Geotechnologies applied to remote coffee mapping and digital currency investment simulations | Geotechnology applied to the remote mapping of coffee and digital currency investment simulations

Portuguese. Coffee production is an activity of great economic and social importance in Brazil. This agribusiness segment stands out in the economy of small cities in southern Minas Gerais, as it involves family farming and the permanence of the rural population in the countryside. This study aimed to contribute and adapt geotechnology-based methods for the remote mapping of coffee and the strengthening of the permanence of this population, providing an online platform to simulate coffee trading. The municipality of Inconfidentes/MG was the study area. Orbital images of the Sentinel-2A satellite were used in the development of the study. Images were classified in a supervised way with the random forest classifier in Google Earth Engine (GEE) and later used as a data source in the online platform developed in the Application Programming Interface (API) Leaflet to simulate coffee trading involving the cryptocurrency Coffee Coin. Results allowed the identification and mapping of coffee growing areas by remote sensing and, also, to demonstrate that the online platform can help in the planning of new investments in coffee production, in addition to presenting an overview of the economic importance of coffee to the municipality.

English. Coffee growing, an activity of great economic and social importance for the country, is a segment of agrobusiness that is prominent in the economy of small towns in the south of Minas Gerais, as it involves family farming and the permanence of the population in the countryside. This work corroborates the development and adaptation of methodologies based on geotechnologies that can significantly contribute to the remote mapping of coffee farming and strengthening the permanence of the rural population by providing an online platform to simulate the negotiation of their coffee production. The municipality of Inconfidentes was selected as the study area. In the development of the work, orbital images from the Sentinel-2A satellite were used. The images were classified in a supervised way with the Random Forest classifier on the Google Earth Engine (GEE) platform and later used as a data source in the online platform that was developed under the Leaflet API, in which it is possible to simulate the negotiation of coffee plots involving the Coffee Coin cryptocurrency. The results showed that it was possible to identify and map the areas cultivated with coffee through Remote Sensing and that the online platform can help in the planning of new investments in coffee farming, in addition to showing an overview of the economic importance of coffee for the municipality.