Spatial quantitative analysis of the potential driving factors of land surface temperature in different "Centers" of polycentric cities: A case study in Tianjin, China

Die Hu; Qingyan Meng; Linlin Zhang; Ying Zhang

doi:10.1016/j.scitotenv.2019.135244

Spatial quantitative analysis of the potential driving factors of land surface temperature in different "Centers" of polycentric cities: A case study in Tianjin, China

Sci Total Environ. 2020 Mar 1:706:135244. doi: 10.1016/j.scitotenv.2019.135244. Epub 2019 Nov 29.

Authors

Die Hu¹, Qingyan Meng², Linlin Zhang¹, Ying Zhang¹

Affiliations

¹ Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China; University of Chinese Academy of Sciences, Beijing 100049, China; Sanya Institute of Remote Sensing, Sanya 572029, China.
² Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China; Sanya Institute of Remote Sensing, Sanya 572029, China. Electronic address: mengqy@radi.ac.cn.

PMID: 31862590
DOI: 10.1016/j.scitotenv.2019.135244

Abstract

Revealing the dominant driving factors of land surface temperature (LST) plays an important role in mitigating the urban heat island (UHI) effect. Numerous international metropolises are developing polycentric forms under the process of suburbanization in conjunction with rapid urbanization, generating new UHI spatial patterns in internal urban areas. To comprehensively understand the effects of multi-factors on the thermal environment, our study examined a typical polycentric city, Tianjin. According to the concept of polycentrism, this study focused on three types of city "centers": major city core, new district core and industrial park. Eleven potential driving factors of LST were explored from four layers, and the geo-detector model was applied to rank the explanatory degree of these factors on LST. Three different city centers of the polycentric city showed varied UHI spatial pattern characteristics, and their response to the effect of natural factors and social factors on LST were quite diverse. Heat island areas were distributed homogeneously in the major city core; the UHI pattern on the east-west axis was unbalanced in the new district core due to the unsaturated urban space and dynamic planning policies; in industrial park, production areas were segregated by green belts with clear boundaries. For the whole city and the major city core, the imperviousness factor had the highest explanatory rate for LST, followed by the greenness factor. In contrast to the results of previous studies, the wetness factors had a greater impact on LST in the new district core and industrial park, second only to the greenness factor. Furthermore, selected factors exhibited bilinear or nonlinear enhanced relationships in their interactions. The driving laws of LST in different city centers were summarized with an explorative case study, aimed at providing theoretical basis and practical guidance for optimizing urban thermal environment planning, especially for highly urbanized polycentric cities.

Keywords: Driving factors; Land surface temperature; Polycentric city; Urban heat island.