This camera trap pilot 1 was primarily focused on testing camera deployment, data accumulation and data transmission (4G coverage) in a remote dune location of the Netherlands. Three Snyper Commander cameras were deployed from August 13th 2021 to August 2023 (approx. 747 days). The three cameras were placed within exclosures (locations Zilkerpad, van Limburgstirum Vallei and Wolfsveld in the Amsterdam Water Supply Dunes), at 30 cm above the ground. All images from 14th of August 2021 until 31st of December 2022 were annotated, with a total of 30,464 images over 505 days from the three cameras. A detailed description of the dataset can be found in a data paper published in the journal Data in Brief (Evans et al. 2024, https://doi.org/10.1016/j.dib.2024.110544).
Data have been standardized to Darwin Core using the camtrapdp R package and only include observations (and associated media) of animals. Excluded are records that document blank or unclassified media, vehicles and observations of humans.
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Animals are unmarked and camera traps are triggered with activity detection.","relatedProjects":[],"abstract":"Three pilot studies were conducted to test the autonomous deployment of wireless 4G wildlife cameras with solar panels and automated data transmission in the coastal dunes of the Amsterdam Water Supply Dunes, The Netherlands. Monitoring and management of grazing mammals such as the European rabbit (Oryctolagus cuniculus) and the European fallow deer (Dama dama) is of key interest in this nature reserve, as they slow down the rate of natural succession and alter plant species composition and vegetation structure through grazing and digging. These grazers as well as predators such as the red fox (Vulpes vulpes) have typically been monitored using traditional survey methods such as transect and areal counts, but only once or twice a year. The study was aimed to test the feasibility and methodology of running long-term autonomous monitoring networks with wildlife cameras. This involved the testing of power usage, data transmission, and data accumulation, and the robustness of cameras to herbivore damage. Furthermore, the pilots specifically tested how the detection of focal species (rabbits, deer, foxes) differs with deployment heights, camera lens types and the placement in different habitats. The pilot also provides labelled images for the development of deep learning algorithms to automatically identify species.\r\n\r\nWork was carried out as part of the development of the monitoring demonstration sites of a large-scale research infrastructure project ARISE."},"countryCoverage":[],"collections":[],"dataDescriptions":[],"pubDate":"2024-07-04T00:00:00.000+00:00","maintenanceUpdateFrequency":"UNKNOWN","maintenanceDescription":"","license":"http://creativecommons.org/licenses/by/4.0/legalcode","dwca":{"coreType":"http://rs.tdwg.org/dwc/terms/Occurrence","extensions":["http://rs.tdwg.org/ac/terms/Multimedia"],"modified":"2026-03-02T21:50:45.466+00:00"},"approximateCounts":{"occurrenceCount":2148}}