%0 Journal Article
%T Spatialization of climatic data at the Italian national level by local regressive models
%A Blasi C
%A Chirici G
%A Corona P
%A Marchetti M
%J Forest@
%D 2007
%I Italian Society of Silviculture and Forest Ecology (SISEF)
%X The availability of spatialised climatic data is an essential pre-requisite for the implementation of GIS-based analysis in many application fields. Among the different methodologies for the spatialization of climatic data collected in weather-stations the most used are those based on geostatistical approaches, on parametric correlative models or on neural networks. Within the ˇ°Completamento delle Conoscenze Naturalistiche di Baseˇ± project, funded by the Italian Ministry for the Environment (Department of Nature Protection) a database of 403 weather-stations distributed across Italy with a time series of thirty years was collected. Data of mean monthly temperature (minimum and maximum) and rainfalls were spatialized by a local linear univariate regressive method based on elevation as independent variable. A total of 36 monthly maps with a geometric resolution of 250 m was generated. The present paper introduces the adopted methodology and the accuracy results estimated by leave-one-out cross validation.
%K Climate
%K Meteorological data
%K Spatialization
%K Regressive models
%K Italy.
%U http://www.sisef.it/forest@/showPaper.php?action=html&issue=12&msid=453&lang=en