The tool aims at supporting compliance controls and checks with various Statutory Management Requirements (SMRs) and Good Agricultural and Environmental Conditions (GAECs). SMR 1 (NVZs) and GAEC 1 (establishment of buffer strips along watercourses) are approached by the risk assessment for water pollution in the Nitrate Vulnerable Zones (NVZs). The Soil-Adjusted Vegetation Index (SAVI) identifies parcels with high soil coverage, providing a monitoring solution to the GAEC 4 (Minimum soil cover) conditions. Identifying burnt crop parcels is related to GAEC 6 (Maintenance of soil organic matter level).
Evaluation can re-use the data provided by the tools to serve many purposes.
First, they can be used, together with other data sources and other EO tools, in estimating environmental indicators. For example, the product is suitable for the estimation of soil erosion. The product describes how the combined use of GIS and erosion models, such as the Revised Universal Soil Loss Equation (RUSLE), is a practical approach for estimating the magnitude and spatial distribution of erosion and soil loss. The five major factors used by RUSLE to compute the expected average soil loss include rainfall pattern, soil type, topography, crop system, and management practices. The product will generate individual GIS layers for each factor in the RUSLE equation and combine them at a parcel scale to predict the soil loss spatially.
Second, the tools can be used to evaluate the effects of agricultural policy measures on environmental indicators. For example, an evaluator can use IACS to derive information on beneficiaries and non-beneficiaries of measures protecting from soil erosion by providing cover or enhancing soil organic matter by fixing nutrients.
Third, information and data from the toolbox can cross-validate and triangulate information received from other sources. For example, the Automated Burnt Scar Mapping can triangulate adaptation to the LULUCF due to burnt areas.
The tool's adoption requires access to EO, the adaptation and application of the algorithms and their training to recognize the crop types of the region or the Member State. It is assumed that the IT infrastructure is adequate and that the evaluator can use the data. In general, when using EO, several conditions may limit their utility and functionality. The most important are cloudiness, the prevalence of small parcels, and the effort that may be needed to link the EO maps to the LPIS and IACS.
When fully operational, the ENVISION platform will be open-source. However, access to the tool will be given primarily to the partners and selected customers identified by the project. The toolbox will not be publicly available due to its specificities and the need to have an in-depth exchange of information with potential users before its use. Interested stakeholders and prospective users should contact the project holder.
