Classifying Urban Climate Zones Based upon Statistical Analysis of Urban Spatial Characteristics

Abstract

To effectively achieve mitigation of heat island effects requires classification of urban climate zones in advance based on analysis of the relationship between air temperature and urban spatial elements. The objective of this study is to: 1) identify influential urban spatial elements affecting air temperature by statistical analysis, and 2) provide fundamental information on establishing thermal environment enhancement planning through urban climate zones (UCZ) based on statistical analysis. This study consists of three parts: First, the air temperature of study area was analyzed using Lands at TM remotely sensed images. Next, preparative variables including topology land use, land cover, building types, and human activities to classify UCZ were prepared, and influential urban spatial elements affecting air temperature were identified by regression analysis. Finally, UCZ were delineated by K-clustering analysis, and the appropriateness of the classified UCZ were verified using ANOVA testing. The study results show that urban elements affecting air temperature include impervious surface ratio, elevation, water area, distance from a subway station, and road area. In addition, a total of 10 UCZ were detected by K-clustering analysis, and the results of the ANOVA test shows that each classified UCZ was in statistically different groups. Moreover, UCZ and air temperature maps were found to display an almost identical pattern. This study identified more accurate and clearer UCZ boundaries and explained statistically significant urban spatial characteristics to better understand the urban climate phenomenon. The results of this study can provide urban planners, architects, and landscape planners fundamental information to help manage the urban thermal environment.