Grassland mowing detection tool

• diversification may exclude grassland, and thus authorities should know its area, which once detected can be calculated from the LPIS; 
• cultivated annual grasslands and permanent (multiyear) grasslands already included under the categories of ‘catch crops’ and/or ‘nitrogen-fixing crops’ at farm-level are excluded from EFA - catch crop and EFA - nitrogen-fixing crop measures; 
• land abandonment estimates exclude previously abandoned grassland fields, a service that was not explicitly assessed by the tool but is possible and very relevant for monitoring.   

Evaluators can re-use the data provided by the tool in various operations. First, the tool can contribute or cross-validate data from other sources to identify natural grassland. Natural grassland is a building block of many context and impact indicators, e.g. C.05 ‘Land Cover’, C.19 ‘Farming in Natura 2000 areas’, C.40 and I.11 ‘Enhancing carbon sequestration: Soil organic carbon in agricultural land’, and the result indicator R.14PR ‘Carbon storage in soils and biomass’. 

The above-mentioned areas of use of the grassland mowing detection tool are indicative and by no means exclusive. 

The tool developed algorithms and processes that allow interested stakeholders to apply it in their regions or the Member States. However, the tool's adoption requires adaptation and application of the algorithms and training to recognize mowing events at a region or the Member State. Adopting the tool assumes that the IT infrastructure is adequate and that the evaluator can use the data. #

The computing system’s specifications are detailed at: http://esa-sen4cap.org/content/download-package-description 

Downloading the package is open to anyone and free of charge. 

 In general, several conditions may limit the utility and functionality of EO. The most critical limitation is the extent of inconclusive parcels, i.e. parcels for which there is no definite crop identification. Inconclusive parcels may be due to specific EO factors such as cloudiness or the prevalence of small parcels, or difficulties in producing the algorithms to train and forecast crop type. Another difficulty is related to the effort and time needed to link the grassland mowing map with the LPIS and IACS.