In This Space
Operational crop yield estimates are multiplied by the cultivated area, providing the crop production estimate at national/regional level. This service uses medium resolution optical satellite data. Agricultural yields are traditionally estimated using Crop Growth Models or Agro-Meteorological Models (AMM) with different levels of complexity, using several data sources. Today, these crop growth models can be improved and also simplified by using EO data that can be input to various stages of the modeling process (parameters, input or driving variable).
Yield values for each crop are provided at sub-national level and then aggregated at country level, either post-harvest or a forecast during the growing season.
The model makes use of several input variables (e.g. phenological, meteorological), not all derived from EO sources. Availability of local data might differ among countries. Similarly to the Early Warning service, another constraint is associated, in some countries, with reliability of historical yield values provided by public authorities in charge of collecting such data. Such yield values are in fact used to calibrate the service.
Extract of MARS bulletin Vol 20 No 9 (European Union 2012). A pan-European crop monitoring and yield forecasting service based on satellite observations.
Relative yield forecast for millet in Senegal. Credits: University of Liége
Transparent and homogeneous data on agricultural production and estimates of agricultural output growth at country level are essential inputs to National Agricultural Statistics and Crop and Food Security Assessment Missions by the international donor community. Timely forecasted yield values are one of the key variables in early warning for food security. Moreover, they can assist agricultural subsidies control.
Yield forecast cost for 2–3 main crops over a 100.000 km² area ranges between 70 and 100 kEuro.
ESA 2013, Earth Observation for Green Growth: An overview of European and Canadian Industrial Capability
|crop health (disease and stress)|
|crop acreage and yield harvest (inventories / statistics)|
crop types (extent, growth, health, stress)
|Application: crop yields|
crop area estimates
agriculture sustainable management
Studying crops, from outer space
The work is based on a breakthrough in the capacity to use satellite technology to measure light that is emitted by plant leaves as a byproduct of photosynthesis.
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