Published October 3, 2022 | Version 1

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

  • 1. Sinergise. 29, Cvetkova, Ljubljana, Slovenia, 386-1-320-6150

Description

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.

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

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

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

  4. 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)

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

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

  7. 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

Files

Files (1.3 GB)

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md5:004495b7e9d82b68685ea91cd3af72af
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Additional details

Funding

European Commission
DIONE - DIONE: an integrated EO-based toolbox for modernising CAP area-based compliance checks and assessing respective environmental impact 870378