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Sentinel-2 satellite data enables multispectral monitoring of the earth at a high temporal revisit rate. Combining this information with a network of optical ground measurements enables a more detailed and a more complete understanding of terrestrial ecosystems. However, independent optical ground measurements often lack consistency, especially when comparing different sites in geographically remote locations. Using the very high temporal and spectral resolution offered by the automated field spectrometer systems FloX and RoX (Fluorescence Box and Reflectance Box, respectively, JB-Hyperspectral Devices GmbH, Duesseldorf, Germany), we investigated continuous time series ranging over three years and in ten different locations across Europe, Africa, America and Asia. The continuous records of ground-measured reflectance were first validated against Sentinel-2 top of canopy (TOC) reflectance to evaluate the consistency of the in-situ network. Our results suggest a good agreement of ground-measured reflectance with Sentinel-2 TOC reflectance in vegetation and snow with R2 around 0.79 in the 833 nm band and R2 up to 0.94 in the bands around 559 nm and 492 nm, demonstrating good consistency across the network. Spatial misalignment of Sentinel-2 pixel-sizes with respect to the different footprint sizes of the ten automated spectrometers on the ground, atmospheric uncertainties, sub-optimal instrument setup and spatial-temporal variable landscape heterogeneity were identified as the most relevant sources of uncertainties in the network. Comparing the Normalized Difference Vegetation Index (NDVI), Transformed Chlorophyll Absorption in Reflectance Index (TCARI) and Enhanced Vegetation Index (EVI) between ground and satellite revealed a decreasing agreement with increasing complexity of index formulation. The best agreement between satellite and ground was exhibited by NDVI with R2 around 0.96 and relative error of 4.3% investigating vegetation and snow across all ten sites. Fu

Knowledge of actual crop transpiration (T) is important for advanced crop management but challenging to obtain due to the large spatial and temporal variation of T. Remote sensing offers various possibilities to assess T dynamics, while particularly sun-induced chlorophyll fluorescence (SIF) has been demonstrated as a sensitive empirical proxy for T. Despite this success, the advancement of the mechanistic understanding of how SIF relates to T dynamics is key for the future development and implementation of robust and reliable SIF-based T products. This study aims to contribute insights by experimentally assessing the sensitivity of several SIF-based T estimation strategies for evolving soil water limitation. We investigated extensive in situ and airborne data acquired during a water limitation experiment in a maize canopy in northern Italy. We evaluated five empirical strategies to integrate SIF in a T modelling framework based on the Penman-Monteith (PM) and the Ball-Berry-Leuning (BBL) concepts. Our results indicate that replacing model parameters sensitive to canopy conductance with SIF results in the best agreement between modelled and measured T under evolving water limitation. Our study contributes expanding existing knowledge with empirical insights on the sensitivity of SIF based T approaches under increasing soil water limitation at short time scales.