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This document serves as the Product User Guide for the crop productivity indicators based on observations developed as part of the C3S Global Agriculture contract for the Sectoral Information Systems (SIS) in Copernicus Climate Change Service. More information about the project can be found at https://climate.copernicus.eu/globalagricultureglobal-agriculture-project
Executive summary
The EO-based crop productivity indicators provide insight in the productivity and yield of the four main crops (wheat, maize, soybean, rice) and main production regions at a global scale over the period 2000-2018. The algorithm combines earth observation data of plant light interception with a simple crop model that converts intercepted light into crop biomass and uses a phenological model to determine the cropping season length.
The product is provided at a 0.1x0.1 degree resolution and can be used to analyse the effect of climate variability on crop yields at regional scale. The product is not suitable for field scale analysis and is therefore only provide at the 0.1 degree aggregated level. The data product contains three main variables:
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Table 1: Overview of the crop productivity indicators generated in C3S Global Agriculture
Acronym | Description | Units |
DVS | Crop phenological stage: 0 at emergence, 1.0 at flowering, 2.0 at crop maturity | - |
TAGP | Total above-ground production (dry matter) | Kg/ha |
TWSO | Total weight storage organs (dry matter), e.g. grains or pods | Kg/ha |
Input data required to generate the product
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- The basic satellite input data has a spatial resolution of 1 km. This means that only agricultural areas with cropping patterns that contain a limited number of dominant crops are included. For example, most of the agricultural areas in Africa are excluded because the cropping patterns in areas with smallholder farming cannot be resolved at a 1km spatial
- The simulation model does not directly include crop water limitations in the Currently, water limitations are expressed through a decrease in crop light interception as observed by the satellite (basically the leaves of the crop are dying). This implies that long term drought effects are reflected in the product but short term droughts will not be properly accounted for. In a next version of the product a crop water balance may be integrated that accounts for this kind of effects.
- The earth observation based data on plant light interception are aggregated based on a crop mask at 1km level. This crop dominance mask is a static product, although it is generally known that cropping areas change or expand. Also, the crop mask has a limited accuracy. These problems are most likely to occur in regions with complex terrain with landscape mosaics of mixed agriculture and natural vegetation. In such cases, for example, satellite pixels with evergreen forest may have been misclassified as rice leading to unrealistic simulation
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This document has been produced in the context of the Copernicus Climate Change Service (C3S). The activities leading to these results have been contracted by the European Centre for Medium-Range Weather Forecasts, operator of C3S on behalf of the European Union (Delegation agreement Agreement signed on 11/11/2014 and Contribution Agreement signed on 22/07/2021). All information in this document is provided "as is" and no guarantee or warranty is given that the information is fit for any particular purpose. The users thereof use the information at their sole risk and liability. For the avoidance of all doubt , the European Commission and the European Centre for Medium - Range Weather Forecasts have no liability in respect of this document, which is merely representing the author's view. |
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