AgroForChange (AFC)
ANALYSIS OF THE HISTORICAL DEVELOPMENT OF THE TERRITORY
Itagra CT
Detecting New Forests Using AI
What is it and what is it used for?
It is a software solution designed entirely in R to analyze land-use changes over the past 20 years. It uses satellite time series (Landsat/Sentinel) and Artificial Intelligence (Random Forest) to automatically detect abandoned agricultural plots that are being converted into forest land. It is used to update forest inventories and monitor land-use changes on a large scale and with high precision.
This is a specific technical contribution by Itagra CT under Action A.3.2 of RetechFOR for the continuous and automated inventory of forest resources.
The problem it solves
The change in land use from agricultural to forest land is governed by the Forestry Law of Castile and León, which stipulates that agricultural land that has been abandoned for a period of at least 20 years is reclassified as forest land. Through the application, we aim to identify which areas have been converted to forest land, quantify them, and also use this as an early warning system to detect areas that are currently in the process of transition.
“Technologyat our service to reveal changes in the landscape and turn rural abandonment into an opportunity for forest management through Big Data and Artificial Intelligence detection techniques.”
What makes it innovative?
Automated detection of new forests
Use of artificial intelligence to accurately identify large areas of new forest land, drastically reducing the manual labor required to locate and analyze them.
Dynamic Forest Inventory
Continuous, near-real-time updates of forest data, providing more up-to-date, accurate, and scalable information than that obtained through traditional inventory methods.
Expected impact
It optimizes forest management and reduces the risk of wildfires by identifying abandoned areas where fuel accumulates. Economically, it drastically reduces inventory costs through automation and helps identify new sources of biomass. Socially, it provides key data for managing rural abandonment and clarifying the legal status of land in transition, facilitating its sustainable use.
