

https://www.mdpi.com/2504-446X/5/3/86

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