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Deriving observation distances for camera trap distance sampling

Camera trap distance sampling (CTDS)o is a recently developed survey method to estimate animal abundance from camera trap data for unmarked populations. It requires the estimation of camera-animal observation distances, which previously was done by comparing animal positions to reference labels at predefined intervals. Here, we test a photogrammetry approach to derive camera-animal observation distances. We applied both, the reference label and photogrammetry approaches to five ungulate species varying widely in body size (Giraffa camelopardalis, Equus grevyi, Oryx dammah, Kobus

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Automated camera trap species recognition made easy: Using entry-level hardware and few training data

Computer vision methods used to analyse camera trap photos are usually computationally expensive, require large training datasets and typically focus on only one species per photograph or rely on static backgrounds between sequential images. In contrast, our proposed method requires only an entry-level computer and relatively few training data while handling multi-species photos with changing backgrounds. It is able to distinguish between four large mammal species common to the Iona–Skeleton Coast TFCA, namely giraffe, impala, oryx and zebra. Trained on

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Automated species identification for camera trapping in the Iona Skeleton Coast Trans-Frontier Conservation Area

The Iona Skeleton Coast Trans-Frontier Conservation Area (TFCA), straddling the border between Angola and Namibia, has suffered through decades of civil war and poaching. While this history has been detrimental to the community of large mammals in the TFCA, data collected on the mammal populations are insufficient to enable effective management. Survey methods such as aerial counts and community-based monitoring have various shortcomings. Therefore camera trapping, which has become important in surveying wildlife worldwide, could become an essential monitoring tool

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