The main objective of EO4AGRI is to catalyze the evolution of the European capacity for improving operational agriculture monitoring from local to global levels based on information derived from Copernicus satellite observation data and through exploitation of associated geospatial and socio-economic information services. EO4AGRI assists the implementation of the EU Common Agricultural Policy (CAP) with special attention to the CAP2020 reform, to requirements of Paying Agencies, and for the Integrated Administration and Control System (IACS) processes. EO4AGRI works with farmers, farmer associations and agro-food industry on specifications of data-driven farming services with focus on increasing the utilization of EC investments into Copernicus Data and Information Services (DIAS). EO4AGRI addresses global food security challenges coordinated within the G20 Global Agricultural Monitoring initiative (GEOGLAM) capitalizing on Copernicus Open Data as input to the Famine Early Warning System Network (FEW-NET). EO4AGRI assesses information about land-use and agricultural service needs and offers to financial investors and insurances and the potential added value of fueling those services with Copernicus information. The EO4AGRI team consists of 11 organizations, complementary in their roles and expertise, covering a good part of the value-chain with a significant relevant networking capital as documented in numerous project affiliations and the formal support declarations collected for EO4AGRI. All partners show large records of activities either in Copernicus RTD, governmental functions, or downstream service operations. The Coordinator of EO4AGRI is a major industrial player with proven capacities to lead H2020 projects. The EO4AGRI project methodology is a combination of community building; service gap analysis; technology watch; strategic research agenda design and policy recommendations; dissemination (incl. organization of hackathons).

EIFFEL will offer the EO-based community the ground-breaking capacity of exploiting existing GEOSS and external datasets, with minimal new data collection activities. Added-value services interoperable with GEOSS will be designed, using cognitive search and metadata augmentation tools based on Artificial Intelligence (AI), including Natural Language Processing. These tools will leverage advanced cognitive features to extract meaningful information from and enrich GEOSS metadata. Moreover, novel methods (super resolution, data fusion) for augmenting the spatiotemporal resolution of explored EO data will be proposed, in order to address the needs of the diverse EIFFEL CC adaptation and mitigation applications. The latter will cover: (i) a set of five different GEO Societal Benefit Areas (SBAs), namely in Water and Land Use Management, Sustainable Agriculture, Transport Management, Sustainable Urban Development and Disaster Resilience domains; (ii) various EU geographical and climatic regions, at local, regional, national, cross-border and pan-European scales. Further, the value of using explainable AI techniques for improving the credibility and comprehensiveness of such CC applications, so that they can offer actionable insights to the decision makers, will be showcased. EIFFEL will foster the co-design of CC adaptation policies and mitigation strategies and monitor CC effects in the respective regions. The project, in line with EuroGEO’s emphasis on early engagement with stakeholders and their participation in the application design, has ensured that they are active consortium members. EIFFEL complies with the framework of results-Oriented GEOSS, to improve the delivery of applications tailored to decision making centres and will actively participate in the GEO Work Programme post-2019. Last, it provides tangible proof of the value of GEOSS data for creating CC applications and encourages projects and initiatives to offer their data through the portal.

DIONE proposes a close-to-market (TRL7) area-based direct payments monitoring toolbox that will address the forthcoming Modernised CAP regulation of using automated technologies to ensure more frequent, accurate and inexpensive compliance checks. In particular, DIONE will: (i) Capitalise on recent results of ESA’s SEN4CAP project that showcased the capability of Sentinel data to monitor the crop diversification rules. DIONE shall further integrate generated crop-type maps in a way directly exploitable by the paying agencies; (ii) Include in the analysis the so far neglected EFA types (fallow land of all sizes, buffer strips, hedges, trees), by making use of super-resolution technology that improves the 10-20m Sentinel resolution to an improved resolution range (5-10m). This is enabled through Machine-Learning (ML) based post-processing and data fusion of Copernicus DIAS-sourced data with targeted drone-obtained data. This aims to motivate the use of such EFAs over the –of ambiguous environmental impact- use of productive areas (nitrogen-fixing crops and catch crops). (iii) Complement the use of EO data with a system of reliable, ground-based geo-tagged photos, captured by the farmers that exploits (a) advances that allow for improved positional accuracy, (ii) low-footprint encryption techniques for improved data security and reliability and (iii) image detecting manipulation techniques (image forensics). The system will allow for an improved LC/LU annotation and ensure the process is untampered. (iv) Implement a Green Compliance toolbox, integrated with the paying agencies’ aforementioned tools. This will benefit from (a) low-cost spectral sensors measuring soil quality and assessing the status of land-degradation in the land parcels and (b) an ML-based inferencing system deployed on a larger scale (regional, national) to quantify the levels of some of the monitored parameters and consequently extract tangible environmental performance metrics for an entire region

The discussion on the modernisation of the Common Agricultural Policy (CAP) is in full progress and one element is how the CAP will benefit from and stimulate ongoing digitisation of the agricultural sector. Digitisation accelerates a cost-effective administration of CAP payments, the update of CAP instruments, stimulates data (re) use for monitoring the societal benefits of agriculture towards climate, environment and rural development and thus improves the sustainability and competitiveness of the sector. Administrative bodies from 9 EU Member States join forces to realise a new vision on the Integrated Administration and Control System (IACS) – the instrument for CAP governance – in this project called: “New IACS Vision in Action” (NIVA). The project is built on an iterative work plan. This ensures fast results, built-in flexibility and greater involvement of stakeholders. NIVA strives for maximum impact by involving all EU paying agencies and other relevant actors in the stakeholder board, by reserving a substantial budget for supporting third parties and the set-up of an innovation ecosystem that will continue after the project. NIVA manages cross cutting digital innovations as well as standardization issues in dedicated work packages as defining, accepting and defending common standards is exemplifying the desire for collaboration. The nine prime use cases are demonstrated in three waves, from national to multi-national to pan-European, hence underlining our ambition to make a significant contribution to improved digital competences, awareness and innovation at the European scale. The project’s results are a suite of digital innovations and a roadmap for IACS transformation. The project will speed up innovation, reduce administrative burden, sustain broader and deeper collaboration in an innovation ecosystem and provide methods to establish information flows to improve environmental performance.

Public administrations responsible for the implementation of the Common Agricultural Policy (CAP) need to monitor farmers’ compliance to standards. Monitoring is performed by in-field visits and through remote sensing. Due to the high complexity and diversity of the obligations that need to be monitored, both methods have limitations, and entail a high cost for public administrations. RECAP proposes a methodology for improving the efficiency and transparency of the compliance monitoring procedure through a cloud-based Software as a Service (SaaS) platform which will make use of large volumes of publicly available data provided by satellite remote sensing, and user-generated data provided by farmers through mobile devices (geo-referenced and time-stamped photos). The RECAP platform will extract useful features from Earth Observation open data, correlate them with user-generated and geo-information data available to public organisations, and model this information for enabling the identification of potential breaches of compliance by public authorities and inspectors. RECAP will offer farmers a tool supporting them to comply with regulations imposed by the CAP, providing personalised information for simplifying the interpretation of complex regulations, and early alerts on potential breaches. RECAP will allow agricultural consultants and developers to create add-ons to the main application that extend its functionality and exploit the data collected through an Application Programming Interface (API), and a Software Development Kit (SDK). Consultants will be able to access data available in the platform, subject to security and privacy policies, and to develop their own services within the platform using design tools, libraries, and communication with the database under an open approach. The RECAP services will be tested and validated in an operational environment in 5 countries with the participation of public authorities, farmers, and agricultural consultants.