关中地区人类活动强度与地表温度的时空关联特征及其驱动作用

doi:10.12118/j.issn.1000-6060.2023.266

摘要/Abstract

摘要：

人类活动对全球温度升高的促进作用愈加明显，如何科学衡量人类活动强度并探究其与地表温度的时空关联性成为当前研究热题。以关中地区为例，整合人口密度、地区生产总值、夜间灯光强度、建设用地面积比例、电量消耗5个指标表征人类活动强度，分析关中地区人类活动强度与地表温度时空变化规律，探究人类活动强度与地表温度关联性及其驱动作用。结果表明：（1） 2001—2020年关中地区平均地表高温、低温区域分别呈现总体增大、减少的趋势，地表高温区域范围不断扩大。（2） 2000—2020年关中地区的人类活动强度逐渐增加，特别是在各地级市的市辖区和主要居民点，高强度区域范围不断扩大，而低强度区域主要位于秦岭山区。（3） 2000—2020年关中地区人类活动强度与地表温度呈显著正相关性和空间上的集聚性，正相关区域面积呈现增大趋势，主要由不显著及负相关转化为正相关区域，高-高类型集聚区主要分布在各城市主城区，低-低类型集聚区主要分布在秦岭山区。（4）影响地表温度的人类活动强度指标中，夜间灯光强度、人口密度、建设用地面积比例对地表温度的驱动作用最为显著；且夜间灯光强度与建设用地面积比例、人口密度与建设用地面积比例交互作用对地表温度的解释力最强。

关键词: 人类活动强度, 地表温度, 时空关联性, 关中地区

Abstract:

The accelerating role of human activities in the rise of global temperature has become increasingly evident. The scientific measurement of human activity intensity and the exploration of its spatiotemporal correlation with surface temperature has become a hot topic in research. Taking the Guanzhong area as an example, we integrate five indicators(population density, regional gross domestic product, nighttime light intensity, proportion of construction land area, and electricity consumption) to analyze spatiotemporal variations in human activity intensity and surface temperature. Furthermore, we explore the correlation and driving forces between human activity intensity and surface temperature. The results show that: (1) From 2001 to 2020, the average surface high and low temperature areas in the Guanzhong area demonstrated overall increasing and decreasing trends, respectively, with the scope of the surface high temperature areas continuously expanding. (2) The human activity intensity in the Guanzhong area gradually increased from 2000 to 2020, especially in downtown districts and major residential areas of prefecture-level cities. High-intensity areas continued to expand, while low-intensity areas were mainly located in the Qinling Mountains. (3) From 2000 to 2020, the human activity intensity in the Guanzhong area showed a significant positive correlation and spatial agglomeration with surface temperature. The area of positive correlation areas shows an increasing trend, mainly transforming from insignificant and negative correlations to positive correlation areas, with high-high type agglomeration areas primarily distributed in the main urban areas of cities, while low-low type agglomeration areas are mainly found in the Qinling Mountains. (4) Nighttime light intensity, population density, and the proportion of construction land area were identified as the most significant indicators of human activity intensity influencing surface temperature. Moreover, the explanatory power is most substantial for the interaction between nighttime light intensity and the proportion of construction land area as well as the interaction between population density and the proportion of construction land area.

Key words: human activity intensity, surface temperature, temporal-spatial correlation, Guanzhong area

纪王迪, 黄晓军, 包微, 马耀壮. 关中地区人类活动强度与地表温度的时空关联特征及其驱动作用[J]. 干旱区地理, 2024, 47(6): 967-979.

JI Wangdi, HUANG Xiaojun, BAO Wei, MA Yaozhuang. Spatiotemporal correlation characteristics and driving forces of human activity intensity and surface temperature in the Guanzhong area[J]. Arid Land Geography, 2024, 47(6): 967-979.

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判断依据	交互作用类型
q(X1∩X2)<Min[q(X1),q(X2)]	非线性减弱
Min[q(X1),q(X2)]<q(X1∩X2)<Max[q(X1),q(X2)]	单因子非线性减弱
q(X1∩X2)>Max[q(X1),q(X2)]	双因子增强
q(X1∩X2)=q(X1)＋q(X2)	独立
q(X1∩X2)>q(X1)＋q(X2)	非线性增强

数据名称	分辨率	年份	数据来源
地表温度（LST）	1 km	2001、2005、2010、2015、2020	https://www.resdc.cn/
人口密度（POP）	1 km	2000、2005、2010、2015、2019	https://www.resdc.cn/
地区生产总值（GDP）	1 km	2000、2005、2010、2015、2019	https://www.resdc.cn/
夜间灯光强度（NL）	1 km	2000、2005、2010、2015、2020	https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/GIYGJ
电量消耗（EC）	1 km	2000、2005、2010、2015、2019	https://doi.org/10.6084/m9.figshare.17004523.v1
建设用地面积比例（CLAP）	30 m	2000、2005、2010、2015、2020	https://www.resdc.cn/

年份	面积占比
年份	≤13.06 ℃	13.07~16.31 ℃	16.32~18.93 ℃	18.94~21.23 ℃	≥21.24 ℃
2001	5.85	14.12	24.06	31.99	23.99
2005	7.27	16.08	26.88	28.50	21.27
2010	6.06	17.58	28.56	26.01	21.79
2015	5.69	19.48	32.32	19.40	23.11
2020	5.12	14.80	27.68	21.61	30.78

年份	面积占比
年份	≤0.02	0.03~0.06	0.07~0.16	0.17~0.34	≥0.35
2000	80.55	13.10	4.81	1.09	0.46
2005	78.73	12.99	5.62	1.80	0.86
2010	74.92	13.53	7.10	3.25	2.20
2015	78.65	8.70	7.21	3.25	2.20
2020	74.67	11.25	7.61	3.70	2.77

驱动因素			影响程度
驱动因素	2000年	2005年	2010年	2015年	2020年
人口密度（POP）	0.2140^***	0.2936^***	0.3129^***	0.2755^***	0.2436^***
地区生产总值（GDP）	0.1121^***	0.1035^***	0.1183^***	0.0515^***	0.0635^***
夜间灯光强度（NL）	0.2330^***	0.3789^***	0.3639^***	0.1768^***	0.2616^***
电量消耗（EC）	0.0547^***	0.1002^***	0.0920^***	0.1151^***	0.1363^***
建设用地面积比例（CLAP）	0.1487^***	0.2367^***	0.2120^***	0.2415^***	0.2757^***