京津冀地区耕地利用转型时空分异及驱动机制

doi:10.18306/dlkxjz.2020.12.003

摘要/Abstract

摘要：

耕地利用转型代表耕地利用形态的趋势性变化。论文以京津冀地区157个县域空间为基本研究单元,从显性形态与隐性形态双重属性出发构建耕地利用形态指标体系,运用冷热点、空间变差函数等方法分析1990—2015年耕地利用形态变化的时空特征,在此基础上,利用空间误差模型(spatial error model, SEM)对耕地利用转型的驱动机制进行了定量分析。结果表明：① 京津冀地区耕地利用形态指数空间分布呈东南高、西北低的格局,与该地区地形分布格局基本一致,且因坝上高原特色农业发展形成独立高值区。② 京津冀地区耕地利用形态指数空间分异呈现逐渐缩小的趋势,显著热点区与显著冷点区分布相对稳定且面积不断缩小,耕地利用转型较为平稳。显性形态值普遍呈现先升高后降低趋势,隐性形态值则呈升高趋势,表明京津冀耕地出现空间收缩、功能优化式转型。③ 高程是影响京津冀地区耕地利用形态空间特征的主要自然环境因素,二三产业占比、地均固定资产投资与城镇化率等经济发展和城镇建设因素则是驱动1990—2015年京津冀地区耕地转型的主导因素,但不同时段、不同县域单元耕地转型动力机制存在差异,各驱动因子作用强度也不完全一致。

关键词: 耕地利用转型, 耕地利用形态, 空间转型, 功能转型, 京津冀地区

Abstract:

The transition of cultivated land use represents the change trend of cultivated land use form. Taking 157 counties in the Beijing-Tianjin-Hebei region as cases, this study constructed the index system of cultivated land use form from the dual attributes of dominant form and recessive form. The spatial and temporal characteristics of change of cultivated land use form were analyzed by the methods of cold/hot spot analysis and spatial variation functions. On this basis, the driving mechanism of cultivated land use transition is quantitatively analyzed by the spatial error model (SEM). The results show that: 1) Cultivated land use form index values in the Beijing-Tianjin-Hebei region is high in the southeast and low in the northwest, which is consistent with the terrain distribution pattern in the region. Due to the development of characteristic agriculture on the Bashang Plateau, an independent high-value area was formed. 2) The spatial differentiation of cultivated land use form index in the Beijing-Tianjin-Hebei region shows a trend of gradual reduction. The distribution of significant hot spots and significant cold spots is relatively stable and the area continues to shrink, which indicates that the transition of cultivated land use is relatively steady. Specifically, the dominant morphological value generally increases first and then decreases, while the recessive morphological value increases, demonstrating that the cultivated land in the Beijing-Tianjin-Hebei region is undergoing spatial contraction and functional optimization transitions. 3) Elevation is the main natural environmental factor that affects the spatial characteristics of cultivated land utilization, while the economic and urban development factors such as the proportion of secondary and tertiary industries, average fixed asset investment, and urbanization rate are the leading factors driving the transition of cultivated land in the Beijing-Tianjin-Hebei region from 1990 to 2015. However, there are differences in the dynamic mechanism of cultivated land use transition in different time periods and different county units, and the intensity of each driving factor is also different.

Key words: cultivated land use transition, cultivated land use form, spatial transition, functional transition, Beijing-Tianjin-Hebei region

付慧, 刘艳军, 孙宏日, 周国磊. 京津冀地区耕地利用转型时空分异及驱动机制[J]. 地理科学进展, 2020, 39(12): 1985-1998.

FU Hui, LIU Yanjun, SUN Hongri, ZHOU Guolei. Spatiotemporal characteristics and dynamic mechanism of cultivated land use transition in the Beijing-Tianjin-Hebei region[J]. PROGRESS IN GEOGRAPHY, 2020, 39(12): 1985-1998.

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决策层	目标层及权重	指标层	指标计算	指标权重	指标释义
耕地利用形态指数	显性形态 0.4997	人均耕地面积	耕地面积/总人口(hm²/人)	0.38	耕地数量水平
		人均粮食播种面积	粮食播种面积/总人口(hm²/人)	0.25	粮食安全状况
		耕地斑块占景观面积指数(PLAND)	利用景观分析软件Fragstats计算	0.23	耕地空间结构
		耕地斑块聚集度指数(AI)	利用景观分析软件Fragstats计算	0.14	耕地集聚程度
	隐性形态 0.5003	粮食单产	粮食产量/粮食播种面积(kg/hm²)	0.14	耕地质量水平
		单位耕地面积化肥用量	农用化肥施用量/耕地面积(t/hm²)	0.39	耕地投入强度
		农业人均产值	农业总产值/农业人口(元/人)	0.34	耕地经济产出
		单位耕地供养人数	农业人口/耕地面积(人/hm²)	0.13	耕地供养功能

准则层	指标层	指标计算或来源	指标释义
自然环境因素	高程	根据DEM计算高程值	地形地貌基础
	年降水量	根据气象站点数据计算地区平均值	区域降水条件
	距主要河流距离	根据水系分布计算欧氏距离	区域水文环境
经济发展因素	人均GDP	GDP总量/总人口	经济发展水平
	农民人均纯收入	来自统计年鉴数据	农民收入水平
	二三产业占比	二三产业产值/GDP总量	产业结构水平
城镇建设因素	地均固定资产投资	固定资产投资总额/区域土地面积	资产投入力度
	城镇化率	城镇人口/总人口	城镇发展程度
	人口密度	总人口/区域土地面积	人口承载能力
	城市行政等级	县、县级市、地级市区、省会城市和直辖市分别赋值1、2、3、4、5	城镇建设水平

指标	参数	1990年	2000年	2010年	2015年
变程	a	628800	718500	577500	255600
块金值	C₀	0.00001	0.00051	0.00013	0.00046
基台值	C₀+C	0.00523	0.00680	0.00682	0.00639
块金系数	C₀/(C₀+C)	0.998	0.925	0.981	0.928
拟合模型		指数	指数	指数	指数
决定系数	R²	0.993	0.986	0.993	0.966

年份	全方位		南—北(0°)		东北—西南(45°)		东—西(90°)		东南—西北(135°)
年份	D	R²	D	R²	D	R²	D	R²	D	R²
1990	1.567	0.940	1.530	0.988	1.614	0.975	1.526	0.880	1.506	0.674
2000	1.700	0.981	1.680	0.851	1.603	0.926	1.771	0.776	1.640	0.730
2010	1.630	0.971	1.580	0.985	1.639	0.968	1.689	0.910	1.599	0.614
2015	1.767	0.905	1.721	0.920	1.778	0.914	1.735	0.945	1.790	0.498

影响因子	1990年			2000年			2010年			2015年
影响因子	OLS	SLM	SEM	OLS	SLM	SEM	OLS	SLM	SEM	OLS	SLM	SEM
高程	-0.182^***	-0.056^***	-0.119^***	-0.094^***	-0.016	-0.100^***	-0.143^***	-0.038^***	-0.140^***	-0.144^***	-0.084^***	-0.151^***
年降水量	-0.192^***	-0.086^***	-0.152^***	0.0003	-0.012	-0.075	-0.038^**	-0.017^*	-0.064^*	-0.169^***	-0.111^***	-0.168^***
距主要河流距离	-0.051^***	-0.028^**	-0.035^*	-0.044^*	-0.032^**	-0.052^**	-0.039^**	-0.022^*	-0.024	-0.084^***	-0.060^***	-0.064^**
人均GDP	0.078^**	0.105^***	0.107^***	0.043	0.047	0.080^**	-0.149	0.005	0.043	0.105	0.156^*	0.169^*
农民人均纯收入	-0.0543^*	0.002	0.025	0.009	0.016	0.010	0.019	0.047	0.006	0.099^***	0.099^***	0.090^***
二三产业占比	-0.010	-0.028^**	-0.027^**	-0.094^***	-0.080^***	-0.065^***	-0.092^***	-0.078^***	-0.044^***	-0.131^***	-0.117^***	-0.103^***
地均固定资产投资	-0.019	-0.069^**	-0.084^***	-0.275^**	-0.282^***	-0.326^***	0.122	-0.063	-0.114^*	-0.081	-0.133	-0.149
城镇化率	-0.051^**	-0.046^***	-0.048^***	-0.041	-0.041^*	-0.057^**	-0.020	-0.023	-0.051^***	-0.074^**	-0.069^**	-0.776^**
人口密度	-0.089^*	-0.051	-0.028	0.160	0.181^***	0.218^***	-0.182	-0.0167	0.035	0.082	0.131^*	0.147^**
城市行政等级	0.010	0.008	0.003	-0.023	0.0003	0.006	-0.036	-0.013	0.007	-0.076^**	-0.072^**	-0.068^**
W-Y		0.764^***			0.779^***			0.796^***			0.422^***
Lambda			0.835^***			0.838^***			0.872^***			0.472^***
R²	0.436	0.739	0.773	0.358	0.713	0.731	0.548	0.808	0.820	0.510	0.577	0.584
LogL	276.7	319.9	327.5	242.1	292.6	294.7	265.8	319.8	320.3	241.5	250.1	250.6
AIC	-531.4	-615.9	-633.0	-462.2	-561.2	-567.4	-509.7	-615.5	-618.6	-461.1	-476.1	-479.1
SC	-497.8	-579.2	-599.4	-428.6	-524.6	-533.7	-476.1	-578.9	-594.9	-427.5	-439.4	-445.6