|Reference : Use of spot/vegetation in different versions of the European crop growth monitoring s...|
|Parts of books : Contribution to collective works|
|Life sciences : Agriculture & agronomy|
|Use of spot/vegetation in different versions of the European crop growth monitoring system.|
|Piccard, I. [ > > ]|
|Eerens, H. [ > > ]|
|Oger, Robert [Université de Liège - ULg > Département des sciences et gestion de l'environnement > Département des sciences et gestion de l'environnement >]|
|Curnel, Y. [ > > ]|
|Tychon, Bernard [Université de Liège - ULg > Département des sciences et gestion de l'environnement > Département des sciences et gestion de l'environnement >]|
|Ozer [ > > ]|
|Van Diepen, K. [ > > ]|
|Proceedings of the 2nd international vegetation user conference, 1998-2004 : 6 years of operational activities|
|Verstraeten, W. W.|
|92 894 9004 7|
|Grand-Duché de Luxembourg|
|[en] remote sensing ; agriculture ; yield forecasting ; global processing|
|[en] The Crop Growth Monitoring System (CGMS) is a GIS-application, developed and operated since 1989 by the MARS-unit of the EU Joint Research Centre. The primary objective is the timely forecasting of the yields of the main crops on the Pan-European continent.To reach this goal, CGMS combines all available (historical and actual) resources: official crop statistics, daily meteorological data, specific crop and soil parameters, the predictions of the (spatialized) crop growth model WOFOST, and the 10-daily composite images of NOAA-AVHRR and SPOT-VEGETATION. In recent years CGMS has been implemented in different regions of the world, also beyond Europe. This paper gives a brief overview of some of these applications, with emphasis on the remote sensing component, especially SPOT-VEGETATION.
In 2000, JRC outsourced the practical operation of CGMS to a consortium composed by Alterra (main tasks, agrometeorological model), MeteoConsult (meteo-provider) and VITO (remote sensing). MARS-STAT delivers the European yield forecasts to the EU statistical office EUROSTAT, in view of the follow-up of market prices and the achievement of the CAP-regulations. MARS-FOOD particularly deals with important food producing areas (Russia, Mercosur) and famine-threatened zones in Africa (IGAD-zone). The long-term goal is to
steadily fill the actual data gaps (crop areas, parameters, meteo,…) so that, in time, the full CGMS (incl. the model) could be applied on these areas (or even globally).
Specific versions of CGMS emerged in different countries (Finland, Spain, Kazakhstan,…), running with more detailed input data. One example is the so-called B-CGMS which has been operating since 1998 on behalf of the Belgian ministry of agriculture, in a collaboration between ULg-Arlon, CRA-Gembloux and VITO. Since 2002, the B-CGMS group publishes monthly bulletins with forecasts on crop yields, areas and productions. The areas are delivered by the IACS (annually updated GIS of all crop parcels, maintained for the EU-CAP).
Together with local partners, the same Belgian group is now implementing CGMS in China’s north-eastern province Heilongjiang, part of former Manchuria and China’s main producer of soybean, maize and singlecropped rice. Special attention is being paid to the steady drying-out of this region, which 50 years ago was mainly covered by wetlands and forests. Climate change and mismanaged paddy irrigation are leading to a dramatic lowering of the water tables.
Technically, this paper will focus on the main deliverables derived from NOAA- AVHRR and SPOT- VEGETATION.
This includes pre/post-processing, extraction of biophysical vegetation state parameters (NDVI, SAVI, fAPAR, Dry Matter Productivity), differences with regard to the historical year (VCI, VPI, etc.), quicklooks, etc.
Of most concern however is the “ unmixing” approach, which attempts to conform the remote sensing data (image format, 1 km-pixels, different crops mixed) to the CGMS-standards (databases with district/crop as spatial/thematic units). If the low/medium resolution sensors (AVHRR, VEGETATION, MODIS, MERIS,..) want to maintain their role in this agricultural domain, this problem has to be solved. Otherwise, the floor is open for new, revolutionary initiatives such as DMC (Disaster Monitoring Constellation: daily global coverage at 32m resolution).
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