Spatialization of attribute data is one of forward issues in the field of GIS While 30 year mean temperature data from 624 meteorological stations in China was spatialized, the temperature was divided into regular component, which is affected by longitude, latitude and altitude, and irregular component affected by other local factorsThey were spatialized with multiple variable regression and inverse distance weighted interpolation respectivelyThere was a correlation ratio of R= 098 between temperature and geographical factors including longitude, latitude and altitudeSumming the two spatialized components generated grid based temperature dataIt can reflect temperature change both at large scale and at small scale.