Using very‐high‐resolution satellite imagery and deep learning to detect and count African elephants in heterogeneous landscapes

Using very‐high‐resolution satellite imagery and deep learning to detect and count African elephants in heterogeneous landscapes

Abstract Satellites allow large‐scale surveys to be conducted in short time periods with repeat surveys possible at intervals of <24 h. Very‐high‐resolution satellite imagery has been successfully used to detect and count a number of wildlife species in open, homogeneous landscapes and seascapes...

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Bibliographic Details
Main Authors: Isla Duporge, Olga Isupova, Steven Reece, David W. Macdonald, Tiejun Wang
Format: Article
Language:English
Published: Wiley 2021-09-01
Series:Remote Sensing in Ecology and Conservation
Subjects:
Machine Learning
Convolutional Neural Network
Aerial Survey
Wildlife Census
Endangered Species
Conservation
Online Access:https://doi.org/10.1002/rse2.195

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