藏北高原砾石粒径空间异质性研究

doi:10.13866/j.azr.2023.02.13

Abstract

Abstract:

Gravel is the product of various hydrological and erosion processes and is a symbol of grassland and soil degradation and ecosystem deterioration. Consequently, gravel also affects various erosion processes. Studying the spatial differentiation of gravel in the Northern Tibetan Plateau is of considerable importance for the restoration of regional ecological environments. In this paper, the size and spatial location of surface gravel were studied, and the spatial heterogeneity was systematically analyzed by Moran’s I index, spatial variogram, geographic detector, and regression analysis. The following results are presented. (1) The global Moran’s I index is 0.481, which shows a significant positive correlation. Meanwhile, the local Moran’s I index shows a high-high gravel accumulation pattern in the eastern part of the study area, low-low in the middle part, and mostly random distribution in the rest of the study area. (2) Gravel spatial heterogeneity is dominated by structural factors. However, some differences are found between the best fitting model of the variogram and the values of characteristic parameters; that is, certain anisotropy characteristics exist. (3) The geographic detector results showed that NDVI and land-use type were the main factors affecting the spatial heterogeneity of gravel size in the study area, while population density, vegetation type, and annual average precipitation were the secondary factors. (4) The results of regression analysis revealed that the optimal scale regression was the best regression model, and NDVI had the largest influence on gravel size, followed by land-use type, annual mean precipitation, and vegetation type.

Key words: Northern Tibetan Plateau, gravel size, spatial heterogeneity, geographic detector, regression analysis

XU Tao, YU Huan, KONG Bo, QIU Xia, HU Mengke, LING Pengfei. Spatial heterogeneity of gravel size in Northern Tibetan Plateau[J].Arid Zone Research, 2023, 40(2): 292-302.

Figures/Tables 12

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数据类型	数据名称	数据来源	分辨率
自然因素	DEM（X₁）	国家地球系统科学数据中心（http:www.geodata.cn）	30 m
	年NDVI（X₂）	中国科学院资源环境科学与数据中心（http:www.resdc.cn）	1000 m
	土地利用类型（X₃）	国家地球系统科学数据中心（http:www.geodata.cn）	30 m
	土壤类型（X₄）	国家地球系统科学数据中心（http:www.geodata.cn）	1000 m
	植被类型（X₅）	中国科学院资源环境科学与数据中心（http:www.resdc.cn）	1000 m
	年均降水（X₆）	中国科学院资源环境科学与数据中心（http:www.resdc.cn）	500 m
人文因素	人口密度（X₇）	中国科学院资源环境科学与数据中心（http:www.resdc.cn）	100 m
人文因素	夜间灯光强度（X₈）	美国国家地球物理数据中心(https:www.ngdc.noaa.gov)	500 m

	方向	块金值（C₀）	偏基台值（C）	块基比（C₀/C₀+C）	变程（a）/km	决定系数（R²）
各向同性	-	0.391	0.708	0.356	26.178	0.981
各向异性	0°	0.537	1.185	0.312	69.500	0.500
	22.5°	0.534	1.330	0.286	76.500	0.788
	45°	0.539	1.195	0.311	69.500	0.585
	67.5°	0.544	1.234	0.306	90.420	0.802
	90°	0.617	1.203	0.339	62.840	0.505
	112.5°	0.606	1.347	0.310	70.240	0.833
	135°	0.601	1.195	0.335	64.360	0.509
	157.5°	0.555	1.503	0.270	110.000	0.801

	DEM（X₁）	年NDVI（X₂）	土地利用类型（X₃）	土壤类型（X₄）	植被类型（X₅）	年均降水（X₆）	人口密度（X₇）	夜间灯光强度（X₈）
q值	0.11	0.41	0.27	0.17	0.15	0.13	0.16	0.02
P值	0.35	0.00	0.00	0.99	0.00	0.00	0.00	1.00

C	A+B	结果	解释
X₂∩X₃=0.56	X₂(0.41)+X₃(0.27)	C >max（A,B）	双因子增强
X₂∩X₅=0.46	X₂(0.41)+X₅(0.17)	C >max（A,B）	双因子增强
X₂∩X₆=0.46	X₂(0.41)+X₆(0.13)	C >max（A,B）	双因子增强
X₂∩X₇=0.47	X₂(0.41)+X₇(0.16)	C >max（A,B）	双因子增强
X₃∩X₅=0.42	X₃(0.27)+X₅(0.17)	C >max（A,B）	双因子增强
X₃∩X₆=0.47	X₃(0.27)+X₆(0.13)	C>A+B	非线性增强
X₃∩X₇=0.39	X₃(0.27)+X₇(0.16)	C >max（A,B）	双因子增强
X₅∩X₆=0.28	X₅(0.17)+X₆(0.13)	C >max（A,B）	双因子增强
X₅∩X₇=0.26	X₅(0.17)+X₇(0.16)	C >max（A,B）	双因子增强
X₆∩X₇=0.27	X₆(0.13)+X₇(0.16)	C >max（A,B）	双因子增强

	标准化系数	显著性	改进后标准化系数	改进后显著性
NDVI	0.530	0.000	0.578	0.000
土地利用类型	0.313	0.000	0.308	0.000
年均降水	0.084	0.003	0.102	0.003
植被类型	0.070	0.000	0.064	0.000
人口密度	-0.044	0.212	-	-

Spatial heterogeneity of gravel size in Northern Tibetan Plateau

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