Collection of urban forestry data through the integration of satellite imagery and gamified satellite directed crowdsourcing

This project demonstrates a service for the improved collection of urban forestry data through the integration of satellite imagery and satellite directed crowdsourcing. The growing awareness of urban trees as a resource that should be managed and maintained has led to increasing efforts to monitor them. Critical to this is the availability of adequate inventory data. Our services provide a platform for the creation and continuous improvement of datasets as well as driving public participation in the effort. The inclusion and support of local communities is significant as public engagement is recognised as being of key importance in the success of effective urban tree management programmes. Previous efforts to automate the collection of information on urban tree stock have focused only on the use of canopy models applied to Earth observation imagery. In order to improve on this, we combine active learning algorithms with automated tree identification models in order to direct crowdsource users to the areas where data is uncertain. Datasets can be analysed through a dedicated hosting and analytics platform that supports open data knowledge sharing. By combining customer goals with a use case that benefits crowd users, we can improve engagement levels and sustain crowdsourcing efforts.