The rise of crowdsourcing practices has revolutionized the way in which organizational tasks can be performed. One application of crowdsourcing that has been receiving growing attention over the past decade is using the crowd to collect environmental data that is needed to monitor, manage and predict environmental events. Most projects are still in their initial stages and since these projects often require high levels of citizen participation, there is a need to better understand the motivations for individuals to(dis)engage in these crowdsourcing projects, especially when long-term participation is required. Therefore, the aim of this thesis is to explore the motivations of individuals that participated in a crowdsourcing project for environmental data collection. Building on Self-Determination Theory, Social Exchange Theory and Social Identity theory, a case was studied of an organization that successfully motivated citizens from all over the world to use their drones to collect geographic climate data. In total, ten interviews were conducted with the drone-operators. The findings suggest that participants felt intrinsically motivated to engage because they wanted to do good, cared about climate change and were passionate about flying drones. Additionally, they experienced extrinsic motivations such as the possibility of gaining future job offers, recognition, and experience. Moreover, since participation was deemed relatively easy and straightforward, costs of participation were low and outweighed by the benefits. Finally, feeling part of a wider community made the participants more motivated to engage. Using crowdsourcing to collect environmental data on a wider spatiotemporal scale can help guide policy-making that mitigates or manages the impacts of climate change. Future projects would benefit from more and diversified research that support the design of long-term participation schemes, as the success of the projects depends on the level of citizen engagement.