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Recherche et applications > Banque de données projets > Banque de données projets FEDRA

Global Agricultural Monitoring systems by integration of earth observation and modelling techniques (GLOBAM)

Projet de recherche SR/00/101 (Action de recherche SR)


Personnes :

  • Prof. dr.  DEFOURNY Pierre - Université Catholique de Louvain (UCL)
    Coordinateur du projet
    Partenaire financé belge
    Durée: 1/12/2006-30/11/2010
  • Dr.  MEULENBERGHS Françoise - Institut Royal Météorologique de Belgique (IRM)
    Partenaire financé belge
    Durée: 1/12/2006-30/11/2010
  • Prof. dr.  TYCHON Bernard - Université de Liège (ULG)
    Partenaire financé belge
    Durée: 1/12/2006-30/11/2010
  • Dr.  PICCARD Isabelle - Vlaamse Instelling voor Technologisch Onderzoek (VITO)
    Partenaire financé belge
    Durée: 1/12/2006-30/11/2010
  • Dr.  DE WIT Allard - Wageningen Universiteit en Researchcentrum (WUR)
    Partenaire financé étranger
    Durée: 1/12/2006-30/11/2010
  • Dr.  LEO Olivier - European Commission (EU)
    Partenaire non financé étranger
    Durée: 1/12/2006-30/11/2010

Description :

Context and objectives

Nowadays, food security and crop production variability become a major concern. Moreover, in spite of major technological and methodological EO improvements observed since the late 1990’s, very little change has been observed in the operational systems. A major gap exists between the remote sensing operationally used and the current scientific state of the art in EO crop monitoring. There is a lack of relevant field data over large areas, and these data are very much needed to gain a better understanding of potential improvements of the operational systems.

The overall objective of the project is to fill the gap between the current state of the art for local crop monitoring and the wide-scale operational system requirement. The research will develop an integrated approach providing area and crop production estimate by combining satellite remote sensing and crop modelling in a quantitative and physically-based approach. The performances of the proposed approach will be assessed for various agro-ecological environments thanks to extensive ground truthing and benchmarked with regards to existing operational systems. The robustness of the performances will be specifically investigated as it becomes more and more critical in a context of increasing inter-annual variability of meteorological conditions and of rapid change in emerging countries. This is also the reason why a conceptual research effort will then attempt to develop more robust indicators of the crop production.


Methodology

The overall research strategy is to adapt, integrate and test advanced methods for the different steps of the proposed crop monitoring system, i.e. croplands mapping and crop area estimation, EO monitoring, crop modelling and, assimilation of the EO-derived information. These developments will be completed on 3 large sites of 300 x 300 km distributed in Northern Europe, Africa and Asia. In each site, a calibration area of 60 x 60 km (typically a SPOT scene) will serve to tune the classification process, the retrieval algorithm and the crop model while their respective performances will be assessed over the 300 x 300 km site thanks to large validation survey. The overall performances of the system will be then compared to existing operational systems and, finally alternative robust indicators will be designed and tested.

The research is organised in three phases within the four years. The first one (2007-2008) will address the development and integration issues for the 3 sites in parallel with a field campaign during the first growing season to provide field and EO data. The second one(2009) will comprise an extrapolation and methods validation to 5 other sites (3 + 2), and the third one (2010) an interannual comparison.


Results expected

The main outcome of the research is a pre-operational approach to estimate crop type area based on optical and SAR HiRes data processing over large areas and to better monitor the crop development thanks to a quantitative coupling of EO-derived variables and different crop models calibrated to regional conditions. Thanks to the complementarities between the various components and to the recalibration/assimilation techniques involved, this approach, as compared with currently existing methods, should be more efficient, more general and, last but not least, more robust with regard to unusual growing conditions. New crop indicators should also be proved to be more robust than classical NDVI profile anomalies or absolute production estimate.

Besides the knowledge accumulation on the three core sites and the estimate to be delivered, the scientific project outcomes concern mainly methodological progresses with regards to the state of the art in the field, in particular when considering large scale experiment. Finally, thanks to the openings to key international players in the field, the Belgian scientific expertise in the field will be enhanced and its networking reinforced.


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