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|Autori interni:||DALLA MARTA, ANNA|
|Data di pubblicazione:||2003|
|Abstract:||Weather variables are one of the most important factors affecting agricultural production, both in terms of quantity and quality. Some of these variables in fact, such as temperature and relative humidity, are directly involved not only in lant growth and development, but also in the spread of many diseases. For these reasons it follows that the monitoring of agrometeorological factors and their spatial distribution on the territory represent important tools for a correct and thoughtful management of agricultural activities. The aim of this work was to compare the performance of different interpolation methods applied at micro and macro spatial scale. Some thematic maps describing the meteorological characteristics of the territory were then created. Weather data were collected from 38 stations for the period 1996/2002 in the experimental farm Poggio Caiano (close to Florence) and from 85 weather stations for the period 1960/1990 in the whole territory of Tuscany region. Two different interpolation methods were used to estimate the variables at unsampled locations: multiple linear regressions (MLR) and ordinary kriging (K). In order to predict the spatial distribution of the meteorological variables some important geo-topographical characteristics were used when spatialising the data. As the true values surface is not known, the comparison statistics were obtained using cross validation where one data point is withhed and the ramaining data points are used to predict the withheld point. The two interpolation techniques were then compared on the basis of mean absolute error (MAE) and root mean squared error (RMSE)|
|Autori:||DALLA MARTA, A.; Mancini, M.; Orlandini, S.|
|Titolo:||ANALYSIS OF INTERPOLATION METHODS APPLIED AT DIFFERENT SPATIAL SCALES.|
|Appare nelle tipologie:||4a - Articolo in atti di congresso|
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