PROGRESS IN GEOGRAPHY ›› 2021, Vol. 40 ›› Issue (6): 1037-1047.doi: 10.18306/dlkxjz.2021.06.013

• Articles • Previous Articles     Next Articles

Influence of the choice of geographic unit on the response of urban thermal environment:Taking Beijing as an example

LIU Shizhe1(), XIE Miaomiao1,2,*(), WU Rongrong1, WANG Yanan1, LI Xinyu3   

  1. 1. School of Land Science and Technology, China University of Geosciences (Beijing), Beijing 100083, China
    2. Key Laboratory of Land Consolidation, Ministry of Natural Resources, Beijing 100035, China
    3. Beijing Institute of Landscape Architecture, Beijing 100102, China
  • Received:2020-07-02 Revised:2021-02-22 Online:2021-06-28 Published:2021-08-28
  • Contact: XIE Miaomiao E-mail:925253045@qq.com;xiemiaomiao@cugb.edu.cn
  • Supported by:
    National Natural Science Foundation of China(41771204);Beijing Municipal Science and Technology Project(D171100007117001)

Abstract:

The scale effect and spatial heterogeneity determine that the effect of the same influencing factor on ecological processes varies in different geographic units. In this study, urban thermal environmental effect, a typical urban ecological process, was examined. In view of the current situation that the thermal environmental response pattern of different geographic units has rarely been studied, four geographic units—land use type, grid, city block, and local climate area, were selected. Normalized Difference Vegetation Index (NDVI), Impervious Surface Area (ISA), and Modified Normalized Difference Water Index (MNDWI)—the commonly used indices for landscape components, were used as the impact factors of thermal environment to explore the differences in the response pattern of urban thermal environment in different geographic units. The urban area of Beijing Municipality as redefined by point of interest (POI) data was chosen as the study area. The results show that: 1) The Pearson correlation analysis of single factor and land surface temperature shows that the block and grid are the division units, and the influence factors have a high correlation with land surface temperature. 2) The multi-factor regression method is more suitable for explaining the spatial variability of land surface temperature (LST). The combination of vegetation and impervious factors is in the 4-km grid unit, while the combination of vegetation and water and the combination of vegetation, water and impervious factors is the strongest in explaining the spatial variability of LST in the local climate zone unit. This paper provides a basis for the selection of the influencing factors of heat island in big cities in northern China, enriches the case study on the response law of thermal environmental effects at different scales, and provides a basis for the selection of appropriate research units for urban ecological environmental effects.

Key words: urban thermal environment, heat island, geographic unit, landscape components, land surface temperature, Beijing