Predicting the plant species present at a given location is helpful for many biodiversity management and conservation scenarios. It allows for building high-resolution maps of species composition and related biodiversity indicators such as species diversity, endangered species, and invasive species. In scientific ecology, the problem is known as Species Distribution Modelling. Moreover, it could significantly improve the accuracy of species identification tools - such as [Pl@ntNet](https://plantnet.org/) - by reducing the list of candidate species observable at a given site.

More generally, it could facilitate biodiversity inventories by developing location-based recommendation services (e.g., on mobile phones), encouraging citizen scientist observers' involvement, and accelerating the annotation and validation of species observations to produce large, high-quality data sets.