Journal of Resources and Ecology ›› 2021, Vol. 12 ›› Issue (5): 609-619.DOI: 10.5814/j.issn.1674-764x.2021.05.004

• Human Activities and Ecological Security • Previous Articles     Next Articles

Spatio-temporal Pattern of Surface Albedo in Beijing and Its Driving Factors based on Geographical Detectors

LIU Qinqin1,2(), TIAN Yichen2, YIN Kai2, ZHANG Feifei2, YUAN Chao2, YANG Guang2,*()   

  1. 1. University of Chinese Academy of Sciences, Beijing 100049, China
    2. Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China
  • Received:2021-01-08 Accepted:2021-04-02 Online:2021-09-30 Published:2021-11-30
  • Contact: YANG Guang
  • About author:LIU Qinqin, E-mail: liuqinqin18@163.com
  • Supported by:
    The Major Project of High Resolution Earth Observation System(06-Y30F04-9001-2022);The National Natural Science Foundation of China(41471423)

Abstract:

Surface albedo directly affects the radiation balance and surface heat budget, and is a crucial variable in local and global climate research. In this study, the spatial and temporal distribution of the surface albedo is analysed for Beijing in 2015, and the corresponding individual and interactive driving forces of different explanatory factors are quantitatively assessed based on geographical detectors. The results show that surface albedo is high in the southeast and low in the northwest of Beijing, with the greatest change occurring in winter and the smallest change occurring in spring. The minimum and maximum annual surface albedo values occurred in autumn and winter, respectively, and showed significant spatial and temporal heterogeneity. LULC, NDVI, elevation, slope, temperature, and precipitation each had a significant influence on the spatial pattern of albedo, yielding explanatory power values of 0.537, 0.625, 0.512, 0.531, 0.515 and 0.190, respectively. Some explanatory factors have significant differences in influencing the spatial distribution of albedo, and there is significant interaction between them which shows the bivariate enhancement result. Among them, the interaction between LULC and NDVI was the strongest, with a q-statistic of 0.710, while the interaction between temperature and precipitation was the weakest, with a q-statistic of 0.531. The results of this study provide a scientific basis for understanding the spatial and temporal distribution characteristics of surface albedo in Beijing and the physical processes of energy modules in regional climate and land surface models.

Key words: albedo, spatio-temporal distribution, explanatory factors, geographical detectors