Crop type map

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This Sentinel-based Earth Observation (EO) product is a thematic map that differentiates the types of crops cultivated in an area or country. The map is provided as a shapefile. Its level of detail regarding the number and variety of crop types depends on the country and the purpose of its use (e.g. for monitoring, detecting compliance, smart sampling). The tool is designed to assess compliance with the crop diversification action of greening, defined in the 2014-2020 CAP programming period. The new CAP green architecture incorporates all greening rules under a list of potential agricultural practices that eco-schemes could support. For this reason, the product will be beneficial in the future. 

Various supporting tools to manage data, user manuals and learning material accompany the tool.

Relevance for monitoring and evaluation of the CAP

The project developed the cultivated crop type maps and other EO products to assess compliance and support the monitoring of crop diversification measures by mapping the number of crops or the percentage distribution of crops to be compliant with regulation thresholds at the farm level. The following link provides an example of the use of a cultivated crop type map in crop diversification compliance:

http://esa-sen4cap.org/content/crop-diversification

Evaluators can re-use the data provided by crop type maps to serve many purposes.

First, these data can be used, together with other data sources and other EO tools, in estimating environmental indicators. For example, an evaluator can estimate irrigation water needs using crop type maps, soil maps, meteorological data, and agronomic information. The estimated irrigation water needs is a proxy for the ‘water use in agriculture’ impact indicator.

Second, crop type maps can evaluate the effects of agricultural policy measures on environmental indicators. For example, an evaluator can use IACS to get information on beneficiaries and non-beneficiaries of measures to reduce water consumption and compare their potential irrigation water needs.

Third, crop type maps are data sources that can cross-validate and triangulate information received from other sources. For example, a crop type map can cross-validate information related to policy effects on crop allocation and its consequent impacts on environmental indicators.

The examples above concern water but can be used for other indicators where prior knowledge of the grown crop is essential. For example, crop type maps can contribute, together with other data, to estimate indicators such as the potential nutrient use, the GHG emissions from managed soils, the soil erosion and soil organic matter, crop diversity, and others that depend on the type of soil cover.

The cultivated crop type map is also a prerequisite to a claimless system that supports the pre-fill of aid declarations. However, this is a long-term goal. The pre-fill stage is critical because it may lead to a higher level of automated monitoring and potentially evaluation data. The areas mentioned above of cultivated crop type mapping are not exclusive.

The tool developed algorithms and processes that allow interested stakeholders to apply it in their regions or the Member States. However, the tool's adoption requires adaptation and application of the algorithms and training to recognize the crop types of the region or the Member State. Adopting the tool assumes that the IT infrastructure is adequate and that the evaluator can use the data. The computing system’s specifications are detailed at:

http://esa-sen4cap.org/content/download-package-description

Downloading the package is open to anyone and free of charge. The tool will require a period of testing and calibration before it can be functional.

In general, several conditions may limit the utility and functionality of EO.  The most critical limitation is the extent of inconclusive parcels, i.e. parcels with no definite crop identification. Inconclusive parcels may be due to specific EO factors such as cloudiness or the prevalence of small parcels, or difficulties in producing the algorithms to train and forecast crop type. Another difficulty may be related to the effort and time needed to link the crop type maps with the LPIS and IACS.

Last modification date: 
08/12/2021