Case Study: Red Eléctrica Group reduces vegetation risk with Overstory

How Overstory Helped REE Identify 37 Species of Trees and Other Vegetation Across 13 Climate Zones from Satellite Data

Red Eléctrica de España (REE), the sole transmission system operator for Spain's national grid, faced a significant challenge in managing vegetation risk across its vast network of high voltage lines. The diverse ecosystems of Spain contain vegetation with vastly different growth rates, and complying with strict electrical and environmental regulations required knowing the exact species growing near their rights-of-way. Manually mapping these 37 different species was cost-prohibitive, creating a major barrier to adopting a risk-based approach for pruning. To solve this, REE partnered with the vegetation intelligence vendor Overstory.

Overstory implemented a scalable solution using high-resolution satellite imagery and machine learning to accurately identify and map all 37 tree, shrub, and grass species across 10,000 miles of REE's corridors. The results exceeded REE's accuracy expectations, enabling the utility to fully integrate this data into its risk models and maintenance cycle. This provided REE with an up-to-date view of risk, allowing them to optimize their budget by focusing pruning efforts on the highest-risk areas and ensuring full regulatory compliance across the country.

Red Eléctrica Group

Iago Veiras Lens

Artificial Intelligence Partner