Acknowledgements
This article has been provided with the support of Yorgos Efstathiou from e-shape partner NEUROPUBLIC.
Common Agricultural Policy – Driver and Beneficiary of Earth Observation solutions
5.5 min.
The production of food, development of rural communities, and environmentally sustainable farming are all high on the agenda of the European Union (EU). Policies and support mechanisms for agriculture aim, among other, to secure the sufficient and sustainable production of safe food, employment and innovation in the sector, and a positive impact on linked communities and the economy at large.
The EU’s common agricultural policy (CAP) is a partnership between agriculture and society, and between Europe and its farmers. A common policy for all EU countries, it supports the above-mentioned goals through nine objectives:
Since 1962, and throughout a series of reforms, the CAP has not only supported farmers in their efforts to supply EU citizens with good quality and safe food; it has also been guiding the implementation of sustainable agriculture across the EU. One element to achieve the CAP’s objectives are direct payments and subsidies to farmers through paying agencies in the EU Member States (direct payments and rural development making up roughly 80% of the CAP). These paying agencies claim expenditures from the EU budget to be reimbursed by the European Commission (EC) to the EU countries. Management and checking systems are in place to ensure the eligibility of fund applications.
The latest amendment on the CAP regulation, introduced in May 2018, attempts to modernise the implementation of checks for area-based payments and for cross-compliance requirements. This landmark change foresees that modern solutions such as geo-tagged photos, E-GNSS enabled receivers, and data from Copernicus Sentinel satellites are used to carry out checks. One initiative to the CAP modernisation is the project New IACS Vision in Action (NIVA), in which nine paying agencies bundle their efforts for a streamlined approach to an Integrated Administration and Control System (IACS).
Meeting the CAP’s objectives, drives the development of Earth Observation (EO)-based services for agriculture, food security, and environment. Thus, the CAP explicitly encourages farmers to apply precision farming, and Member States to use Big Data and new technologies for monitoring and checks. EO data is already used as evidence when checking area-based CAP payments to farmers. The Sentinels for Common Agricultural Policy (Sen4CAP) project, set up by the European Space Agency (ESA) in collaboration with the European Commission, aims at providing CAP stakeholders such as Paying Agencies with validated algorithms, products, workflows and best practices for agriculture monitoring relevant for the management of the CAP. In that context, e-shape Pilot 1.2 (EU-CAP Support) aims to support farmers in being CAP-compliant and in utilising the data also for optimising the performance of their farms. Similarly, the project “PeRsonalised public sErvices in support of the implementation of the CAP” (RECAP) created a Software-as-a-Service platform to facilitate compliance with the CAP. Such projects, but also contracts with public authorities represent great business opportunities for EO service providers.
To fulfil their duties, paying agencies rely on data and IT systems that enable evaluation checks with that data – one system for farmers making declarations, one system for agencies controlling. Different countries, or even regions, have different approaches for implementing solutions: some develop their own, others may outsource data services (sometimes even the analysis of data) as well as systems and infrastructure to the private sector, which in itself represents business opportunities. The solutions enabling compliance checks need to constantly evolve, e.g. to involve farmers more, increase accuracy of crop detection and variety of crops, etc. This opens up the space for new business, but also new actors, e.g. coming from a machine learning and Artificial Intelligence (AI) background.
Data for CAP monitoring may come from Sentinel-1 and -2 or Landsat (all free). Specific applications or crops and smaller parcels may require higher resolution data provided by commercial providers (e.g. Maxar, Airbus, Planet, etc.). Every paying agency through their contract with European Commission or their national space agencies has access to 3-7 high-resolution images per year. Some paying agencies have contracts with commercial providers themselves. Other agencies have instances in one or more of the Copernicus Data Information Access Services (DIAS) or host their own Cloud platform – the landscape of EO platforms is currently cluttered.
In all cases, the data is most often used for crop classification, i.e. to check whether eligible crops are being grown at the right time of the year. Other aspects include change detection of agricultural activities (e.g. mowing, harvest). Minimum agricultural activity on eligible areas can be verified through e.g. detection of cattle, mowing stripes, or spraying tracks. Also, through geometry checks, which requires high resolution imagery, ineligible features can be detected.
A general trend in requirements and solutions is that for more automation. The classic approach is to manually check every image and mark anomalies. Machine Learning approaches (e.g. Deep Neural Networks) show promising results for automating these steps obtaining information on crop types and agricultural activities. Other means to reduce manual workload are provided by image segmentation software that splits parcels into smaller segments, reducing the amount of non-relevant data to be processed. Agencies require an online platform they can use, need to be able to understand the tools behind, and prefer open source solutions accessible in-house and integrated with their other systems.
Providing agencies with automated solutions is a great opportunity for service providers, and the time is ripe: Currently, Member States have to randomly check 5% of their country’s parcels. Soon, they will be moving to “checks by monitoring”, putting together national-scale monitoring systems, which for some will require significant IT system changes to provide compatibility of data, workplaces, interoperability with dedicated systems etc. The growing amount of data to be processed implies further capacity needs.
Beyond compliance checks, EO can support farmers to optimise production in a more sustainable way: monitoring their crops; analysing soil, climate, and weather conditions; enabling variable rate application of seeds, water, and fertiliser; or evaluating damage for insurance or compensation. e-shape Pilot 1.1 (GEOGLAM), for instance, addresses the processing and analysis of agricultural information from combined sources. Pilot 1.3 (Vegetation-Index Crop-Insurance in Ethiopia) provides a geodata-driven insurance to smallholder farmers. Pilot 1.4 (Agro industry) provides agriculture with services to resist and adapt to climate change.
Overall, modernising the CAP will require more use of new imaging technology, and changing from a traditional rule-based approach to new intelligent Machine Learning solutions. The agencies will have to trust Deep Learning algorithms. Synergies between different satellite data types (i.e. radar and optical) will enable more dense time series. And algorithms are constantly trained to recognise a larger variety of crops and conditions. Developments in agricultural monitoring and enabling technologies such as exemplarily mentioned above will be monitored and presented by the e-shape Market Trends Observatory.
Acknowledgements