Linking Sap Flow Measurements with Earth Observations
This work addresses the problem of upscaling ecosystem fluxes for forest resilience analysis in climate change, though it is incremental as it applies existing methods to new data.
The study tackled the challenge of linking single-tree transpiration with earth observations by using sap flow sensors in spruce forests and Sentinel-2 data within a machine learning framework, achieving cross-validated R2 values between 0.57 and 0.80 for modeling canopy transpiration.
While single-tree transpiration is challenging to compare with earth observation, canopy scale data are suitable for this purpose. To test the potentialities of the second approach, we equipped the trees at two measurement sites with sap flow sensors in spruce forests. The sites have contrasting topography. The measurement period covered the months between June 2020 and January 2021. To link plot scale transpiration with earth observations, we utilized Sentinel-2 and local meteorological data. Within a machine learning framework, we have tested the suitability of earth observations for modelling canopy transpiration. The R2 of the cross-validated trained models at the measurement sites was between 0.57 and 0.80. These results demonstrate the relevance of Sentinel-2 data for the data-driven upscaling of ecosystem fluxes from plot scale sap flow data. If applied to a broader network of sites and climatic conditions, such an approach could offer unprecedented possibilities for investigating our forests' resilience and resistance capacity to an intensified hydrological cycle in the contest of a changing climate.