中国粮食主产区耕地利用效率时空格局演变及影响因素——基于180个地级市的实证研究

doi:10.18402/resci.2017.04.03

摘要/Abstract

摘要：

本文通过构建DEA模型测度了1994-2014年全国粮食主产区13个省份180个城市的耕地利用效率,利用空间统计模型分析其时空格局演变特征,并运用地理加权回归模型探究了粮食主产区耕地利用效率时空演变的主要影响因素。研究结果表明：①1994-2014年,粮食主产区耕地利用效率总体上呈波动上升的趋势,且具有明显的阶段性变化特征,但整体效率值并不高;②全国粮食主产区耕地利用效率空间差异性显著;粮食主产区耕地利用效率热点区域空间极化现象明显,且随着时间的推移而逐渐变化,呈现出“两核集聚”、“多核极化”、“两核极化”的演变特征;③自然条件是粮食主产区耕地利用效率时空演变的基础因素,耕地资源禀赋、地区经济发展水平、农业生产条件是重要影响因素,而地区科技水平对耕地利用效率的作用不断增强。

关键词: 耕地利用效率, 时空格局, 演变特征, 影响因素, 粮食主产区, 中国

Abstract:

Cultivated land utilization efficiency was measured and evaluated using the method of DEA （data envelopment analysis）for 180 cities in the major grain producing area of China. At the same time,ArcGIS was used to explore the spatiotemporal characteristics of cultivated land utilization efficiency evolution. The spatial distribution and driving factors are discussed using Geographically Weighted Regression（GWR）. We found that the rising trend of cultivated utilization efficiency appeared in major grain producing areas over the whole period from 1994 to 2014,which had significant periodic variation characteristics with low values. There was significant spatial heterogeneity of cultivated land use efficiency in a major grain producing area. It could be found that spatial polarization appeared in hotspot areas of cultivated land use efficiency,and gradually changed over time. Hotspot areas diffused from “two core” clustering to “multicore” clustering,and then to “two core” clustering. The spatiotemporal characteristic evolvement of cultivated land use efficiency resulted from the comprehensive effects of natural conditions,cultivated land resource endowments,regional economic development level and agricultural production conditions.

Key words: cultivated land utilization efficiency, spatiotemporal pattern, evolvement, driving factors, major grain producing area, China

张立新, 朱道林, 谢保鹏, 杜挺, 王兴. 中国粮食主产区耕地利用效率时空格局演变及影响因素——基于180个地级市的实证研究[J]. 资源科学, 2017, 39(4): 608-619.

Lixin ZHANG, Daolin ZHU, Baopeng XIE, Ting DU, Xing WANG. Spatiotemporal pattern evolvement and driving factors of cultivated land utilization efficiency of the major grain producing area in China[J]. Resources Science, 2017, 39(4): 608-619.

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指标	变量	指标说明	备注
投入指标	I₁	耕地面积	反映耕地利用情况
	I₂	第一产业从业人员	反映劳动力投入情况
	I₃	农用化肥使用量	表示生产投入的资本部分
	I₄	农业机械总动力	表示生产投入的资本部分
产出指标	O₁	农业产值	反映农业生产情况
	O₂	粮食总产量	反映农业生产情况

具体指标（变量）	指标说明	变量类型	指标预期方向
耕地复种指数（MULC）	农作物总播种面积与耕地面积之比	连续变量	+
耕地质量等别（QUALITY）	依据各县耕地质量等别测算出的加权平均值	连续变量	-
人均GDP（PCGDP）	人均GDP	连续变量	+
灌溉指数（IRRIGA）	灌溉面积与耕地面积之比	连续变量	+
科技投入（TECL）	地区科技支出占财政支出的比例	连续变量	+

	1994年	2004年	2014年
Moran's I	0.118 4	0.163 5	0.243 0
期望值	-0.053 5	-0.053 5	-0.053 5
Z得分	5.817 2	7.929 7	9.598 4
P检验	0.001	0.001	0.001

变量	1994年	2004年	2014年
Cond	1.165~142.365	10.249~127.714	20.466~159.278
MULC	0.175~0.696***	0.130 ~0.528***	0.232~0.838***
	（0.466）	（0.341）	（0.537）
QUALITY	-0.335~-0.194***	-0.285~-0.081***	-0.360~0.213***
	（-0.252）	（-0.235）	（-0.275）
PCGDP	0.117~0.310**	0.057~0.182**	0.200~0.428**
	（0.225）	（0.150）	（0.315）
IRRIGA	-0.303 ~0.211**	-0.247 ~0.235**	0.113~0.264**
	（0.139）	（0.123）	（0.190）
TECL	-0.200~0.041*	-0.013~0.101*	0.167~0.378*
	（0.011）	（0.093）	（0.205）
Bandwidth	1.703	1.994	2.355
Residual Squares	2.688	3.226	4.193
Effective Number	26.490	39.735	45.033
Sigma	0.129	0.335	0.206
AICc	266.664	158.329	146.967
R²	0.710	0.795	0.801
Adjusted R²	0.664	0.750	0.774