UAV data and deep learning: efficient tools to map ant mounds and their ecological impact

Abstract High‐resolution unoccupied aerial vehicle (UAVs) data have alleviated the mismatch between the scale of ecological processes and the scale of remotely sensed data, while machine learning and deep learning methods allow new avenues for quantification in ecology. Ant nests play key roles in e...

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Bibliographic Details
Main Authors: Jérémy Monsimet, Sofie Sjögersten, Nathan J. Sanders, Micael Jonsson, Johan Olofsson, Matthias Siewert
Format: Article
Language:English
Published: Wiley 2025-02-01
Series:Remote Sensing in Ecology and Conservation
Subjects:
Online Access:https://doi.org/10.1002/rse2.400
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