This paper provides a short analysis on how and in what extend the satellite-based technologies and smart farming systems can act as new sources of information towards the realization of future CAP objectives. The report focuses on the integration of these new technologies in support of advanced decision making for the regional/national Integrated Administration and
There is currently an EU wide effort aiming to achieve environmental protection and optimisation
of agricultural practices in a combined manner. From a policy perspective, these interrelated objectives
are mainly pursued through the introduction of regulations like the Common Agricultural Policy (CAP).
One of the key parameters of CAP is the support of farmers income through a system of agricultural
subsidies and programmes covering farming, environmental measures and rural development. The main
building block of the management of payments system is the Integrated Administration and Control
System (IACS) [
The new CAP, which is due to begin in 2023, aims to be the key instrument for securing the future
of agriculture and forestry, as well as achieving the objectives of the European Green Deal paving the
way for a fairer, greener and more performance-based policy implementation. [
Even since 2015, the EU has set the objective of integrating “farm level data with micro-data
transmission, based on a modular approach with core variables, modules and satellites” [
Management Information Systems (FMIS) that are increasingly being deployed by service providers.
2022 Copyright for this paper by its authors.
This paper provides the key outcomes and future directions towards the further interconnection of
regional/national IACS systems with innovative information sources, based on the analysis conducted
in the context of H2020 NIVA project [
The CAP monitoring through EO data has been made possible by the Sentinel missions that provide
free and open high-resolution satellite datasets (spatial resolution of 10m) with frequent visits: the time
series of Sentinel or other satellite images are a powerful mean to check farmer’s declarations. However,
accessing and pre-processing these big volumes of images in order to get ARD (Analysis Ready Data)
is a complex task, raising many issues concerning computing performance, multi-temporal and
multilevel analysis [
Sentinel-2 provides optical images easy to be interpreted with valuable information and the
preprocessed products are available as open data. They are the first candidates for crop monitoring.
However, they suffer from the cloud contamination losing land surface information, creating gaps on
the time-series. That depends on geographic location and it is more disturbing in northern or
mountainous areas.
Even for the “standardised” product L2A, there are various options for atmospheric correction
according to the way to access images: for instance, the Copernicus Open Access Hub [
Sentinel-1 provides radar images that are powerful but complex products that are more difficult to
be interpreted. The ARD products are not available as open data from the Copernicus hub. However,
the ESA provides the SNAP [
The resolution of S-2 and S-1 images is not sufficient to monitor all parcels as issues may occur for
small parcels and also for parcels of specific shape (such as narrow parcels). Using High High
Resolution (HHR) images such as Planet and SPOT-6/7 or even VHR images such as WorldView or
Pleiades have been mentioned as potential solutions. [
The Copernicus Hub offers free access to Sentinel images but in practice, this access is not so easy due to technical restrictions; the storage and handling of these big volumes of data require significant IT infrastructure investment as well as specialized employees that increase the overall cost. Extracting the information at pixel level means that users will have to get the entire image and will have to deal with huge volumes of data. Until now, this is the main available solution on the market. The investment on pre-processing and IT infrastructure may be done in the Paying Agency itself (through buying ICT material and training staff) or it may be outsourced (through buying predefined services and computation power, such as “Copernicus Data and Information Access Service” (DIAS) or other cloud infrastructures). It is mainly between being straightforward (lots of preliminary steps already done before PA accesses the image data) and being flexible (doing things yourself require more expertise but enable to decide on each step of the process).
The concept of “Farm Management Information Systems” (FMIS) is an umbrella term that refers to
a set of computer-based information systems operating at a farm level which are able to receive data
streams, store and process them and provide output useful to the various stakeholders (individual
farmers, farmers associations, advisors, etc.). FMISs are usually offering, the functionality related with
the digital recording of agricultural activities (also called “Farmer’s Calendar”, “Farm Log”, “Field
book”) that demonstrates the potential to contain various relevant to CAP monitoring information (e.g.
use of pesticides, irrigation, fertilizers, harvested yields). There are currently hundreds of FMISs
available on the market that can support decision making by finding the best practices for farm
management [
“Digital field book” - usually as part of a FMIS- is potentially one of the most valuable information sources for IACS. Unfortunately, FMIS are not yet used by a wide range of farmers, the situation varying a lot depending on countries and regions. However, the use of digital means for recording applied practices is expected to be continuously adopted by more farmers during the next years due to introduced legislation but also because it is more efficient for the everyday activities of the farmers. Typically, recordings of pesticides applications are more mature to be captured and shared with various administrative entities. Similar policies and tools are currently under development for the collection of data on utilized irrigation water and soil nutrition status. 3.2.
The semantics utilized for recording the various information items maintained by FMISs are still heterogeneous. However, there are various efforts towards harmonization based on existing well-known approaches especially with code lists (e.g. Agrovoc taxonomy, EPPO glossary, code lists for agrochemicals). NIVA proposed the use of the eCrop standard [12] as a common data model for data exchange between FMIS and IACS and proposes the introduction of “Farm Registry” as a component of the new IACS with the role of recording in a continuous way the information provided (Figure 3).
Non interoperable interactions
Semantic Interoperability based on Standards FMIS (A) FMIS (B) FMIS (C) FMIS (D)
IACS (1) IACS (2) IACS (3)
FMIS (A) FMIS (B) FMIS (C) FMIS (D)
Standards (e.g. eCrop)
IACS Farm Registry
Although in some cases record keeping in “Field Book” is even mandatory the recording of
information is still fragmented and prone to intentional or unintentional errors. Data related with
cultivation practices are not reliable given that it is manually imported to FMISs. An approach to
mitigate inconsistency of manually imported records is to escort them with data derived from additional
sources (e.g. farm machinery, geotagged photos, environmental sensors and hard copies of invoices).
Interesting approaches have been recorded including the “building of trust with farmers” [13], the
combined use of FMIS data with “on the spot checks” [
The majority of the FMISs are not considering -yet- the public administrative agencies (e.g. Paying
Agencies) as potential 3rd party entities that are useful to interact with, either to provide data or to
retrieve data. This means that currently there are few or even no data exchange mechanisms by FMISs
explicitly established for connecting with IACS systems. Paying Agencies consider that change in
legislation is required to enable data exchange from FMIS to IACS. [
This paper presents the key findings on the use of EO and FMIS in support of future IACS operation and future CAP monitoring and evaluation based on the analysis of the NIVA project. The overall outcomes show that there is high potential for further assisting IACS operations with innovative digital technologies but legal, technical and organizational challenges need to be addressed.
Parts of the work presented here were funded by the European Commission within the H2020 Programme project “NIVA-New IACS Vision In Action” under grant agreement no. 842009.