Agro-environmental monitoring tool: Operationalising agro-climatic and agro-environmental indicators

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NIVA’s agro-environmental monitoring suggests measuring the impact of agricultural practices on the environment through three indicators:

’Carbon storage’ to reflect effects on climate change:

Carbon storage will be estimated with Tier 1, 2 and 3 methodologies. At Tier 1, the indicator on carbon storage can estimate, at parcel scale, a simple CO2 flux by utilising only the Normalised Difference Vegetation Index (NDVI) variable derived and calculated from sentinels. This estimation can be done efficiently only on arable land and for 13 families of crops. Tier 1 has been tested in several zones in France and Spain, in the whole territory of the Netherlands and Denmark. Tiers 2 and 3 will calculate more accurate C budget indicators by adding to the tested Tier 1 methodology meteorological and soil data and other ancillary data from external sources. Tiers 2 and 3 have not been developed yet.

’Risk to nitrate leaching’ to capture effects on water quality:

The index on ‘risk to nitrate leaching’ estimates a Tier 1 indicator from IACS data (information on previous and current crop) and sentinel data (information on catch crops) to account for the mineralisation and N uptake. Tier 2 will build on Tier 1 by utilising climatic data and exact catch crop type from Farm Management Information Systems (FMISs).

’Biodiversity’:

Biodiversity is a challenging area for the development of impact indicators. At Tier 1, the biodiversity indicator reflects the landscape by measuring the proportion of Semi-Natural Habitats (SNH). This measurement is achieved by combining crop diversity, field size, and artificial surfaces in the broader area (landscape). Higher tier methods will add to the proportion of SNH (Tier 1) the type of SNH as woods, hedges, grassland, ponds, and others, possibly data on the use of fertilisers and all that by using external data sources.

The indicators are based on information and data sources derived from:

  • Published scientific methods and former EU projects (e.g., DiverImpact, Sensagri, Sen4CAP)
  • IACS data at the parcel level, including information from the Land Parcel Information System (LPIS) and Geo-Spatial Aid Application (GSAA)
  • Sentinel data images (Copernicus service) based on Sen4Cap software standards
  • Farm Management Information System data (FMIS) whenever this is feasible
  • Other external data sources for soil, the weather, and others.

Each indicator will be computed using at least Tier 1 methods.

Description of the use case
A policy brief that presents the outcomes of a workshop on the development of agro-environmental and agroclimatic indicators for monitoring the impacts of CAP
Relevance for monitoring and evaluation of the CAP

Indicator estimation: This tool allows evaluators to estimate three essential agro-environmental indicators: two at the parcel level and one at the broader landscape level. Each indicator can be estimated at least using Tier 1 methodology. Calculations must use IACS/LPIS data and connect them with Earth Observations and other widely used existing data. This data may include soil data from LUCAS Soil or other soil surveys, meteorological data, fertiliser consumption data, or general statistics data from Eurostat to obtain Tier 2 estimates. The link with Farm Management Information Systems (FMISs) can support higher tier methodology, but this is not always easy and straightforward.

The indicators can contribute to the evaluation of the Green Deal and especially of the Farm-to-Fork and Biodiversity strategies. More specifically, the indicators can support the evaluation of Farm-to-Fork targets related to reducing nutrient losses, the EU’s carbon farming initiative, and the Biodiversity Strategy target of bringing back agricultural areas under high-diversity landscape features. In addition, the carbon storage indicator, mainly when applied to a countrywide scale, can support the estimation of impact indicator I.11 ‘Enhancing carbon sequestration’. Similarly, the risk to nitrate leaching indicator can offer data and supporting evidence to estimate impact indicator I.15 ‘Gross nutrient balance – nitrogen’.

All indicators have been tested in the field, in various physical environments and scales ranging from regional to national. If the methodology remains at Tier 1, access to data is standard, and the methods are well-known. In this case, transferability depends on the successful application of the Artificial Intelligence (AI) and Machine Learning (ML) algorithms and the link of Earth Observations to IACS/LPIS. While applying the indicators’ Tier 1 methodology to the case studies, NIVA has done significant work unifying the list of crops. NIVA also gained much experience in connecting the IACS with FMISs and recorded a range of problems that, for the time being, prohibit the widespread use of FMISs. Some of the problems concerned with interoperability of the numerous commercial FMISs, a bias in the adoption of FMISs by larger and more entrepreneurial farmers and various other issues related to accuracy and data quality.

The evaluators who are interested in NIVA tools should consult the Action Plan for the uptake of NIVA tools:

https://www.niva4cap.eu/wp-content/uploads/2021/08/D5.3.-Action-Plan-for-the-uptake-of-NIVA-tool-D1.0.pdf

Last modification date: 
08/12/2021