Visitors hiking in the Cascade Mountains, Washington, USA with white boxes indicating parts of
the image that the AI tool might identify as important to the classification. White text is an
example of model output, showing the probability that the image belongs to each class.

(Photo by Sama Winder, annotations added for demonstration).

By Samantha Winder, Heera Lee, Bumsuk Seo, Emilia Lia, and Spencer A. Wood.

Read the full paper here.

People share a lot of information on social media. This includes images of where they have different types of outdoor recreation experiences. Sorting through the millions of images that people share on social media is not feasible, however, so we created a computer vision tool called recCNNize that uses artificial intelligence to identify images of recreational activities such as hiking, biking, and birding. Our study introduces, tests, and applies this tool to more than 30,000 photographs taken in a national forest in Washington, USA. This research is unique in a few key ways.

First, our tool is entirely open source, and we are sharing it publicly so that others can use and improve it. Most prior research uses proprietary algorithms that are created by for-profit companies who frequently make undocumented changes to their tools and who is allowed to use them. Our paper discusses the strengths and weaknesses of our tool so others can make informed decisions about how to interpret our results or apply the tool themselves.

Second, our study quantifies biases in what is represented in people’s social media feeds by comparing our results to an on-site survey of visitors to the same destinations. We find that there are major differences between the activities identified in social media and the activities that visitors self-report on a survey. This highlights one of the pitfalls of research that relies on social media – we can not assume that social media and social media users are representative of everyone who recreates outdoors.

Finally, we use our new method to create maps of the number of distinct activities that visitors engage in and post about across two regions in Washington, USA. Using this map, we find that images on social media show a greater number of activities in places that have trails, are easily accessible from a road, and include access to rivers or lakes. Results like these help managers decide how to improve people’s recreational experiences. In Washington, for example, National Forests might consider building or improving trails that lead to areas with rivers and lakes in order to support a broader number of outdoor activities.