Healthier Forests Through Early Detection of Diseases

The Balearic Islands apply digital innovation to improve forest health

What does it consist of?

The active conservation of Balearic forests requires new tools against pests and diseases. This plan promotes the use of modelling and monitoring technology to predict threats and strengthen plant protection management in the main forest ecosystems of the archipelago.

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Data

PROJECT TITLE IN THE CALL
Forest Health 3.0: use of new technologies applied to forest modernisation and the phytosanitary improvement of forest stands.
LOCATION
Mallorca, Minorca, Ibiza, Formentera
Entity submitting the PROJECT
Govern de les Illes Balears
Entity that executes the project
Conselleria de Medi Ambient i Territori
Project code
ITS2019-137
Total project amount
709.210 €
ITS granted amount
709.210 €
Executed amount
660.809 €
Call year
2019
Execution status
Executed
Purpose
Environment
Budget execution
Executed: 93.18%
Last data request
13.04.2026

The project

Island forests, such as the pine and oak forests on the Balearic Islands, are increasingly at risk from invasive species and forest diseases. To tackle this deterioration, the Balearic Government has launched a strategy that combines citizen science with new technology to strengthen forest health based on holistic prevention.

The plan includes three lines of action: the application of prediction models and technology to monitor damage, the creation of a web viewer with accessible plant protection monitoring data, and the direct implementation of treatments in the most vulnerable areas of forest. These actions are particularly focused on protected natural areas and public estates.

Essential to the project is the monitoring network based on Geographic Information Systems (GIS), which integrates data from trapping, affection maps and monitoring plots. Public access to this information aims to involve citizens and local actors in active forest management.

This action seeks to tackle threats such as Xylella fastidiosa and strengthen the capacity to respond to new diseases. The experience will serve to create models of action protocols, where prediction and digital analysis help to prevent delayed reactions to forest emergencies.