Monitoring, remote sensing and forest modelling
We develop and integrate tools to observe forests from individual trees to landscapes and to transform observations into indicators, maps and scenarios. The goal is not simply to collect more data, but to connect different spatial scales and information sources in order to understand processes that are difficult to observe directly.
Research questions
- How can sensors, field surveys, drones and satellites be integrated?
- Which indicators can provide early detection of stress and change?
- How can models be used to explore scenarios that cannot be directly observed?
Approaches and methods
We use IoT sensors and Tree Talkers, terrestrial, airborne and satellite LiDAR, multispectral and hyperspectral imagery, drones, GIS, time series, and models of growth, landscape dynamics, carbon and fire behaviour. A central part of our work concerns integration and cross-validation among independent data sources.
Related projects
ForBEST · REWILD-FIRE · FIRE-BOX · eLTER+ · USEFOL · Regione Lombardia – foreste di protezione · Regione Lombardia – boschi vetusti · Parco del Ticino · Val di Mello · Tree Talker · BIO-WATCH · Parco Italia
Selected publications
- Vizzarri M. et al. (2025). Hearing nature’s heartbeat: towards large-scale real-time forest monitoring network in Italy.
- Ceriani R. et al. (2025). Hyperspectral and LiDAR space-borne data for assessing mountain forest volume and biomass.
- Hof A.R. et al. (2024). A perspective on the need for integrated frameworks linking species distribution and dynamic forest landscape models across spatial scales.
- Oggioni S.D. et al. (2026). Simulating silver fir provenance responses to climate change: A forest modelling approach in the Northern Apennines.
- Vacchiano G., Motta R. (2015). An improved species distribution model for Scots pine and downy oak under future climate change in the NW Italian Alps.