Agricultural and Veterinary sciences, Agriculture, Forestry and Fisheries, Agricultural Science, Lantbruksvetenskap och veterinärmedicin, Jordbruk, skogsbruk och fiske, Jordbruksvetenskap, Engineering and Technology, Environmental Engineering, Earth Observation, Teknik, Naturresursteknik, Jordobservationsteknik

Monitoring agricultural land with optical remote sensing offers a valuable tool for estimating crop yield and supporting decision-making for food security. Cropland phenology indicators, such as the start of season (SOS), the end of season (EOS), and the number of growing seasons per year, provide essential information for land managers. While established toolboxes like TIMESAT have been extracting phenological metrics from coarse remote sensing data for two decades, agricultural monitoring applications demand continuous time series of high-resolution data, made possible by the European Union's Copernicus Sentinel-2 since 2015. Recently, the Copernicus Land Monitoring Service (CLMS) released the pan-European High-Resolution Vegetation Phenology and Productivity (HR-VPP) product suite. We conducted the first comprehensive validation of the analysis-ready SOS and EOS metrics from the VPP dataset of the HR-VPP product over a large set of agricultural fields spanning 10 countries, 14 crop types and 164 growing seasons. Our results demonstrate that the VPP product of the HR-VPP dataset correlates well with the sowing (r2 = 0.75) and harvesting (r2 = 0.56) dates observed in situ. The biases differ between spring (SOS bias: 59 days, EOS bias: 3 days) and winter (SOS bias: 136 days, EOS bias: –44 days) crops, likely due to the suppression of the autumn vegetation signal in the plant phenology index (PPI) by a solar zenith angle-dependent gain factor. We show that other indicators from the HR-VPP Vegetation Indices (VIs) product and re-parameterization of TIMESAT or DATimeS toolboxes are more suitable for winter crop phenology monitoring. This study calls for researchers and practitioners to carefully evaluate the performance of analysis-ready products to ensure their suitability for specific applications, ultimately promoting informed decision-making in agricultural management and food security endeavours.