Resources
Concepts and tools to link remote sensing and ground-based monitoring of European forests – D2.1
02-10-2026
This report presents approaches developed within the FORWARDS project WP2 to bridge ground-based forest monitoring and remote sensing. Advances in proximal methods, including improved dendrometer measurements, meteorological integration, and terrestrial laser scanning, have contributed towards enhanced data quality and comparability. Physiological links between leaf-level traits and drone-based optical data demonstrate that vegetation indices (VIs) can capture drought impacts and recovery at the tree scale. Scaling analyses reveal limitations in applying optical indicators across spatial resolutions and forest types, though relationships between VIs and water availability still show promise at landscape scales. Satellite-based approaches, including temporal autocorrelation, can detect early resilience loss and flag forest areas at risk. Within such targeted risk areas, satellite-based VIs could be directly correlated with plot-scale measurements or integrated within models, for which we demonstrate examples. Machine learning models integrating data from the ground and gridded meteorological data, in future also remote sensing data, can provide complementary wall-to-wall insights, e.g. on tree water deficit. Together, these approaches support identification of forest vulnerability and prioritization of monitoring efforts across Europe
Annual canopy height mapping in Italy from Landsat and multi-source LiDAR for disturbance and recovery monitoring
09-09-2026
Accurate monitoring of forest canopy height is essential for assessing forest structure, biomass, disturbance, and recovery, but airborne laser scanning (ALS) has limited coverage and high acquisition costs. We present an annual 30 m canopy height dataset for Italy from 2004–2024, integrating Landsat imagery with multi-source LiDAR through deep learning and Bayesian Model Averaging. Validation against Italian National Forest Inventory measurements yielded a mean absolute error of 3.98 m, outperforming existing Italian canopy height products despite its coarser resolution. The dataset also supports disturbance detection and recovery monitoring, achieving a mean precision of 0.64 for disturbance events from 2005–2016, and provides a harmonized resource for forest monitoring.
Natural disturbances from bark beetle outbreaks and windthrow increasingly affect Europe’s most mature and carbon-rich forests
31-08-2026
Europe’s forests store nearly 40 PgC, but climate-sensitive disturbances increasingly threaten their carbon sink. Combining three decades of satellite-derived disturbance maps with spatial data on forest age, biomass, and species composition, this study investigates whether windthrow and bark beetle outbreaks increasingly affect older, carbon-rich forests. Natural disturbances have shifted toward forests over 60 years old, with disturbed area nearly tripling since 2010. Bark beetle outbreaks increasingly affect mature spruce forests in Central Europe, driving a fivefold increase in biomass losses between 2011–2016 and 2017–2023. Projections suggest disturbances could expose carbon stocks equivalent to 20% of Europe’s current forest carbon sink by 2040.
Disturbance characteristics and forest properties regulate surface warming and recovery across Europe
25-08-2026
Forest disturbances are increasing across Europe due to climate change and land-use pressures, yet their effects on local surface climate remain poorly quantified. Combining Landsat-derived summer land-surface temperatures with a Europe-wide disturbance record, this study assesses how disturbance and forest properties shape post-disturbance warming and recovery. Disturbed forests were 1.70 °C warmer than adjacent undisturbed forests, with warming driven mainly by vegetation and canopy-structure loss and best predicted by disturbance severity. Needleleaf forests and plantations warmed more than broadleaf and natural forests. Over 82% of warming dissipated within ten years. These findings highlight biophysical controls on warming and forest-management strategies to limit it.
Spatio-temporal assessment of Toumeyella parvicornis spread in mediterranean coastal pine forests through sentinel-2 data
28-07-2026
Mediterranean coastal pine forests provide important ecological and cultural benefits but are increasingly threatened by climate change, urbanization, and invasive pests. This study develops an interpretable remote sensing framework to monitor Toumeyella parvicornis infestation in Pinus pinea forests across Campania, Italy, from 2017 to 2025. Multitemporal Sentinel-2 composites and spectral indices were combined with spatial and temporal predictors in Google Earth Engine. Random Forest models and SHAP interpretation were used to assess infestation dynamics, vulnerability, and risk. The attack-transition and risk models achieved AUC values of 0.79 and 0.80, respectively. The framework supports scalable monitoring and operational prediction of pest spread.
A meta-analysis of carbon losses and gains from tropical moist forest degradation and regeneration
03-07-2026
Carbon losses and recovery following partial disturbance in tropical moist forests (TMF) remain uncertain. This study synthesizes 146 studies quantifying aboveground carbon (AGC) changes after disturbance relative to undisturbed forests. Immediate AGC losses were greatest following forest fires (49 ± 26%), selective logging (34 ± 20%), and edge effects (31 ± 19%). Higher disturbance frequency and intensity significantly increased carbon losses. After 20 years of regeneration, recovering degraded forests retained substantially higher AGC stocks (41–117%) than secondary forests regrowing after complete deforestation (1–74%), highlighting greater recovery potential when forest structure is preserved. The resulting database and meta-analysis improve carbon inventories, modeling, and evidence-based strategies for forest recovery and climate mitigation.
