Course: Classifying Camera Trap Footage

Learn to review, identify and classify footage, manage data, and share camera trap findings through MammalWeb.

Camera trapping is a non-invasive way to study wildlife, using motion- and heat-sensitive cameras to automatically record animals in their natural environments. It enables the study of species that are often hard to observe directly, offering insights into their behaviour, distribution, and ecology with limited human disturbance.

Collecting camera trap footage is just the beginning. The real insight comes from reviewing and analysing what’s been captured. Effective classification and data management are essential for identifying species accurately, recognising patterns, and contributing useful information to wildlife monitoring projects.

This session will take you through the process of classifying footage, managing data efficiently, and sharing your findings to support conservation and research efforts.

In this webinar, we’ll cover the following topics:

• Reviewing and Sorting Footage– Best practices for organising files and identifying key clips or images.
• Species Identification Tips– How to recognise common UK mammals and avoid misidentification pitfalls.
• Using MammalWeb for Classification– Step-by-step guidance on uploading and classifying footage within the platform.
• Processing and Analysing Data– Managing metadata, summarising results, and using data for research or community engagement.
• Sharing and Learning from Results– How to contribute to collective datasets, compare findings, and improve future deployments.

By the end of this webinar, we hope you'll be confident in processing your camera trap footage from start to finish: turning your images and videos into valuable wildlife insights.

The 90-minute event will consist of a 1-hour presentation followed by a Q&A with the tutor using questions provided by the live audience.

The presentations will be recorded and shared with those who booked alongside Q&A transcripts and relevant links following the event via a password-protected website.