Title: The Use of Remote Sensing Within the Mars Crop Yield Monitoring System of the European Commission
Authors: BARUTH BETTINAROYER ANTOINEKLISCH ANJAGENOVESE Giampiero
Citation: Proceedings of the 21st Congress of the International Society for Photogrammetry and Remote Sensing vol. 27 Part B8 Commission VIII p. 935-940
Publisher: International Society for Photogrammetry and Remote Sensing - ISPRS
Publication Year: 2008
JRC N°: JRC46248
URI: http://www.isprs2008-beijing.org/pdf/0610-T2-Program.pdf
http://publications.jrc.ec.europa.eu/repository/handle/JRC46248
Type: Contributions to Conferences
Abstract: The objective of the Mars Crop Yield Forecasting Systems (MCYFS) is to provide precise, scientific, traceable independent and timely forecasts for the main crops yields at EU level. The forecasts and analysis are used since 2001 as a benchmark by analysts from DG ¿ Agriculture and Rural Development in charge of food balance estimates. The system is supported by the use of Remote Sensing data, namely SPOT-VEGETATION, NOAA-AVHRR, MSG-SEVIRI and MODIS TERRA and in the future METOP AVHRR too. So a broad spectrum from low to medium resolution data at pan-European level is covered and historical time series go back to 1981 for NOAA and 1998 for SPOT VEGETATION. In order to work with the data operationally, processing chains have been set-up to make the data consistent with our requirements concerning near real time delivery (3 days), spatial coverage (pan-Europe), projection and ten day time steps. Moreover tailored indicators like NDVI, fAPAR and DMP are derived. In case of available time-series, difference values of the indicators (e.g. relative or absolute differences) and frequency analysis of the indicators (e.g. position in historical range or distribution) are calculated. The data is explored at full resolution or unmixed related to landcover types and aggregated at administrative NUTS 2 level (profile analysis of time series). Special tools to inspect and distribute the data to external users have been developed as well. Furthermore, it is the objective to develop a strategy for an optimal use of the different sensors and thus derived indicators at different aggregation levels for the ingestion into the MCYFS. As a first step smoothing algorithms have to be applied to the time series to diminish noise effects and to retrieve continuous information. Thus, an algorithm based on Swets et al. (1999) is employed. Thereafter, so-called Chronos Key Indicators are derived from the smoothed time-series. Currently, a study is carried out to establish the link between these indicators and (1) state variables of the crop growth simulation (e.g., development stages), and (2) the forecasted yield/production.
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