中国县域国土空间集约利用计量测度与影响机理

doi:10.11821/dlxb201412001

摘要/Abstract

摘要：

土地利用问题日益成为中国经济发展的重要约束力之一。快速城镇化背景下城镇和乡村的快速扩张吞噬了宝贵的土地资源,粗放非集约的利用方式更加剧了土地资源的浪费。从国土空间集约利用的影响机理出发分析中国县域国土空间集约的影响机理对指导集约利用实践以及宏观集约利用政策瞄准和政策矫正都具有特殊意义。综合运用OLS模型、空间面板滞后模型和空间面板自相关模型以GIS和Matlab为技术平台,构建中国县域发展基础数据库 (1992-2010年),定量刻画中国2286个县级单元的空间集约利用度时空变化格局,计量分析社会经济发展、自然环境本底、区位交通地理、宏观战略政策和历史基础5大类变量17项具体因素的影响机理。研究结果表明,空间面板数据模型的整体显著性和可信度检验略高于一般面板数据OLS模型;在固定相关效应后对各因素的影响机制进行了检验,表明工业化、城镇化、经济发展水平、区位、交通和宏观战略政策等因素对县域国土空间集约利用的影响较为明显。自然环境因素弱于社会经济因素。被忽略的历史因素对县域国土空间集约利用具有极显著的影响。未来县域国土空间集约利用应因势利导,强化有利因素,减小不利因素影响。提高工业化和城镇化发展水平和质量。发挥市场的主导作用,完善土地市场和运行机制。优化国土空间集约利用调控政策和管治手段,制定差别化的空间集约利用政策。以资源环境承载力为基础和约束最大限度地提高投入和产出水平。

关键词: 集约利用, 国土空间, 测度, 影响机理, 影响因素, 空间计量经济模型, GIS, 县域, 中国

Abstract:

Land use issue is an important constraining force for economic sustainable development of China. Urban and rural rapid expansion depletes valued land resources under the background of rapid urbanization. An extensive use pattern might cause a serious waste of land resources. The study on influencing mechanism of land intensive use (LIU) in China at the county level is an important tool for effective LIU practice and policy-making. This paper uses OLS model, Spatial Panel Lagged model and Spatial Panel Error model to characterize the influencing mechanisms of five class factors and 17 variables supported by GIS (Geographic Information System) and MATLAB. And a comprehensive data set, including physical geography attributes and socio-economic information with 2286 counties, was developed. Meanwhile, the spatiotemporal pattern of LIU has been discussed by means of GIS. The results show that Spatial Panel Data models are slightly superior to OLS model in terms of significance and confidence level. Regression results of these models indicate that industrialization, urbanization, economic development level, location, transportation and policy have significant impact on LIU of counties. The variables of physical geography are less significant than socio-economic variables. An ignored variable of historical factor, however, became the most significant factor. In the future, the LIU at the county level should enhance favorable factors and reduce disadvantageous ones, which can be acquired by improving the entire level and quality of industrialization and urbanization. We argued that an efficient and complete land market and operating system should be built to reflect market-oriented activities at the first place. Then, according to regional differences, differential LIU regulation policies and measurements should be optimized. Meanwhile, we should pay close attention to the carrying capacity of local resources and environments when conducting LIU practices.

Key words: land intensive use, national territory, quantitative measure, influencing mechanism, influencing factors, spatial econometrics models, GIS, county, China

李广东, 方创琳. 中国县域国土空间集约利用计量测度与影响机理[J]. 地理学报, 2014, 69(12): 1739-1752.

Guangdong LI, Chuanglin FANG. Quantitative measure and influencing mechanism of land intensive use in China at the county level[J]. Acta Geographica Sinica, 2014, 69(12): 1739-1752.

图/表 11

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图2

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表1

1979-2010年中国主要区域性优惠政策定位表

批准年份	类型与数量	区域	批准年份	类型与数量	区域
1979	3 SEZ	深圳、珠海、汕头	1999	1WDS	西部地区
1980	1 SEZ	厦门	2000	11 ETDZ	合肥、郑州、成都、长沙、西安、昆明、贵阳、石河子、南昌、西宁、呼和浩特
1984	14 COC; 10 ETDZ	天津、上海、大连、秦皇岛、烟台、青岛、连云港、南通、宁波、温州、福州、广州、湛江、北海;大连、秦皇岛、烟台、青岛、宁波、湛江、天津、连云港、南通、广州	2001	4 ETDZ	南宁、太原、银川、拉萨
1985	1 ETDZ; 3 COEZ	福州;长江三角洲、珠江三角洲、闽东南地区、环渤海地区	2002	2 ETDZ	兰州、南京
1986	2 ETDZ	上海 (闵行)、上海 (虹桥)	2003	1 RNEC	东北地区老工业基地
1988	OCB; 1 SEZ; 1 ETDZ	沿海经济带;海南;上海 (漕河泾)	2004	1RCCP	中部地区
1989	1 ETDZ	厦门 (海沧)	2005	1NSRTD	浦东新区
1990	1 PD; 1 ETDZ	浦东新区、上海 (金桥)	2006	1ELD;1BH;1 NSRTD	东部地区;滨海新区
1992	13 BA; 10 MC;13BECZ;AC; 5 ETDZ	黑河、绥芬河、珲春、满洲里、二连浩特、伊宁、塔城、博乐、瑞丽、畹町、河口、凭祥、东兴;温州、昆山、营口、威海、福清 (福清融侨)、海南 (洋浦)	2007	4 NSRTD	重庆市、成都市;武汉城市圈、长株潭城市群
1993	12 ETDZ; 1 ETDZ	东山、沈阳、杭州、萧山、广州(南沙)、惠州 (大亚湾)、武汉、芜湖、长春、哈尔滨、重庆、宁波 (大榭)	2009	2 ETDZ;1 NSRTD	廊坊、扬州;深圳市
1994	2 ETDZ; 1 ETDZ	北京、乌鲁木齐、苏州 (工业园)	2010	1 SEZ 1LJ 1 NSRTD 32 ETDZ	喀什;重庆;沈阳;锦州、大连(长兴岛)、吉林、宾西、海林、日照、潍坊、东营、马鞍山、安庆、徐州、镇江、绍兴、嘉兴、湖州、漳州、泉州、增城、襄樊、黄石、岳阳、常德、井冈山、赣州、九江、金昌、天水、曲靖、德阳、广安、遵义、万州、陕西省航天、陕西省航空、临沂

表1

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图6

图7

图8

表2

表3

中国县域国土空间集约利用影响因素计量分析结果

	(1)	(2)	(3)	(4)	(5)
	OLS	SAR 时空固定 (ML)	SAR 时间固定 (ML)	SEM 时空固定 (ML)	SEM 时间固定 (ML)
α	-0.001493^***
α	(-2.6120)
LNGDP	0.000138^***	0.000453^***		0.000459^***
LNGDP	(2.1139)	(7.5172)		(7.5232)
LNPOP	-0.000148	-0.000179		-0.000165
LNPOP	(-0.9617)	(-1.3779)		(-1.2498)
IND	0.001056^***	0.002470^***		0.001763^***
IND	(3.2009)	(8.8279)		(3.4884)
URBAN	0.002233^***	0.005983^***		0.002536^***
URBAN	(7.4161)	(3.5428)		(9.3160)
POLICY	0.000251^***	0.000551^***		0.000561^***
POLICY	(8.5146)	(8.7210)		(8.7705)
LNELV	-0.000167^***		-0.000144^***		-0.000168^***
LNELV	(-4.7297)		(-4.0509)		(-4.6797)
LNSLOPE	-0.000062^***		-0.000059^**		-0.000063^***
LNSLOPE	(-2.6428)		(-2.5075)		(-2.6210)
LNRAI	0.000131		0.000127		0.000132
LNRAI	(1.6255)		(1.4923)		(1.5947)
LNTEM	0.000056		0.000052^**		0.000056
LNTEM	(1.5794)		(2.0475)		(1.5465)
LNWATER	0.000005^***		0.000005^***		0.000005^***
LNWATER	(5.9565)		(16.2101)		(15.2856)
LNDIST_PORT1	-0.000101^**		-0.000093^***		-0.000101^*
LNDIST_PORT1	(-1.9987)		(-2.7832)		(-1.9835)
LNDIST_PORT2	-0.000065^**		-0.000060^***		-0.000065^*
LNDIST_PORT2	(-1.5784)		(-2.1576)		(-1.5756)
LNDIST_CITY	-0.000106^***		-0.000095^**		-0.000105^*
LNDIST_CITY	(-1.7944)		(-2.1448)		(-1.7667)
LNTRAN_DENS	0.000076^***		0.000419^***		0.000075^***
LNTRAN_DENS	(4.1285)		(6.5455)		(4.1050)
REG	0.000171^*		0.000156^***		0.000172^**
REG	(2.5522)		(2.3459)		(2.5190)
CITY_COUNTY	0.000682^***		0.000674^***		0.000681^***
CITY_COUNTY	(5.5233)		(5.4681)		(5.4984)
LIU_A0	1.002834^***	0.760664^***	1.004324^***	0.760664^***	1.002239^***
LIU_A0	(758.0175)	(191.7858)	(770.4556)	(191.7857)	(762.4691)
ρ		0.006915^***	0.006917^***
ρ		(5.7392)	(5.7393)
γ				0.021971^***	0.025973^***
γ				(15.1074)	(16.1554)
Rbar²	0.9537	0.9584	0.9534	0.9584	0.9536
σ²	0.0001	0.0001	0.0001	0.0001	0.0001
LM lag	3736.5680^***
LM err	2200.3740^***
R-LM lag	1755.2066^***
R-LM err	219.0127^***
Durbin-Watson	2.0005
Log-likelihood	96323	99113	96300	99114	96272

表3

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要素集	具体因素	符号与单位	变量 (或代理变量)	预期影响方向
被解释变量	空间集约利用度	LIU	县域空间集约利用度指数 (由地均GDP、地均固定资产投资额和人口密度综合计算得到)
经济社会发展	经济发展水平	LNGDP	人均地区生产总值	+
	人口增长量	LNPOP	人均地方财政预算支出	+
	工业化水平	IND	第二产业增加值占国民生产总值的比重	+
	城市化水平	URBAN	非农人口占总人口的比重	+
自然环境本底	高程	LNELV	平均高程	-
	坡度	LNSLOPE	平均坡度	-
	降水	LNRAI	年均降水	+
	气温	LNTEM	年均气温	?
	水资源利用	LNWATER	全社会水资源利用总量	+
区位交通地理	距一级海港距离	LNDIST_PORT1	到最近的一级海港距离	-
	距二级海港距离	LNDIST_PORT2	到最近的二级海港距离	-
	距地级城市距离	LNDIST_CITY	到最近的地级城市距离	-
	高等级道路密度	LNTRAN_DENS	铁路、高速公路和国道密度(线路长度/面积)	+
	区域虚拟变量	REG	东、中和西部分别设定为3,2和1	+
	市县虚拟变量	CITY_COUNTY	市和县分别设定为1和0	+
宏观战略政策	国家战略与宏观区域政策	POLICY	是否是国家战略性政策瞄准区	+
	国家级经济技术开发区		是否设置国家级经济技术开发区	+
	地位与等级		在全国城镇体系中的地位,在全国主体功能区中的功能定位	+
历史基础	期初集约利用水平	LIU_A0	基期年1992年空间集约利用度	+