Identification and mapping of trees through a Geo Collaborative Inventory (GCI) platform is an important task for research in botany, citizen sciences and education. The quantity and veracity of the recorded data rely mainly on the motivation and engagement of each participant. However, for a non botanist, tree mapping can be perceived as an unstructured and tedious task that requires advanced skills. In addition, existing GCI applications deliver poor or nonexistent feedbacks regarding identification and mapping skills as well as progression in these skills. Structuring GCI sessions and enhancing them with game mechanics and clear objectives may have a positive effect on the inventory quality. Inventory situations being highly context dependant, a descriptive model of the GCI task is required to create adapted activity scenarios usable in various situations. This paper presents Albiziapp: a web collaborative and mobile tool, based on OpenSteetMap, that operationalizes any gamified scenario, consistent with a descriptive model built from a structural analysis of the GCI task.