ORBi: Eerens Herman - Use of medium-resolution imagery in the Belgian crop growth monitoring system (B-CGMS).

Reference : Use of medium-resolution imagery in the Belgian crop growth monitoring system (B-CGMS).


	Document type :	Scientific congresses and symposiums : Paper published in a book
	Discipline(s) :	Life sciences : Agriculture & agronomy
	To cite this reference:	http://hdl.handle.net/2268/94321

Title :	Use of medium-resolution imagery in the Belgian crop growth monitoring system (B-CGMS).
Language :	English
Author, co-author :	Eerens, Herman [ > > ]
	Wouters, Katy [ > > ]
	Dehem, Didier [ > > ]
	Tychon, Bernard [Université de Liège - ULg > Département des sciences et gestion de l'environnement > Département des sciences et gestion de l'environnement >]
	Buffet, D. [ > > ]
	Oger, Robert [Université de Liège - ULg > Département des sciences et gestion de l'environnement > Département des sciences et gestion de l'environnement >]
Publication date :	2000
Main document title :	Proceedings of Vegetation 2000 : 2 years of operation to prepare the future, Lake Maggiore - Italy - 3-6 April 2000
Editor :	Saint, Gilbert
Publisher :	Joint research Centre
Pages :	361-366
Audience :	International
City :	Ispra
Country :	Italy
Event name :	Vegetation 2000 2 years of operation to prepare the future.
Event date :	du 3 avril 2000 au 6 avril 2000
Event place (city) :	Lake Maggiore
Event country :	Italy
Keywords :	[en] B-CGMS ; SPOT-VEGETATION ; fAPAR ; Crop yield forecast
Abstract :	[en] The Belgian Crop Growth Monitoring System (B-CGMS) uses the 1km²-resolution imagery of NOAA-AVHRR and SPOT-VEGETATION to improve its yield estimates. The pre-processed images are converted to fAPAR and combined with meteorological data (irradiance, temperature) to daily growth values by means of the Monteith approach. The regional means of the cumulative monthly growth numbers are calibrated against official harvest statistics by means of crop-specific neural networks. The quality of the yield estimates varies with the importance of the crop: the R²-values for winter wheat, sugar-beets and fodder maize are respectively 60%, 48% and 36%. The final yield forecasts will be better, because the B-CGMS integrates the image-based yield estimates with the assessments of the agromet-model and of the technological trend function. The technique of linear unmixing seems promising but in its actual state it is too unpredictable to be included in an operational scheme.
Target :	Researchers ; Professionals ; Students
Permalink :	http://hdl.handle.net/2268/94321

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