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Abstract

Spatialization in agrometeorology is the process of translating observed or derived data on weather stations to points or to areas outside these stations. The spatialization consists of the interpolation of station values to interpolation points or to an interpolation surface. The result of the interpolation is the estimate of the value of property in the interpolation point.
The choice of an interpolation method depends on the purpose of the application, the availability of data, efficiency of data processing and costs. A functional evaluation of interpolation methods must consider the spatial and temporal variability of the different types of meteorological data in relation to the meteorological processes.
This paper is based on a study on spatialization of daily meteorological data required as input of a crop model for the calculation of the growth of crops, their water use and water requirements, and phenological development. The study consisted of a theoretical evaluation of interpolation methods (BEEK, 1991a, 1991b) and the development of a new procedure (Van der Voet et al, 1994). The spatialization requirement was to translate data from synoptic weather stations to a 50x50 km grid over Europe. The developed spatialization method and the model are applied in the Crop Growth Monitoring System (CGMS) of the MARS-STAT project (Vossen and Rijks,1995;) Van Diepen and Van der Wal, 1995) for the continuous monitoring of the agricultural season and regional yield forecasting in semi real time over the whole territory of the European Union (EU).

Additional information

Authors: GOZZINI B, ;HIMS M (EDITORS),
Bibliographic Reference: EUR 18473 EN (1998) 149pp.
Availability: COST PUBLICATIONS ARE TO BE ORDERED THROUGH OOPEC SALES POINTS at http://eur-op.eu/general/fr/index.htm
ISBN: ISBN 92-828-4858-2
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