SimpLee

Why is it important?

Reforestation plays a key role in the fight against climate change, but selecting the most suitable species for each terrain and accurately estimating their carbon sequestration capacity remains a challenge. GreenWest addresses this issue using artificial intelligence, integrating forest, climate, and satellite data to optimise reforestation projects and promote more efficient, sustainable carbon management.

Project objective

To develop an artificial intelligence model capable of predicting CO₂ absorption capacity in Spanish forest ecosystems based on climate, soil, and tree species variables, providing a tool that optimizes the planning of reforestation projects, facilitates the generation of carbon credits, and supports environmental decision-making.

How does it work?

GreenWest integrates information from the Spanish National Forest Inventory, climate data from Copernicus ERA5-Land, and vegetation indices obtained from Landsat imagery processed using Google Earth Engine. After a cleaning, unification, and storage process in a relational database, the data feeds various machine learning models that estimate the biomass and carbon sequestration capacity of each forest plot. Based on these predictions, the platform identifies the combinations of species and terrain conditions with the highest potential for CO₂ absorption, providing a decision-support tool for planning reforestation projects and validating carbon credits. The system combines technologies such as Python, Google Earth Engine, QGIS, ArcGIS, MySQL, and Machine Learning algorithms such as CatBoost, LightGBM, XGBoost, and Random Forest.

Research lines

Environmental data integration: Unification of forest, climate, and satellite information into a relational database prepared for training artificial intelligence models.

Predictive models for carbon sequestration: Development and evaluation of machine learning algorithms to estimate biomass and CO₂ absorption capacity in forest ecosystems.

Smart reforestation: Analysis of the most efficient combinations of species, terrain characteristics, and climate conditions to maximise carbon sequestration.

Relationship with the demographic challenge

GreenWest contributes to the demographic challenge by promoting the recovery and valorisation of underutilised forest and agricultural land in rural areas through artificial intelligence tools that optimise carbon sequestration. By encouraging more efficient reforestation projects and facilitating the generation of carbon credits, the project creates new opportunities for sustainable economic development, incentivising activity and investment in areas affected by depopulation.