Overview
Camera traps are an essential tool for wildlife monitoring and ecological research. They generate vast amounts of data that require careful processing, cleaning, and analysis to extract meaningful insights. Researchers use camera trap data for tasks such as species identification, biodiversity assessment, activity pattern analysis, occupancy modeling, 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 manipulate and transform datasets. Additionally, it integrates seamlessly with ggplot2, allowing users to generate highly customizable visualizations.
Key Features
The ct package provides a comprehensive suite of 60+ functions covering the complete camera trap data analysis workflow. Population density estimation is supported through Distance Sampling with automated model selection, Random Encounter Models, Time-To-Event, Space-To-Event, and Instantaneous Sampling. Data management capabilities include filtering independent detections, timestamp correction, and interactive spatial validation. Community ecology functions enable activity pattern analysis with, biodiversity assessment, and occupancy modeling input preparation. Quality control tools include detecting temporal gaps, monitoring deployment status, and taxonomic validation. The package also features Camera Trap Data Package integration, survey design tools, and more.
For a full overview of all available functions, please visit the ct website
Installation:
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")Code of conduct
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.
Getting help
If you encounter a clear bug, please file an issue with a minimal reproducible example. For questions and other discussion, please use relevant section.
Funding
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.