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Stimulating Innovation for Global Monitoring of Agriculture and its Impact on the Environment in support of GEOGLAM

The G20 launched in June 2011 the “Global Agricultural Geo-Monitoring” (GEOGLAM) and the Agricultural Market Information System (AMIS) initiatives. The main objective of GEOGLAM is to improve crop forecasts to increase transparency on agricultural production through the creation of an operational global agricultural monitoring “system of systems” based on earth observation and in situ data.  SIGMA is part of Europe’s contribution to GEOGLAM.  

Stimulating Innovation for Global Monitoring of Agriculture and its Impact on the Environment in support of GEOGLAM

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SIGMA is actively networking expert organizations world-wide, in a common effort to enhance current remote sensing based agricultural monitoring techniques. Its aim is to develop innovative methods and indicators to monitor and assess progress towards “sustainable agriculture”, focussed on the assessment of longer term impact of agricultural dynamics on the environment and vice versa.

SIGMA implements activities in Europe, Russia, Ukraine, China, Vietnam, Africa, Argentina and Brazil and is financed through the EC’s Research Framework programme (FP7).
In order to design and develop methods to assess/monitor (longer term) impacts of agricultural dynamics, as a contribution to GEOGLAM, it is important to thoroughly understand the currently used practises at a global scale. The GEO Agriculture Community of Practise describes a number of national and international agricultural monitoring systems, such as EC JRC/MARS (Monitoring Agricultural Resources), FAO/GIEWS (Global Information and Early Warning System), China’s CropWatch, and the USDA FAS (Foreign Agricultural Service). In generic terms, most of these systems have a combined approach using time series of satellite and meteorological data, a “static” crop map mask, agro-meteorological models and a statistical tool box, resulting in within-season crop yield estimates, area estimates and production forecasts. As a consequence, little attention is given to pluri-annual changes such as shifts in cultivation practises (intensification), expansion or abandonment of agricultural land (expansion or shrinking). Both intensification and expansion of agricultural land  are the primary focus of SIGMA.

As such, SIGMA has three main objectives:

  • Identify, map and assess agriculture and crop land changes, globally, regionally and locally
  • Identify, map and assess changes in agricultural production levels and shifts in cultivation practises
  • Identify, map and analyze environmental impacts of Agriculture and cultivation practices
SIGMA undertakes activities at global, regional and local scale, the main challenge being to thoroughly understand the dynamics, interactions and validity of the developed methods at the various scales. Global and regional data sets (based on low resolution data and models) are used to analyze crop land change and some well-known land degradation issues. This global approach is then ‘verified’ at regional level and number of sites at specific locations, providing insight into the validity of such global and regional approaches. Confronting information at the various scales will generates a methodological dynamic whereby, as a result, significant improvements can be expected.

 

Program: FP 7 | Scientific field: Agricultural Sciences | Related Topics: Research and innovation community | Geographical focus: Russia, Ukraine