EO-based area monitoring markers computed over the Lithuanian pilot region (2022)

In the context of the EU-funded project DIONE (No. 870378), the following EO-based monitoring marker maps were released over the two pilot regions, containing the results produced from a set of image analysis and machine learning techniques. The latest explores the benefits of Copernicus's multispectral high-resolution Sentinel-2 data acquired from 01-01-2022 until 04-07-2021 and provides tailored information for the needs of European paying agencies (e.g. CAPO and NPA), expressed with the following markers. <strong>Mowing marker:</strong> used to detect mowing events on meadow/grass like Features Of Interest (FOI) <strong>Mean-NDVI marker:</strong> used to detect erroneous claims with no vegetation <strong>Homogeneity marker:</strong> used to determine if a parcel geometry consists of a single crop or if multiple things are growing on the parcel <strong>Bare soil marker:</strong> used to detect observation where bare soil is present on the feature of interest. This indicates agricultural activity on the FOI (plowing, harvest) <strong>Similarity and distance markers:</strong> used to give additional context to the crop classification and to detect erroneous claims <strong>Land marker:</strong> used to detect the land type and non-productive EFAs of the FOI <strong>Crop-type marker:</strong> used to detect the specific crop growing on the FOI This dataset is comprised of one geopackage file, the <em>"markers_summary.gpkg", which</em> was computed for the Lithuanian pilot region<em>. </em>Descriptions are given below. <strong>Markers summary dataset: </strong>There is a total of **1074460** FOIs for the complete country GSAA dataset. Out of these, markers are computed on **996028** FOIs that contain more than 1 Sentinel-2 pixel. <strong>Description of the information contained in the corresponding "markers summary" dataset</strong> Attribute name Description POLY_ID Reference ID of the polygon CROP_LABEL Declared crop group S2_all_observations_count Count of all observations S2_valid_observations_count Count of all valid observations S2_pixel_count Number of S2 pixels within FOI declared_as Declared crop group (v1) classification_score The pseudoprobability of the crop-group (v1) prediction. A score close to 1 indicates that the model is very confident in the prediction classification The FOI label as predicted by the crop group (v1) model crop_declared_as_2 Declared crop group (v2) crop_classification_score_2 The pseudoprobability of the crop-group (v2) prediction. A score close to 1 indicates that the model is very confident in the prediction crop_classification_2 The FOI label as predicted by the crop group (v2) model mowing_event_count Number of mowing events detected