E-FORESTER

The E-FORESTER project (Grant Agreement No. 101182985) represents a paradigm shift in environmental monitoring. Aligning with the European Green Deal and the Valletta Convention, we are bridging the gap between field biology, archaeology, and cutting-edge robotics.

Our mission is to construct an autonomous Unmanned Ground Vehicle (UGV) capable of navigating complex, GPS-denied forest environments. Equipped with AI-driven edge computing and multimodal sensor arrays, the rover acts as a continuous, non-invasive observer of our natural and cultural landscapes.

Traditional biological inventory is labor-intensive and difficult to scale. E-FORESTER introduces a "human-in-the-loop" AI approach to ecological monitoring across temperate (Poland), alpine (Italy), and Mediterranean (Cyprus) ecosystems.

Tracking Fauna: Using high-resolution optical cameras and lightweight deep learning models (like YOLOv8), the rover identifies tracks, scat, and other signs of elusive medium-sized mammals (e.g., foxes, badgers) directly in the field.

Tick-Borne Disease Mapping: The rover features a robotic sampling module utilizing the flagging/dragging method. Combined with real-time microclimate sensors, it maps tick abundance to create highly accurate, dynamic epidemiological risk models.

Tree-Related Microhabitats (TreMs): By fusing LiDAR point clouds with multispectral data, the rover assesses forest health and identifies crucial microhabitats, such as tree cavities and anthills, which serve as ecological hubs.

Forests often conceal centuries of human activity beneath their dense canopies, rendering traditional aerial and satellite prospection ineffective. E-FORESTER utilizes a synergistic suite of geophysical tools to perform non-invasive subsurface mapping.

Geophysical Prospection: The rover payload incorporates Ground-Penetrating Radar (GPR), Time-Domain Electromagnetics (TDEM), and Magnetometry to identify buried walls, hearths, and ditches.

Plant Vitality as a Clue: We apply a groundbreaking interdisciplinary approach. Subsurface ruins alter local soil moisture and chemistry. By utilizing multispectral imaging, the rover detects "cropmarks" and subtle physiological stress in the forest undergrowth, using the plants themselves as indicators of buried archaeological relics.