Abstract
This paper aims to analyze the spatio-temporal structure of urban air temperature distribution in the southern part of Kanto Plain using GIS. Temperature is affected by many factors such as the ocean, land cover and topography. To estimate the contribution of the each factor statistically, multi-regression analysis is applied to air temperature data (1984-1993) of 96 meteorological stations in the study area. From the diurnal and seasonal variations of the estimated coefficients of those factors, spatio-temporal structure of the air temperature distribution is revealed. Finally, urban heat island phenomena in the daytime and nighttime is visually demonstrated using pixel-field data of air temperature generated based on the results of multiple regression analysis.
