This is a fully automated urban tree data collector. It delivers an inventory of every tree located near or into public property (municipalities and cities). 

The main idea is to collect as much data as possible remotely from any data sources available and accessible. We use artificial intelligence to classify images (data). 

This technology also fits perfectly in what is widely known as the Smart City ecosystem. We provide a key tool to collect, update and deliver a better and cheaper database for managing and maintaining trees. 

The project itself starts from the base that there is no efficient way of creating a self-updating tree inventory for a specific area. The idea that started this comes from the expensive prices that some companies charge to manually take care of mapping and cataloging every single tree that, for example, a municipality owns.   

We as a GIS company propose that we can take satellite imagery and AI based computing to easily and in an expedited manner create an interactive map with screen annotations and identifiers for every tree available from a satellite image, the algorithm identifies the exact coordinates (latitude and longitude) of the tree and identify the species via an API call that is made to a plant identifier which returns a data base containing species, common name and scientific name. We then proceed to add it to