Supporting the Common Agricultural Policy with Sentinel-2 data and deep recurrent networks

2021 ◽  
Author(s):  
Manuel Campos-Taberner ◽  
Francisco Javier García-Haro ◽  
Beatriz Martínez ◽  
Sergio Sánchez-Ruiz ◽  
María Amparo Gilabert
Keyword(s):  
Agricultural Policy ◽  
Common Agricultural Policy ◽  
Recurrent Networks ◽  
The Common ◽  
Sentinel 2

scholarly journals Scalable Parcel-Based Crop Identification Scheme Using Sentinel-2 Data Time-Series for the Monitoring of the Common Agricultural Policy

2018 ◽  
Vol 10 (6) ◽  
pp. 911 ◽  
Author(s):  
Vasileios Sitokonstantinou ◽  
Ioannis Papoutsis ◽  
Charalampos Kontoes ◽  
Alberto Arnal ◽  
Ana Pilar Andrés ◽  
...  
Keyword(s):  
Time Series ◽  
Agricultural Policy ◽  
Common Agricultural Policy ◽  
Identification Scheme ◽  
The Common ◽  
Sentinel 2

scholarly journals A Possible Role of Copernicus Sentinel-2 Data to Support Common Agricultural Policy Controls in Agriculture

Agronomy ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 110
Author(s):  
Filippo Sarvia ◽  
Elena Xausa ◽  
Samuele De Petris ◽  
Gianluca Cantamessa ◽  
Enrico Borgogno-Mondino
Keyword(s):  
Agricultural Policy ◽  
Common Agricultural Policy ◽  
Observation Data ◽  
Key Factor ◽  
Ndvi Time Series ◽  
Earth Observation Data ◽  
Four Levels ◽  
Nw Italy ◽  
Sentinel 2

Farmers that intend to access Common Agricultural Policy (CAP) contributions must submit an application to the territorially competent Paying Agencies (PA). Agencies are called to verify consistency of CAP contributions requirements through ground campaigns. Recently, EU regulation (N. 746/2018) proposed an alternative methodology to control CAP applications based on Earth Observation data. Accordingly, this work was aimed at designing and implementing a prototype of service based on Copernicus Sentinel-2 (S2) data for the classification of soybean, corn, wheat, rice, and meadow crops. The approach relies on the classification of S2 NDVI time-series (TS) by “user-friendly” supervised classification algorithms: Minimum Distance (MD) and Random Forest (RF). The study area was located in the Vercelli province (NW Italy), which represents a strategic agricultural area in the Piemonte region. Crop classes separability proved to be a key factor during the classification process. Confusion matrices were generated with respect to ground checks (GCs); they showed a high Overall Accuracy (>80%) for both MD and RF approaches. With respect to MD and RF, a new raster layer was generated (hereinafter called Controls Map layer), mapping four levels of classification occurrences, useful for administrative procedures required by PA. The Control Map layer highlighted that only the eight percent of CAP 2019 applications appeared to be critical in terms of consistency between farmers’ declarations and classification results. Only for these ones, a GC was warmly suggested, while the 12% must be desirable and the 80% was not required. This information alone suggested that the proposed methodology is able to optimize GCs, making possible to focus ground checks on a limited number of fields, thus determining an economic saving for PA and/or a more effective strategy of controls.

scholarly journals Budget of the EU and Common Agricultural Policy for 2014-2020 in the light of the polish interests

Management ◽  
2014 ◽  
Vol 18 (1) ◽  
pp. 473-487
Author(s):  
Andrzej Czyżewski ◽  
Sebastian Stępień
Keyword(s):  
European Commission ◽  
Agricultural Policy ◽  
Common Agricultural Policy ◽  
European Parliament ◽  
Point Of View ◽  
European Council ◽  
The Political ◽  
The Common ◽  
Polish Economy ◽  
The Eu

Summary The objective of the paper is to present the results of negotiations on the EU budget for 2014-2020, with particular emphasis on the Common Agricultural Policy. Authors indicate the steps for establishing the budget, from the proposal of the European Commission presented in 2011, ending with the draft of UE budget agreed at the meeting of the European Council on February 2013 and the meeting of the AGRIFISH on March 2013 and then approved by the political agreement of the European Commission, European Parliament and European Council on June 2013. In this context, there will be an assessment of the new budget from the point of view of Polish economy and agriculture.

scholarly journals Sentinel-2 Based Temporal Detection of Agricultural Land Use Anomalies in Support of Common Agricultural Policy Monitoring

2018 ◽  
Vol 7 (10) ◽  
pp. 405 ◽  
Author(s):  
Urška Kanjir ◽  
Nataša Đurić ◽  
Tatjana Veljanovski
Keyword(s):  
Land Use ◽  
Time Series ◽  
Agricultural Policy ◽  
Common Agricultural Policy ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Agricultural Land ◽  
Agricultural Land Use ◽  
Land Use Control ◽  
Sentinel 2

The European Common Agricultural Policy (CAP) post-2020 timeframe reform will reshape the agriculture land use control procedures from a selected risk fields-based approach into an all-inclusive one. The reform fosters the use of Sentinel data with the objective of enabling greater transparency and comparability of CAP results in different Member States. In this paper, we investigate the analysis of a time series approach using Sentinel-2 images and the suitability of the BFAST (Breaks for Additive Season and Trend) Monitor method to detect changes that correspond to land use anomaly observations in the assessment of agricultural parcel management activities. We focus on identifying certain signs of ineligible (inconsistent) use in permanent meadows and crop fields in one growing season, and in particular those that can be associated with time-defined greenness (vegetation vigor). Depending on the requirements of the BFAST Monitor method and currently time-limited Sentinel-2 dataset for the reliable anomaly study, we introduce customized procedures to support and verify the BFAST Monitor anomaly detection results using the analysis of NDVI (Normalized Difference Vegetation Index) object-based temporal profiles and time-series standard deviation output, where geographical objects of interest are parcels of particular land use. The validation of land use candidate anomalies in view of land use ineligibilities was performed with the information on declared land annual use and field controls, as obtained in the framework of subsidy granting in Slovenia. The results confirm that the proposed combined approach proves efficient to deal with short time series and yields high accuracy rates in monitoring agricultural parcel greenness. As such it can already be introduced to help the process of agricultural land use control within certain CAP activities in the preparation and adaptation phase.

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