长城沿线生境质量与城镇化时空耦合协调及驱动因子研究

doi:10.12118/j.issn.1000-6060.2025.508

Abstract

Abstract:

The coordinated development of urbanization and habitat quality is crucial for sustainable development, representing a core requirement for Chinese-style modernization. Focusing on 97 cities along the Great Wall from 2000 to 2020, this study integrates the InVEST model, coupling coordination model, and a spatiotemporal geographically weighted regression model to systematically analyze the spatiotemporal dynamics and driving mechanisms of the coupling and coordination between habitat quality and urbanization. The results reveal the following: (1) Throughout the study period (2000—2020), the macropattern of habitat quality along the region remained relatively stable, exhibiting a “high in the east, low in the west” gradient distribution. Concurrently, urbanization presented a polarized spatial pattern, facilitating development within core urban agglomerations, such as Beijing-Tianjin and Zhengzhou, while driving broader regional development. (2) Temporally, the coupling and coordination degrees between habitat quality and urbanization exhibited a slow upward trend, although the overall level remained low. The relative development level of certain subregions progressed from a lagging phase to a synchronized or advanced stage. (3) Spatially, the coupling and coordination degree between habitat quality and urbanization manifested a distinct “high in the east, low in the west” differentiation, characterized by a significant regional imbalance of “high-high and low-low agglomerations”. Over time, the “middle collapse” phenomenon gradually eased, although the broader system evolution continued to exhibit pronounced path dependency. (4) The driving mechanisms of the established coupling and coordination were complex. Precipitation, economic development, technological innovation, and traffic density were key positive factors, with their marginal impacts exerting pronounced spatiotemporal heterogeneity across the region. Consequently, different regions must establish dynamic assessment and early-warning systems, formulating differentiated coordinated development strategies based on their local resource endowments and development stages to promote harmonious human-nature coexistence along the Great Wall.

Key words: habitat quality, urbanization, coupling coordination, along the Great Wall

NIE Chengjing, LI Yadi, LIU Fangtian, HAN Fang, GAO Xing. Spatiotemporal coupling coordination and driving factors of habitat quality and urbanization along the Great Wall[J].Arid Land Geography, 2026, 49(8): 1587-1600.

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目标层	准则层	指标层	权重
城镇化	人口城镇化	人口密度	0.2440
	经济城镇化	地区生产总值密度	0.5049
	空间城镇化	城市建设用地占比	0.2511

威胁因子	最大胁迫距离/km	影响权重	空间衰退类型
耕地	4	0.6	线性衰退
城镇用地	8	1.0	指数衰退
农村居民点	6	0.6	指数衰退
工业和交通用地	9	0.8	指数衰退
未利用地	4	0.5	线性衰退

土地利用类型	生境适宜度	威胁因子
土地利用类型	生境适宜度	耕地	城镇用地	农村居民点	工业和交通用地	未利用地
水田	0.3	0.0	0.8	0.5	0.6	0.3
旱地	0.5	0.0	0.8	0.5	0.7	0.4
有林地	1.0	0.6	0.9	0.8	0.8	0.4
灌木林	0.9	0.6	0.7	0.7	0.6	0.5
疏林地	0.8	0.7	0.9	0.8	0.8	0.5
其他林地	0.7	0.7	0.8	0.8	0.7	0.5
高覆盖度草地	0.9	0.6	0.7	0.6	0.6	0.7
中覆盖度草地	0.8	0.7	0.8	0.7	0.7	0.7
低覆盖度草地	0.7	0.7	0.8	0.8	0.7	0.7
河渠	0.9	0.6	0.7	0.7	0.8	0.4
湖泊	0.9	0.6	0.8	0.6	0.7	0.4
水库坑塘	0.8	0.5	0.8	0.7	0.7	0.4
永久性冰川雪地	0.1	0.1	0.0	0.1	0.2	0.1
滩涂	0.5	0.5	0.5	0.4	0.6	0.3
滩地	0.5	0.5	0.5	0.4	0.6	0.3
城镇用地	0.0	0.0	0.0	0.0	0.0	0.0
农村居民点	0.0	0.0	0.0	0.0	0.0	0.0
工业和交通用地	0.0	0.0	0.0	0.0	0.0	0.0
沙地	0.2	0.2	0.2	0.2	0.2	0.0
戈壁	0.1	0.1	0.1	0.1	0.1	0.0
盐碱地	0.2	0.2	0.2	0.2	0.3	0.0
沼泽地	0.2	0.2	0.3	0.3	0.3	0.0
裸土地	0.2	0.1	0.4	0.4	0.5	0.0
裸岩石质地	0.1	0.0	0.1	0.2	0.2	0.0
其他	0.1	0.1	0.1	0.1	0.1	0.0

年份	变程	块金值	基台值	块金系数	拟合模型	决定系数	残差
2000	3966	0.0232	0.2134	0.891	高斯模型	0.904	1.08×10^-3
2005	4195	0.0200	0.1660	0.892	高斯模型	0.888	8.19×10^-4
2010	3135	0.0200	0.1350	0.852	高斯模型	0.896	8.56×10^-4
2015	7110	0.0181	0.1133	0.840	高斯模型	0.892	4.47×10^-4
2020	7110	0.0105	0.0774	0.864	球状模型	0.864	3.19×10^-4

年份	全局Moran’s I	Z统计量
2000	0.456	11.280
2005	0.480	11.798
2010	0.452	11.138
2015	0.422	10.414
2020	0.380	9.424

Spatiotemporal coupling coordination and driving factors of habitat quality and urbanization along the Great Wall

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变量	主效应	直接效应	间接效应	总效应
降水量	0.0158^**（0.0072）	0.0166^**（0.0078）	-0.0203（0.0182）	-0.0037（0.0123）
空气质量	-0.0345^*（0.0182）	-0.0364^**（0.0184）	0.1515^***（0.0509）	0.1151^***（0.0401）
经济发展	0.0064^***（0.0007）	0.0066^***（0.0007）	-0.0089^***（0.0022）	-0.0024（0.0020）
产业结构	0.0084^***（0.0026）	0.0090^***（0.0026）	-0.0241^*（0.0143）	-0.0151（0.0141）
科技创新	0.4914^***（0.1362）	0.5078^***（0.1350）	-0.7723（0.5611）	-0.2645（0.5525）
人力存量	0.0134^***（0.0050）	0.0133^***（0.0051）	0.0144（0.0209）	0.0278（0.0196）
交通密度	-0.0126^*（0.0069）	-0.0131^*（0.0069）	0.0219（0.0182）	0.0088（0.0150）
政府规制	-0.0102^*（0.0053）	-0.0096^*（0.0056）	-0.0247（0.0250）	-0.0343（0.0251）
空间自回归系数	-0.8542^***（0.3102）	-	-	-
对数似然值	1307.4709	-	-	-
样本量	485	-	-	-

模型参数	OLS	TWR	GWR	GTWR
带宽	-	0.3284	0.2513	0.2209
残差平方和	-	2.0048	2.0251	1.7930
回归标准差	-	0.0643	0.0646	0.0608
赤池信息量准则	-1214.45	-1241.44	-1230.25	-1251.58
R²	0.6800	0.7138	0.7109	0.7441
调整后R²	-	0.7090	0.7061	0.7398

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