Data processing and management are critical steps in any camera trapping study, given the large amounts of data camera traps produce. We have compiled several resources relevant to proper data management as well as software for efficient data processing.
Camera Trap Software and Data Management Resources
Data Management & Metadata
Proper data management is important to ensure minimal loss of data resolution and the highest efficiency possible. We suggest that practitioners use the Camera Trap Metadata Standard (CTMS) outlined by Forrester et al.'s 2016 paper. These metadata standards are currently in use by most of the largest names in large-scale camera trapping, such as eMammal, and the Wildlife Conservation Society.
The government of British Columbia has also produced their own standards for camera trap metadata: the RISC Wildlife Camera Metadata Protocol. Influenced by Forrester et al.'s paper, it adapts the CTMS for use within the British Columbia Wildlife Species Inventory data management system.
We also recommend checking out Scotson et al.'s 2017 review paper on data management, where the authors suggest nine themes to ensure that no data resolution is lost.
Scotson, L., L.R. Johnston, FIannarilli, O.R. Wearn, J. Mohd‐Azlan, J.M. Wong, C.E. Willard. 2017. Best practices and software for the management and sharing of camera trap data for small and large scales studies. Remote Sensing in Ecology and Conservation, 3: 158-172.
For tips and tricks on how to organize camera trap data, check out this WildCAM webinar co-hosted by the Columbia Mountains Institute for Applied Ecology. The webinar was led by Dr. Christopher Beirne (UBC WildCo Lab) and takes you through the process of getting a memory card out of a camera trap through to producing useful and simple data exploration in R.
Data platforms are web- and desktop-based tools often used for efficient and standardized data management, sharing, and analysis of remote camera data. A number of platforms exist and it is important that users choose the one best suited to their project needs. To help camera trap users make this decision, we have created a comparison of different camera data platforms. It provides an overview of various platforms and software used in remote camera research in western Canada. It also compares the offerings of platforms for remote camera data storage, processing, analysis, mapping, and more. As software and online tools are often subject to frequent updates and change, we recognize this as a document subject to change over time. Click here to review the comparison (last updated June 2020). We welcome feedback at any time.
The use of programs specifically designed for camera trap photos and their associated data is now recognized as the best method for data processing. There are quite a few programs available for practitioners now, but many of them have most of the same functionalities. The relatively few unique features that distinguish programs will help to determine what software to use, and what features are needed for specific studies will vary depending on their study designs.
The following resources review and compare software programs, helping practitioners to evaluate their respective features and decide which is best for their research goals.
Scotson, L., L.R. Johnston, F. Iannarilli, O.R. Wearn, J. Mohd‐Azlan, W.M. Wong, C.E. Willard, 2017. Best practices and software for the management and sharing of camera trap data for small and large scales studies. Remote Sensing in Ecology and Conservation. 3: 158-172.
Greenberg, S., Godin, T. and Whittington, J. 2019. User Interface Design Patterns for Wildlife-Related Camera Trap Image Analysis. Ecology and Evolution. 9: 13706-13730.
You can also click here to get more information on the software program, TimeLapse Image Analyser for Camera Traps (developed by lead author and WildCAM member Saul Greenberg). Timelapse reads and displays images and videos from any type of remote camera, automatically extracting information from all images such as dates, times and metadata of your choosing. For more information, please contact Saul Greenberg: email@example.com.
Wearn, O. R. and P. Glover-Kapfer. 2017. Camera-trapping for conservation: a guide to best-practices. WWF conservation technology series 1.1 181.
Young, S., J. Rode‐Margono and R. Amin. 2018. Software to facilitate and streamline camera trap data management: a review. Ecology and Evolution, 8: 9947-9957.
** NOTE: UBC’s Wildlife Coexistence Lab is currently developing a cloud-based program for camera data management that may be available to WildCAM members in the future. Contact firstname.lastname@example.org for more information. **
Image Recognition for Camera Trap Photos
Researchers are increasingly exploring the use of image recognition software as a way to more efficiently and accurately classify species and to differentiate empty camera trap photos from those with animals. An automated process for classifying images may be a big break for photo management, but there is a lot of important information that potential users should know. Saul Greenberg of the University of Calgary has produced a guide about the use of image recognition for processing camera trap photos. This guide gives an overview of how it works and also details the advantages and current limitations associated with image recognition.
Greenberg, S. 2020.Automated Image Recognition for Wildlife Camera Traps: Making it Work for You. Technical report, Prism University of Calgary’s Digital Repository http://hdl.handle.net/1880/112416,
University of Calgary, Calgary, Alberta, Canada. August 21
If you have any questions about this guide, please contact Saul at email@example.com
Some of the resources listed above may not be open access. If an article is not open access, we recommend contacting the corresponding author to request a copy or checking common repositories such as Research Gate for now.