Abstract
Acute droughts observed in recent years represent one of the most significant vegetation disturbances and are expected to intensify under climate change, even in cooler regions like northern Europe and the Alps often referred as the Europe’s ‘Water Tower’. Limited precipitation, higher temperatures and reduced soil moisture largely affect vegetation vigour and the water cycle. Increased drought events negatively impact canopy health, leading to larger plant water demands, elevated risk of insect outbreaks and vegetation mortality, wildfires, and also shifts in mountain forest composition. In the framework of the recently funded ESA SENWISE project (New Sentinel Missions for Optimized Wildfire Hazard, Forestry and Agriculture Monitoring), we aim to develop a high-resolution canopy water index (≤ 100 m) for forestry and agriculture management practices by leveraging sensing capabilities of the two ESA Copernicus Expansion missions: the Land Surface Temperature Radiometer (LSTM) and the Copernicus Radar Observing System for Europe at L-band (ROSE-L), supported by in-situ observations and airborne campaigns. Our approach involves two major steps: consolidating representative remote sensing datasets for LSTM and ROSE-L instruments and integrating the multi-sensor products in two-source energy balance modeling of green water flux combined with water sensitive EO indices for monitoring vegetation water status in forests and grasslands. To ensure long-term and frequent observations, we combine land surface temperature (LST) imagery through synergistic use of high-resolution NASA Landsat and ECOSTRESS data, complemented by Copernicus Sentinel-3 mission. In parallel, the representative datasets for ROSE-L will be derived from NISAR and CONAE SAOCOM dual-pol and quad-pol acquisitions to estimate vegetation biophysical properties, including tree canopy height and biomass. Initial simulations using 100-m sharpened Sentinel-3 LST data, Sentinel-2 reflectances, and LIDAR GEDI-derived canopy height show promising results. Modeled ET correlates well with eddy covariance measurements (correlation coefficient of nearly 0.6), with potential improvements expected from incorporating high-resolution inputs like Landsat and ECOSTRESS LST data and L-band derived structural parameters. The multi-sensor ET-based index will be linked with in-situ indicators of plant water availability (i.e., soil moisture and temperature, sap flow, and turbulent fluxes) to quantify its sensitivity to drought periods, vegetation type, and climatic conditions. This will provide a foundation to upscale the EO vegetation water index across study areas in South Tyrol (Italy), Wallonia Region (Belgium), and Provence (France). Following the Sentinel User Preparation initiative, SENWISE results will be shared with local stakeholders active in forestry and agricultural sectors to evaluate the practical utility of the developed product with respect to their needs and requirements.