Improving Air Temperature Modelization by Means of Remote Sensing Variables

Author

Cristóbal, J. ; Ninyerola, M. ; Pons, X. ; Pla, M.

Author_Institution

Autonomous Univ. of Barcelona, Cerdanyola del Valles

fYear

2006

fDate

July 31 2006-Aug. 4 2006

Firstpage

2251

Lastpage

2254

Abstract

In this article we present a hybrid methodology between Remote Sensing and Geographical Information Systems to retrieve instantaneous, mean, maximum and minimum air temperatures for daily, monthly and annual periods between 2000 and 2005 on a regional scale (Catalonia, North-West Spain) by means of multiple regression analysis and spatial interpolation techniques. Best air temperature models are obtained when remote sensing variables are combined with geographical variables: averaged test R²=0.67 and averaged RMS error=1.22degC for daily temperatures and averaged test R²=0.90 and averaged RMS error =0.84degC for monthly and annual temperatures.

Keywords

atmospheric techniques; atmospheric temperature; geographic information systems; interpolation; regression analysis; remote sensing; AD 2000 to 2005; Catalonia; Spain; air temperature modelling; geographical information systems; instantaneous air temperature retrieval; maximum air temperature retrieval; mean air temperature retrieval; minimum air temperature retrieval; multiple regression analysis; remote sensing variables; spatial interpolation techniques; Interpolation; Land surface; Land surface temperature; MODIS; Meteorology; Regression analysis; Remote sensing; Satellite ground stations; Temperature sensors; Testing;

fLanguage

English

Publisher

ieee

Conference_Titel

Geoscience and Remote Sensing Symposium, 2006. IGARSS 2006. IEEE International Conference on

Conference_Location

Denver, CO

Print_ISBN

0-7803-9510-7

Type

conf

DOI

10.1109/IGARSS.2006.582

Filename

4241729