Forests play a central role in the global carbon cycle, biodiversity conservation, and climate regulation, yet their monitoring remains challenging due to spatial heterogeneity and the need for continuous, high-resolution data. While satellite-based observations provide global coverage and long-term continuity, they are constrained by spatial resolution, limited revisit frequency, cloud cover, and difficulties in resolving understory processes or fine-scale structural and physiological dynamics. As a result, satellites alone cannot capture the short-term variability or small-scale heterogeneity that govern many ecological processes.
Internet of Things (IoT) based sensor networks and UAV-based approaches address this gap by delivering spatially detailed, flexible, and high-frequency measurements that bridge the scale mismatch between in situ observations and satellite data, while also enhancing the calibration and validation of satellite products.
At the tree scale, IoT-based devices allow the near-continuous acquisition of ecophysiological variables such as stem growth and sap flow, or microclimatic conditions, as well as canopy spectral properties. IoT sensor networks facilitate the study of tree-to-tree variability in functional traits and their differential responses to climate change drivers. The development of custom-built, low-cost sensors based on open hardware and accessible electronics provides an additional pathway to intensify spatial sampling density while maintaining cost efficiency.
UAV platforms equipped with multispectral and hyperspectral sensors enable canopy-level spectral measurements, which can be processed to detect physiological stress, assess forest health, and generate biodiversity distribution maps. In parallel, UAV-borne LiDAR systems support the derivation of biomass and carbon stocks temporal change estimates, and fine-scale mapping of disturbance events (e.g., pest outbreaks, windthrow, or fire scars).
The session will present recent technological and methodological developments, case studies, and applications demonstrating how, IoT networks, low-cost electronics and UAV sensing can be embedded into ecological monitoring frameworks to improve forest observation capacity across spatial and temporal scales. Finally, research gaps and technical challenges related to integration of UAV and IoT technologies for forest monitoring will be uncovered.