Current article

Correlation between urban construction and urban heat island: A case study in Kaizhou District, Chongqing


Han Guifeng , Cai Zhi , Xie Yusi , Zeng Wei

DOI:10.11835/j.issn.1674-4764.2016.05.018

Received January 21, 2016,Revised , Accepted , Available online July 04, 2017

Volume ,2016,Pages 138-147

  • Abstract
Urban construction was an important driving factor result in the urban heat island. In order to reveal the relationships between urban construction and urban heat island, taking Kaizhou District, as an example, land surface temperatures (LST) and urban construction index were extracted using ArcGIS spatial analysis tools, and the relationship between the two was analyzed in SPSS on three spatial scales: land patch, regular grid and building lot. The results showed that LST varied greatly from land use type, and the correlations between LST and urban construction index were different among three scales. On land patch scale, there were significantly negative correlations between LST and greening ratio (GR), floor area ratio (FAR) and building density (BD) respectively and there were significantly positive correlations between LST and building bottom area (BBA) and total construction area (TCA) respectively. On regular grid scales, the correlations between LST and urban construction index increased along with the increase of grid area, and almost all correlation coefficients reached maximum values on the 840-meter grid scale. The LST was negatively correlated with GR and was positively correlated with BD and FAR respectively. Then the multiple regression model was established between LST and BD and GR. On building lot scale, there were significantly positive correlations between LST and BD and FAR respectively. However, there were significantly negative correlations between LST and building floors (BF) and strong positive correlations between LST and TCA. Although, urban construction index had great influence on urban heat island, not all urban construction index were positively correlated with LST. The results implied that urban heat island intensity and its spatial distribute were also affected by other various factors including topography, local climate, urban morphology, designated function of city, urban transportation and building material and color. Furthermore, the impact of various factors on urban heat island may be a nonlinear complicated and dynamic process.