Remote sensing of cropping practice in Northern Italy using time-series from Sentinel-2

[Display omitted] •Gross features of the phenology of fields can be detected with Sentinel-2.•High weed infestations can be detected from NDVI time series from Sentinel-2.•Seven phenological classes of cropping practice were mapped for two Sentinel-2 tiles.•Two thirds of the winter crops show some sign of weed infestation.•The thematic accuracy of the land use map is assessed to 69%. Maps of cropping practice, including the level of weed infestation, are useful planning tools e.g. for the assessment of the environmental impact of the crops, and Northern Italy is an important example due to the large and diverse agricultural production and the high weed infestation. Sentinel-2A is a new satellite with a high spatial and temporal resolution which potentially allows the creation of detailed maps of cropping practice including weed infestation. To explore the applicability of Sentinel-2A for mapping cropping practice, we analysed the Normalised Differential Vegetation Index (NDVI) time series from five weed-infested crop fields as well as the areas designated as non-irrigated agricultural land in Corine Land Cover, which also contributed to an increased understanding of the cropping practice in the region. The analysis of the case studies showed that the temporal resolution of Sentinel-2A was high enough to distinguish the gross features of the cropping practice, and that high weed infestations can be detected at this spatial resolution. The analysis of the entire region showed the potential for mapping cropping practice using Sentinel-2. In conclusion, Sentinel-2A is to some extent applicable for mapping cropping practice with reasonable thematic accuracy.