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Chinese Journal of Applied Ecology ›› 2018, Vol. 29 ›› Issue (9): 2861-2868.doi: 10.13287/j.1001-9332.201809.015

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A multi-scale study on the formation mechanism and main controlling factors of urban thermal field based on urban big data.

LUAN Xia-li1, WEI Sheng2,3, HAN Shan-rui4, LI Xiao-ting1, YANG Wen-yu1, LIU Mao-song1, XU Chi1*   

  1. 1School of Life Sciences, Nanjing University, Nanjing 210023, China;
    2Jiangsu Institute of City Planning and Design, Nanjing 210036, China;
    3School of Architecture and Urban Planning, Nanjing University, Nanjing 210093, China;
    4East China Investigation and Design Institute, Hangzhou 310014, China.
  • Received:2018-01-15 Online:2018-09-20 Published:2018-09-20
  • Supported by:

    This work was supported by the National Natural Science Foundation of China (31770512) and the Fundamental Research Funds for the Central Universities (020814380089).

Abstract: The composition and structure of urban landscape and human activity intensity are key factors shaping urban thermal fields, whereas the relative importance of influencing factors for urban thermal distribution remains unclear. We carried out a case study in Yixing City. Land surface temperature (LST), ecological infrastructure (including vegetation and water cover), building volume and point of interest data were extracted from the RS interpretation, field mapping and programming technique. Using Pearson correlation analysis, univariete regression analysis, multiple regression analysis and relative weight analysis, we quantitatively analyzed the relationships between urban land surface temperature to ecological infrastructure, building volume, POI density at multiple scales (500, 1000, 2000 m) as well as their relative importance. The results showed that ecological infrastructure had a significant cooling effect, and the building volume and POI density were positively correlated with LST. Among the influence factors of urban heat field, ecological infrastructure had the highest relative weight (21.3%-43.8%), followed by building volume (20.7%-22.6%) and POI density (13.7%-21.7%). Our results would help to understand the relative importance of factors driving urban thermal field and offer important reference for taking mitigation measures to alleviate urban heat island effect.