Scalable Parcel-Based Crop Identification Scheme Using Sentinel-2 Data Time-Series for the Monitoring of the Common Agricultural Policy  
[PERSON]  
1 Institute for Space Applications and Remote Sensing, National Observatory of Athens, I. Metaxa and Vas. Pavlou St, Penteli, 15236 Athens, Greece; [EMAIL_ADDRESS] (I.P. ); [EMAIL_ADDRESS] (C.K.) 2 INITA Tecnologias e Infraestructuras Agroalimentarias, Av. [PERSON], 22, 31610 Villava, Spain; [EMAIL_ADDRESS] (A.L.A. ); [EMAIL_ADDRESS] (A.P.A.A. ); [EMAIL_ADDRESS] (J.A.G.Z.) [PERSON]  
2 Institute for Space Applications and Remote Sensing, National Observatory of Athens, I. Metaxa and Vas. Pavlou St, Penteli, 15236 Athens, Greece; [EMAIL_ADDRESS] (I.P. ); [EMAIL_ADDRESS] (C.K.) 2 INITA Tecnologias e Infraestructuras Agroalimentarias, Av. [PERSON], 22, 31610 Villava, Spain; [EMAIL_ADDRESS] (A.L.A. ); [EMAIL_ADDRESS] (A.P.A.A. ); [EMAIL_ADDRESS] (J.A.G.Z.) 2 Institute for Space Applications and Remote Sensing, National Observatory of Athens, I. Metaxa and Vas. Pavlou St, Penteli, 15236 Athens, Greece; [EMAIL_ADDRESS] (I.P. ); [EMAIL_ADDRESS] (C.K.) 2 INITA Tecnologias e Infraestructuras Agroalimentarias, Av. [PERSON], 22, 31610 Villava, Spain; [EMAIL_ADDRESS] (A.L.A. ); [EMAIL_ADDRESS] (A.P.A.A. ); [EMAIL_ADDRESS] (J.A.G.Z.) 2 Institute for Space Applications and Remote Sensing, National Observatory of Athens, I. Metaxa and Vas. Pavlou St, Penteli, 15236 Athens, Greece; [EMAIL_ADDRESS] (I.P. ); [EMAIL_ADDRESS] (C.K.) 2 INITA Tecnologias e Infraestructuras Agroalimentarias, Av. [PERSON], 22, 31610 Villava, Spain; [EMAIL_ADDRESS] (A.L.A. ); [EMAIL_ADDRESS] (A.P.A.A. ); [EMAIL_ADDRESS] (J.A.G.Z.) 2 Institute for Space Applications and Remote Sensing, National Observatory of Athens, I. Metaxa and Vas. Pavlou St, Penteli, 15236 Athens, Greece; [EMAIL_ADDRESS] (I.P. ); [EMAIL_ADDRESS] (C.K.) 2 Institute for Space Applications and Remote Sensing, National Observatory of Athens, I. Metaxa and Vas. Pavlou St, Penteli, 15236 Athens, Greece; ipapoutsis@noa. applications to their paying agency, declaring the location and the cultivated crop type for all owned parcels [4]. In turn, paying agencies are required to inspect at least 5% of declarations, via means of field visits and photointerpretation of Very High Resolution (VHR) and High Resolution (HR) satellite imagery (i.e., SPOT, Worldview, IKONOS) [4; 5]. However, these methods are time-consuming, complex, and reliant on the skills of the inspector. Contrariwise, automated remote sensing methods, suitably designed with respect to computational efficiency, large-scale coverage, and spatial resolution, can offer a monitoring alternative with reliable solutions [2]. In the context of the expected CAP 2020+ reform, there is a clear intention for simplification and a reduction of the administrative burden for both farmers and paying agencies. This study showcases how timely and accurate crop identification can assist the paying agency controls, suggesting an effective and efficient tool towards the required shift from sample inspections to large scale monitoring. The freely available data and global coverage of Landsat satellites have established them, over the years, as one of the primary data sources for operational agriculture monitoring applications. Landsat data have been exploited in crop type mapping from as early as the 1980s, with [PERSON] and [PERSON] (1984) using Vegetation Index (VI) time-series under threshold-based approaches, while in more recent studies their usage has evolved into non-parametric supervised classification schemes [2; 6]. However, low (e.g., MODIS 250 m) and moderate (e.g., Landsat 30 m) spatial resolution data, with pixel sizes comparable to the parcel area, provide suboptimal thematic accuracy [7]. VHR (e.g., QuickBird and IKONOS) and HR (e.g., SPOT 5) satellite imagery has also been extensively used in crop classification studies [8; 9]. VHR offers an excellent target to pixel ratio and allows for the appropriate exploitation of image processing features, such as texture, context, and tone [10].