陕西省林业企业时空格局演变及影响因素分析

doi:10.12118/j.issn.1000-6060.2023.175

摘要/Abstract

摘要：

林业是生态文明建设的主战场，也是经济社会发展的重要基础产业。林业企业作为林业产业经济的具体落脚点，其时空演变规律和影响因素分析可以辅助决策者合理安排林业产业布局，促进林业产业良好发展。基于2000—2020年陕西省林业企业数据，采用平均最近邻、标准差椭圆、核密度分析等地理信息系统（GIS）空间分析方法，分析了陕西省林业企业的时空演变特征；运用普通最小二乘法（OLS）模型和地理加权回归（GWR）模型，探讨了107个县区林业企业分布数量影响因素的空间异质性，揭示了不同因素的影响作用及空间分异特征。结果表明：（1）陕西省林业企业数量增长幅度逐渐加大，空间格局具有明显的集聚特征且集聚程度不断增强。（2）陕西省林业企业空间分布整体向东偏移，但核密度热点区域始终位于西安市，并与咸阳市形成连片的高值区域。（3）陕西省林业企业经营范围鲜明，以林业相关的“销售”和“服务”为主，随着产业结构进一步优化，从初加工、再加工到深加工，林业企业技术含量不断增加，并扩增相关服务项目。（4）从林业企业分布数量的影响因素看，社会消费品零售总额、地区生产总值、常住人口数量等外部社会经济条件对于林业企业分布数量的影响强度最大，但第一产业增加值占比、林地面积等产业条件也具有正向作用，企业注册资本平均值、园地面积、公路密度与林业企业数量的负相关性，反映了同类型企业的竞争压力、体现了林业企业面积较大的客观现实，也与林业产业中第一产业比重大的特点契合。陕西省林业企业分布的影响因素存在显著空间分异，政府及相关部门在制定产业政策时需要考虑不同地区的特点，采取针对性措施，促进林业产业的健康协调发展。

关键词: 陕西省, 林业企业, 空间分析, 时空演变, 地理加权回归模型

Abstract:

Forestry is a pivotal domain in the construction of ecological civilization and constitutes a fundamental industry for economic and social advancement. Functioning as a specific cornerstone of the forestry industry economy, analyzing the spatial evolution and influencing factors is crucial for decision makers to judiciously organize the forestry industry layout and foster its development. Drawing on data spanning from 2000 to 2020 for forestry enterprises in Shaanxi Province, China, this study employs geographic information system (GIS) spatial analysis techniques, including average nearest neighbor, standard deviation ellipse, and kernel density analysis, to scrutinize the spatial and temporal evolution characteristics of these enterprises. In addition, ordinary least squares regression and geographically weighted regression models were used to explore the spatial heterogeneity of factors influencing the distribution of forestry enterprises across 107 counties and districts. This study unveils the influence of various factors and spatial differentiation characteristics. The findings reveal the following: (1) The number of forestry enterprises in Shaanxi Province has steadily increased, demonstrating a discernible agglomeration pattern with strengthening degrees of concentration. (2) The overall spatial distribution of forestry enterprises in Shaanxi Province shifts eastward, yet the central nuclear density hotspot remains consistently situated in Xi’an City, forming a contiguous high-value area with Xianyang City. (3) Forestry enterprises in Shaanxi Province exhibit a distinct business scope, primarily revolving around sales and services related to forestry. As the industrial structure is optimized, there is an evident increase in the technical content of forestry enterprises, accompanied by the expansion of related service offerings from primary processing to reprocessing and deep processing. (4) Regarding the influencing factors of forestry enterprise distribution, socioeconomic factors such as total retail sales of consumer goods, gross regional product, and the number of permanent population exert the most substantial impact. However, industry-related factors, including the proportion of primary industry value added and forest area, also positively influence the distribution of forestry enterprises. Conversely, a negative correlation was observed between the registered capital average of enterprises, garden plot area, highway density, and the number of forestry enterprises, indicative of competitive pressures and the reality of expansive land area the forestry enterprises owned. These outcomes align with the characteristics of the forestry industry, which is predominantly driven by the primary sector. The factors influencing of forestry enterprise distribution in Shaanxi Province exhibit notable spatial heterogeneity. Consequently, when formulating industrial policies, it is imperative for the government and relevant departments to consider regional nuances and adopt targeted strategies to facilitate the healthy and coordinated development of the forestry industry.

Key words: Shaanxi Province, forestry enterprise, spatial analysis, temporal and spatial evolution, geographically weighted regression model

倪红红, 马强, 卜元坤, 杨小轩, 李卫忠. 陕西省林业企业时空格局演变及影响因素分析[J]. 干旱区地理, 2023, 46(12): 2098-2110.

NI Honghong, MA Qiang, BU Yuankun, YANG Xiaoxuan, LI Weizhong. Spatiotemporal distribution pattern evolution and influencing factors of forestry enterprises in Shaanxi Province[J]. Arid Land Geography, 2023, 46(12): 2098-2110.

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年份	平均观测距离/km	预测平均距离/km	最近邻指数	Z得分	分布特征
2000	7.5549	18.4191	0.4102	-17.2612	集聚
2005	5.1422	14.3823	0.3575	-25.2784	集聚
2010	3.3019	10.2568	0.3219	-38.1076	集聚
2015	1.7702	6.1472	0.2880	-67.3693	集聚
2020	0.7486	3.0002	0.2495	-149.0122	集聚

变量	定义	单位
交通便利性	公路密度	km
劳动力数量	常住人口数量	人
企业发展状况	企业注册资本平均值	元
经济发展水平	地区生产总值	10⁸元
产业结构	第一产业增加值占比	%
生产条件	林地面积	km²
	园地面积	km²
市场规模	社会消费品零售总额	10⁸元

变量	系数	标准误差	T检验	P值	方差膨胀因子（VIF）
常数项	-40.344	19.048	-2.118	0.038^*	-
公路密度	-72.188	59.328	-1.217	0.227	3.838
常住人口数量	155.821	68.278	2.282	0.025^*	4.481
企业注册资本平均值	-8.476	35.334	-0.240	0.811	1.579
地区生产总值	309.740	93.012	3.330	0.001^*	4.957
第一产业增加值占比	76.307	32.972	2.314	0.023^*	1.778
林地面积	52.656	23.592	2.232	0.028^*	1.488
园地面积	-30.376	35.291	-0.861	0.391	1.582
社会消费品零售总额	806.909	109.080	7.397	0.000^*	7.878

变量	中位数	最小值	最大值	均值
公路密度	-61.610	-117.506	-37.423	-63.653
常住人口数量	145.524	115.798	167.323	145.715
企业注册资本平均值	-15.738	-33.024	28.795	-12.750
地区生产总值	443.244	132.537	506.701	410.001
第一产业增加值占比	73.372	41.103	89.019	71.560
林地面积	65.682	25.793	79.107	62.633
园地面积	-25.146	-34.316	-9.469	-24.247
社会消费品零售总额	719.808	667.718	963.479	742.170