Forests play a critical role in the global carbon cycle, acting as either carbon sinks or sources depending on natural and anthropogenic factors. Understanding these dynamics, particularly in remote, hard-to-reach forests, is essential for addressing climate change. The RemoTrees project aims to bridge the gap between satellite Earth Observations (EO) and in-situ data to improve the accuracy and reliability of carbon flux assessments in these ecosystems.

RemoTrees focuses on the development and deployment of advanced IoT multi-sensor devices designed to monitor physiological and radiometric parameters of forests. These devices provide near-real-time, high-resolution data on variables such as under-canopy VIS-NIR data, soil moisture, and sap flow, with a particular focus on radiometric indicators vital for assessing forest health and carbon dynamics. By installing these sensors in remote forests, we can generate comprehensive ground-based datasets that are currently lacking, enabling more accurate validation and calibration of satellite-derived measurements.

Our approach leverages EO data to model and predict the impacts of extreme climate events (e.g., storms, droughts, heatwaves, heavy precipitation) and human activities (e.g., logging, land-use changes, soil protection practices) on the carbon cycle. Integrating IoT sensor data with satellite observations enhances our ability to detect early signs of carbon losses or gains in biomass and soil, contributing to a more refined understanding of terrestrial carbon pools.

The outcomes of RemoTrees will offer key insights into the role of remote forests in the carbon cycle and their response to environmental stressors. This will support more effective conservation and management strategies, ultimately aiding global climate mitigation efforts. Our presentation will showcase the technological innovations of RemoTrees, preliminary data from existing TT-Cyber installations (the baseline for RemoTrees devices), and implications for future EO-based carbon studies.