In June 2025, TREAD was launched. Led by the Consejo Superior de Investigaciones Científicas (CSIC, Spain), and with the participation of the University of Córdoba and CoLAB ForestWISE, this project aims to develop an automated system for the early detection of forest vulnerability, using functional parameters and thermal data from remote sensing.

Developing models for the early detection of pest and disease symptoms is a challenge due to the limited knowledge of the physiological changes that affect plant functional parameters under stress. Although remote sensing data shows potential for quantifying parameters that provide information about susceptibility to pests and diseases at an early stage, the specific responses to different stress factors remain poorly understood. Furthermore, the spatial and temporal transferability of pest and disease detection models is still limited.

The TREAD project aims to overcome these limitations and create a satellite monitoring system of critical disturbance points, facilitating the early detection of changes. The focus of the project will be on areas of Pinus spp. and Quercus spp. affected by water stress and diseases caused by agents such as Phytophthora and the pine wood nematode, along a climatic gradient in Portugal and Spain.

Over two years, real-time data will be collected from remote sensing, field measurements and physical models.