Data from: Snapshot Serengeti, high-frequency annotated camera trap images of 40 mammalian species in an African savanna
Domaine:
environment and energygeospatialType de record:
dataset
Créateur:
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Camera traps can be used to address large-scale questions in community ecology by providing systematic data on an array of wide-ranging species. We deployed 225 camera traps across 1,125 km2 in Serengeti National Park, Tanzania, to evaluate spatial and temporal inter-species dynamics. The cameras have operated continuously since 2010 and had accumulated 99,241 camera-trap days and produced 1.2 million sets of pictures by 2013. Members of the general public classified the images via the citizen-science website www.snapshotserengeti.org. Multiple users viewed each image and recorded the species, number of individuals, associated behaviours, and presence of young. Over 28,000 registered users contributed 10.8 million classifications. We applied a simple algorithm to aggregate these individual classifications into a final 'consensus' dataset, yielding a final classification for each image and a measure of agreement among individual answers. The consensus classifications and raw imagery provide an unparalleled opportunity to investigate multi-species dynamics in an intact ecosystem and a valuable resource for machine-learning and computer-vision research.
Gold Standard Data
Expert classifications for 4,149 image sets. Unlike Snapshot Serengeti volunteers, experts were allowed to indicate if a capture event was impossible to identify. Fields are as follows: CaptureEventID: Same indicator as in the raw and reduced classification data; NumSpecies: The number of species in this capture event; Species: One of the 48 possibilities or "impossible"; Count: Number of individuals, estimated as 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11-50 or 51+.
gold_standard_data.csv
Operation Dates
The dates that each camera was active and functioning properly, extracted from the image EXIF data as the first and last dates of valid photographs on a given SD card. Valid photographs are defined as those taken while the camera was secured on the tree pointing outwards (in contrast to photos taken after a camera was torn down and facing the ground).
search_effort.csv
Consensus classifications and metadata
We applied the plurality algorithm (described in the manuscript) to the raw classification data to produce a single classification per capture event, accompanied by measures of uncertainty and difficulty. Each species classified in a single capture event receives its own record and species-specific measures of uncertainty. Metadata (data/time & location) are included to facilitate ecological analyses. This dataset excludes all images retired as "blank."
consensus_data.csv
Images
URL information for retrieving each image; 1 record per image. All images in this data descriptor can be accessed at
snapshotserengeti.s3.msi.um… by appending the URL_Info field. For example, appending the value 'S1/B04/B04_R1/S1_B04_R1_PICT0012.JPG' yields the full URL:
snapshotserengeti.s3.msi.um…. Pasting this value into a browser will display the image in the browser.
all_images.csv
Raw classification data
Raw classification dataset; 1 record per unique user, capture event, and species. Includes images retired as "Blank" and "Blank_consensus."
raw_data_for_dryad.csv.zip