Table 1 Overview of NIVA progress on main challenges


Baseline (project start) situation

NIVA achievements up to date

Absorbing innovations to simplify the governance 

  • Innovations implemented separately in the 41 different IACS systems in Europe 

  • Only 2 to 3 open source solutions covering small parts of IACS systems 

  • More than 30 components have been developed and are being tested in cross-boundary collaboration 

  • Working modes to learn from each other in an active way and start relying on developments implemented in different PA systems

  • Methodologies for Multi-Actor development and innovation deployment in IACS specified 

Reducing socio-economic and administrative burden to farmers 

  • Digital innovations offer potential to reduce the burdens to farmers and PA’s

  • Digital innovation being tested in some research projects 

  • Different aspects of implementing digital solutions have been aligned through an ‘As-is’ analysis 

  • Wider adoption of research products in innovations and field testing ongoing 

  • Pilots being tested specifically focused on lowering administrative burden through technology 

Reducing the gap between IACS data use and potential broader uses 

  • IACS derived data are shared in some member states on an ‘As-is’ basis 

  • Lack of standardization across claim years and common lists of relevant attributes (e.g. parcels, crops, vegetation types) 

  • Operational testing of IACS data use in pilots for other purposes

  • Standardization issues in IACS highlighted and recommendations provided in a stakeholder oriented way 


Table 2 Overview of NIVA progress on main objectives


Baseline (project start) situation

NIVA achievements up to date

Integrate and reuse IACS evolutions based on open standards and common services 

  • Lack of standardisation across IACS systems 

  • Largely independent development within MS borders 

  • Raised awareness on need and pressure points for harmonisation and shared services 

  • IACS evolution based on components developed in different trials and experiences with testing 

  • Joint learning on potential IACS evolution through digital innovations through cross-collaboration 

Build on farmers’ acceptance of the Smart Monitoring methodology 

  • Testing panels in different Member states 

  • Demands in new CAP for more monitoring data raising challenges with farmers 

  • Methodologies for joint development in a co-design and multi-actor approach 

  • Active participation of farmer and farmer representatives in developing new monitoring approaches 

  • Active participation of farmers in NIVA events  

Reducing the gap between IACS data use and potential broader uses** 

  • IACS derived data are shared in some member states on an ‘As-is’ basis 

  • lack of standardisation across years and common issues 

  • Operational testing of IACS data use in pilots for other purposes

  • Standardisation issues in IACS highlighted and recommendations provided in a stakeholder oriented way

Create a permanent exchange platform for discussion and exchange 

  • Knowledge flow largely passive through presentation sessions at annual events 

  • EC DG JRC as a knowledge partner for both EC services and MS PAs 

  • Joint collaboration and working modes between MS on diverse aspects of IACS systems 

  • NIVA providing knowledge products and briefs complementary to EC DG JRC 

  • Increasing participation across stakeholder groups in NIVA stakeholder events


Table 3 Main innovations as achieved in the Large Scale Pilots

Use Case number

Use case title

Building on

Main Innovations

Main challenges


Earth Observation Monitoring and Traffic Lights

EO Processing chain  of SEN4CAP for  the AMS, Open EO

Expanding the coverage of SEN4CAP crop/permanent pasture classifiers, also extending to smaller sized parcels

Integrating EO processing chain into PA processes for eligibility at the parcel level

Limited reusability of SEN4CAP, not ready to be integrated in an IACS system

Improve marker uncertainty to reduce uncertain/yellow

cases, also dealing with Sentinel limitations and need to add high-high resolution for specific cases

Customizing the system for specifics of other MS


Agri-environmental monitoring

SEN4CAP for EO processing, scientific definitions of indicators and dedicated models

Operationalizing indicator calculations addressing 3 CAP objectives: Climate change, Environmental care, landscape and biodiversity

More advanced indicator calculations require multiple data sources (incl. FMIS, soil samples, etc)

Eligibility criteria for eco-schemes not fully clear yet


Farmer Performance

FMIS data and E-Crop exchange standard (FMIS <–> IACS)

Automated data exchange of farm level relevant data between FMIS and IACS systems

Assessment of farmer performance, based on integration of FMIS, IACS, potentially other data

Every FMIS is different, lack standardization=> difficult to provide (easily) reusable tools

Authentication and agreement by farmers


Prefilled application, GSAA/Land link

SEN4CAP and UC1a EO processing chains  /traffic lights

Automated tools for data harvesting from external registers in case of low/unknown system integration levels

-early crop prediction requires investment from PA (training data from the fields)

– sufficient quality of parcel delineation

–  external registers may be very different depending on countries.


Farm Registry

-New policies on agriculture (new CAP)

-Commission strategies 2030 (F2F and SB)

-Seamless claim

-Reference Data Model

– Common definitions and common code lists

– Basis for a crossborder Farm Registry

– Provide comparable data form different PA’s in order to exchange information and to obtain statistics and indicators

Situation per Member state is different, big standardization challenge

Part of the data model is dependent on yet unknown implementation of the new CAP

Contents of the data model go beyond IACS data

Authentication and agreement by farmers


Geotagged photos

GSAA app for positioning

Farmer acceptance of geo-tagged photo app, integration with PA systems

Many different Mobile phones, many options for mistakes by farmers

Other geotagged applications already in the market => need to prove added value of the NIVA one


Machine data in Geo-spatial ‘on-line’ aid application GSAA as added value data

E-Crop exchange standard, and AgGateway, and IsoXML

absorption/acceptance of machinery-borne data in PA systems

Alternative evidence in case of yellow light

Many different farm machines, lack of standardization, many data links

Given eCrop complexity and flexible standard => need of adapted profiles according required data.

Need to convince machine data suppliers to adopt  standards tested and recommended by UC4B.


Land Parcel Identification System LPIS update & change detection

Already running LPIS update systems

Automate detection for objects (EFA, LF, buildings) and update of eligible parcel now requiring manual work

Machine and/or deep learning techniques

High costs and management requirements of orthophotos

Some objects cannot be automated (e.g. difference between high grass and maize)


Scheme Eligibility and Payment eligibility: Click & Pay

Operationalisation of the principle of automated payment

Use of smart contracts, integrating downstream components 

Simulation of farm typology and entitlements

All downstream processes are operational

Skills of the farmers in understanding the process

Table 4 NIVA links to other projects and initiatives

Project or initiative

Use in NIVA

SEN4CAP, ESA project on Remote Sensing processing chain for the CAP

  • SEN4CAP tools are used in UC1A, 1B and 2 and further improved and validated in operational systems

  • NIVA highlighted the urgent need for technical documentation and source code documentation and training of such systsems

EGNSS4CAP: GSAA app for positioning

  • NIVA embedded these functionalities in its Geotagged Photo app, further expanding them

H2020 OpenEO: an open source collection of tools for EO data processing

  • NIVA is tailoring this for CAP applications, combining it with SEN4CAP processing workflows

CEF components, DG-Connect/DG-DIGIT components and protocols for common definitions

  • CEF components are being tested in NIVA UC3

  • CEF components further developed as part of common components in WP4

H2020 IoF2020, large scale pilots on IoT devices

  • NIVA participation in workshops around semantic interoperability of systems

H2020 OpenIACS, using LinkedOpenData and CEF components for IACS data

  • NIVA provides recommendations and guidelines on standardization issues, complementary to OpenIACS technical solutions

H2020 MEF4CAP, on evaluation frameworks for the CAP

  • Developing joint strategies for stakeholder engagement

Learning Network of directors of PA’s

  • Validation in larger group of Paying Agencies, also dissemination


  • Collaborated stakeholder forum meetings, focussing on knowledge exchange

  • Useful in approaching space industry and agri-businesses.


  • Dissemination to farming sector


  • Monitoring of environmental practices for sustainable agriculture supported by EO