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.

Mowing marker: used to detect mowing events on meadow/grass like Features Of Interest (FOI)

Mean-NDVI marker: used to detect erroneous claims with no vegetation

Homogeneity marker: used to determine if a parcel geometry consists of a single crop or if multiple things are growing on the parcel

Bare soil marker: used to detect observation where bare soil is present on the feature of interest. This indicates agricultural activity on the FOI (plowing, harvest)

Similarity and distance markers: used to give additional context to the crop classification and to detect erroneous claims

Land marker: used to detect the land type and non-productive EFAs of the FOI

Crop-type marker: used to detect the specific crop growing on the FOI

This dataset is comprised of one geopackage file, the "markers_summary.gpkg", which was computed for the Lithuanian pilot region. Descriptions are given below.

Markers summary dataset: 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.

Description of the information contained in the corresponding "markers summary" dataset

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