基于地理探测器的北京市地表反照率时空分异及其驱动因素研究

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

地表反照率直接影响着辐射平衡和地表热收支,是地球-大气系统研究中的关键因子。本文研究了2015年北京市地表反照率的时空分布特征,并基于地理探测器定量分析了地表反照率空间分异的驱动因素及其交互作用。结果表明:北京市地表反照率呈东南高、西北低的趋势;冬季变化最大,春季变化最小;年地表反照率最小值出现在秋季,最大值出现在冬季,具有显著的时空异质性。土地覆盖类型、NDVI、高程、坡度、温度和降水对地表反照率的空间分异均有显著影响,影响力分别为0.537、0.625、0.512、0.531、0.515和0.190;且一些驱动因素对反照率空间分布的影响存在显著差异。任意两种驱动因素之间均存在交互作用,表现出双变量增强的结果。其中,地表覆盖类型与NDVI的交互作用最大,影响力为0.710,而温度与降水的交互作用最弱,影响力为0.531。研究结果为了解北京市地表反照率的时空分布特征以及区域气候和陆面模式中能量模块的物理过程提供了科学依据。

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.