Identification of organic farming practices

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This product of ENVISION will deliver a fully automated organic crop identification. It will identify whether a particular crop type declared as organic is classified as such based on a traffic light system. Plants cultivated under organic and conventional farming practices present biological, chemical and physical differences. The differences can be detected by satellite imagery, especially during the vegetative and reproductive growth stages. The logic behind the service is to identify distinct patterns characterising the growth and evolution of organic and conventional crops during the growing season through high-resolution optical and radar satellite images depicting the phenological status of the cultivated parcels.

The tool will enable the continuous, all-year-round and territory-wide monitoring of organic farming and crops in general, including verifying actual cropped area, the presence of crops, the crop’s performance, and the crop’s anticipated yield. The product will build a traffic light system with the cultivation method classification at the parcel level. The tool will identify the cultivation practices by the end of the growing season, and the traffic light system will enable a smart sampling technique for the inspections. Each parcel will be characterised by its classification decision's confidence (red, green, blue).

The architecture and the service report of the product
Relevance for monitoring and evaluation of the CAP

The identification of the organic farming practices tool to be produced by ENVISION aims at compliance checks. They provide alerts at various time points in the growing season and support Certification Bodies (CBs) in pursuing smart sampling.

Evaluation can re-use the data provided by the tool to cross-validate the data recorded by CBs and surveys, e.g., the FSS, concerning the agricultural area under organic farming. This is context indicator C.33 and a primary Farm-to-Fork policy target. Also, since the tool provides the information annually and timely, it will be a good source of updated data for ongoing or intermediate evaluations. Since the tool can provide estimates of anticipated yields, it may contribute to the estimation of the new PMEF impact indicator I.29 ‘Responding to consumer demand for quality food: Value of production under EU quality schemes and organics’. The statistical authority of the Member State may derive the average producer and consumer prices for organic products needed for an approximation of the value of organic production.  

In addition, data from the tool in association with data from CBs and data from IACS can support the evaluation of the effects of CAP on the adoption of organic farming by facilitating the construction of beneficiaries and non-beneficiaries samples of farms.

The tool's adoption requires access to EO, the adaptation and application of the algorithms recognising the characteristics of organic practices and their training on specific crop types of the region or the Member State. It is assumed that the IT infrastructure is adequate and that the evaluator has the skills to use the data. In general, when using EO, several conditions may limit their utility and functionality. For this tool, the most critical limitation is the extent of inconclusive parcels, i.e. parcels with a blue traffic light. Inconclusive parcels may be due to specific EO factors such as cloudiness or the prevalence of small parcels and also may be due to difficulties in producing the algorithms to train and forecast organic practices.

When fully operational, the ENVISION platform will be open-source. However, access to the tool will be given primarily to the partners and selected customers identified by the project. Interested stakeholders and prospective users should contact the project holder.

Last modification date: 
10/12/2021