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Camera traps are an essential tool for wildlife monitoring and ecological research, especially for species identification, biodiversity assessment, activity pattern analysis, occupancy modeling, density/abundance estimation, and among other.
Processing and analyzing camera trap data in R often requires multiple steps, from cleaning raw data to statistical modeling and visualization. The ct R package addresses these challenges by providing a modern, tidyverse-friendly workflow. It enables users to efficiently process data, and estimate density or abundance with several (~6) documented methods. Additionally, it integrates seamlessly with ggplot2, allowing users to generate highly customizable visualizations.
The ct package provides a comprehensive suite of 60+
functions covering the complete camera trap data analysis workflow.
Population density estimation is supported through
Random Encounter Models, (REM), Camera Trap Distance Sampling (CTDS)
Time-To-Event (TTE), Space-To-Event (STE), Instantaneous Sampling
Estimator (ISE), and Random Encounter and Staying Time (REST/RAD-REST).
Data management capabilities include filtering
independent detections, timestamp correction, and interactive spatial
validation. Community ecology functions enable activity
pattern analysis, biodiversity index assessment, and occupancy modeling
input preparation. Quality control tools include
detecting temporal gaps, monitoring deployment status, and taxonomic
validation.
For a full overview of all available functions, please visit the ct website
You can install ct directly from GitHub:
# Install pak firstly if not installed
if (!requireNamespace("pak", quietly = TRUE)) {
install.packages("pak", dependencies = TRUE)
}
# Install ct from GitHub
pak::pkg_install("stangandaho/ct")Please note that this project is based on the Contributor Covenant v2.1. By participating in this project you agree to abide by its terms.
If you encounter a clear bug, please file an issue with a minimal reproducible example. For questions and other discussion, please use relevant section.
The development of the ct package is supported by the R Consortium Infrastructure Steering Committee (ISC) under grant 25-ISC-1-04. This funding enables the creation of comprehensive statistical tools for camera trap data analysis, including population density estimation methods, and standardized data integration workflows.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.