Production of climatic and bioclimatic maps by Universal Kriging with external drift: theory and examplesfor Italy. In this paper GIS-based maps of climatic and bioclimatic data for Italy have been obtained by inter­polating values observed at measurement stations. Long-term (1961-1990) average monthly data were obtai­ned from weather stations measuring precipitation (1102 sites) and temperature (321 sites). We analysedtwelve climatic variables (temperature and precipitation) and nine bioclimatic indexes. Terrain variables andgeographical location have been used as predictors of climate variables: longitude, latitude, elevation, aspect,slope, continentality and estimated solar radiation. Universal kriging (i.e., simple kriging with trend functiondefined on the basis of a set of covariates), which is optimal (i.e., BLUP, best linear unbiased predictor) if spa­tial association is present, has been used as spatial interpolator. Based on the root mean square errors fromcross-validation tests, we ranked the best search radius for each variable data set. A 15 km search radius hasbeen demonstrated to be the best one to model precipitation variables and precipitation-based bioclimatic in­dexes, while temperature variables were modelled using a 30 km radius.

Produzione di mappe climatiche e bioclimatiche mediante Universal Kriging con deriva esterna: teoria ed esempi per l'Italia

Collalti Alessio;
2008

Abstract

Production of climatic and bioclimatic maps by Universal Kriging with external drift: theory and examplesfor Italy. In this paper GIS-based maps of climatic and bioclimatic data for Italy have been obtained by inter­polating values observed at measurement stations. Long-term (1961-1990) average monthly data were obtai­ned from weather stations measuring precipitation (1102 sites) and temperature (321 sites). We analysedtwelve climatic variables (temperature and precipitation) and nine bioclimatic indexes. Terrain variables andgeographical location have been used as predictors of climate variables: longitude, latitude, elevation, aspect,slope, continentality and estimated solar radiation. Universal kriging (i.e., simple kriging with trend functiondefined on the basis of a set of covariates), which is optimal (i.e., BLUP, best linear unbiased predictor) if spa­tial association is present, has been used as spatial interpolator. Based on the root mean square errors fromcross-validation tests, we ranked the best search radius for each variable data set. A 15 km search radius hasbeen demonstrated to be the best one to model precipitation variables and precipitation-based bioclimatic in­dexes, while temperature variables were modelled using a 30 km radius.
2008
Istituto per i Sistemi Agricoli e Forestali del Mediterraneo - ISAFOM
Bioclimatic indexes
GIS
Italy
Spatial interpolation
Universal kriging
File in questo prodotto:
File Dimensione Formato  
Forest@_efor0507-0050008_Attorre.pdf

accesso aperto

Descrizione: Produzione di mappe climatiche e bioclimatiche mediante Universal Kriging con deriva esterna: teoria ed esempi per l’Italia
Tipologia: Versione Editoriale (PDF)
Licenza: Creative commons
Dimensione 659.8 kB
Formato Adobe PDF
659.8 kB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/362660
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
  • ???jsp.display-item.citation.isi??? ND
social impact