A Text-Messaging Chatbot to Support Outdoor Recreation Monitoring Through Community Science

People who manage parks and other public lands need reliable information about how many people are visiting and how they are recreating. That kind of data helps them make better decisions about maintenance, safety, and conservation. The problem is that traditional ways of tracking recreation—like counting visitors or running surveys—are expensive and hard to use across large areas, especially in remote or undeveloped places.

In this study, researchers tested a new and simpler way to gather this information. They used a text-message chatbot that people could interact with on their phones to share basic information about their visit. This approach draws on ideas from community science and crowdsourcing and is designed to be low-cost and easy for both visitors and land managers.

Researchers tested this method for 18 months in a national forest in Washington State. The results were encouraging. The data collected through the chatbot closely matched what researchers found using traditional visitor counts and in-person surveys. At some locations, participation was surprisingly high—up to 12% of visiting groups took part—even in areas with limited or no cell service.

This study is the first to use a text-message chatbot to involve public land visitors directly in collecting recreation data. It shows that simple technology can open the door to new, community-based ways of monitoring outdoor recreation, while also helping visitors feel more connected to the care and stewardship of the places they enjoy.

Abstract

Public land managers depend on reliable and readily available data about outdoor recreation in parks and greenspaces. However, traditional recreation monitoring techniques including visitor surveying and counting cannot be implemented over large spatial and temporal scales, especially in remote and undeveloped settings where monitoring is costly. To fill these data gaps, and thereby inform decision-making, this study develops and tests the efficacy of a novel recreation monitoring technique that engages visitors in data collection using a chatbot and text-messages. Drawing on knowledge and methods from community science and crowdsourcing, we present a relatively low-cost and low-barrier approach to counting and characterizing recreational visits on public lands. In an 18-month pilot implementation on a national forest in Washington, USA, we found that crowdsourced data collected using the chatbot were consistent with results of controlled counts and in-person surveys. Furthermore, some sites received relatively high participation rates, up to 12% of recreating parties, regardless of cellular connectivity at the site. This study, which is the first to engage public land users in community science using a text-messaging chatbot for the purposes of studying outdoor recreation, demonstrates the potential for technology to support new community science approaches that involve visitors in land stewardship and the development of recreation monitoring systems.