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

被引:30
|
作者
Sarvia, Filippo [1 ]
Xausa, Elena [2 ]
Petris, Samuele De [1 ]
Cantamessa, Gianluca [2 ]
Borgogno-Mondino, Enrico [1 ]
机构
[1] Univ Turin, Dept Agr Forest & Food Sci, Lgo Braccini 2, I-10095 Grugliasco, Italy
[2] Agenzia Reg Piemontese Erogaz Agr, Via Bogino 23, I-10123 Turin, Italy
来源
AGRONOMY-BASEL | 2021年 / 11卷 / 01期
关键词
common agricultural policy; service prototype development; crop monitoring; crop detection; random forest classification; minimum distance classification;
D O I
10.3390/agronomy11010110
中图分类号
S3 [农学(农艺学)];
学科分类号
0901 ;
摘要
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.
引用
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页数:19
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