|Table of Contents|

Analysis of Spatial Differentiation Characteristics and Influencing Factors of Forestry Enterprises in China(PDF)

《南京师大学报(自然科学版)》[ISSN:1001-4616/CN:32-1239/N]

Issue:
2024年04期
Page:
39-47
Research Field:
空间数据智能研究
Publishing date:

Info

Title:
Analysis of Spatial Differentiation Characteristics and Influencing Factors of Forestry Enterprises in China
Author(s):
Ma Qiang12Ni Honghong34Li Weizhong4Li Jun1Su Xiangxiang1Zhu Xueqing1Liu Jikai125Li Xinwei1235
(1.College of Resources and Environment,Anhui Science and Technology University,Chuzhou 233100,China)
(2.Anhui Agricultural Waste Fertilizer Utilization and Cultivated Land Quality Improvement Engineering Research Center, Chuzhou 233100, China)
(3.Research Office,Anhui Science and Technology University,Chuzhou 233100,China)
(4.College of Forestry,Northwest A&F University,Yangling 712100,China)
(5.Anhui Province Engineering Research Center for Intelligent Cultivation and Processing of Crops,Chuzhou 233100,China)
Keywords:
forestry enterprisesspatial autocorrelationMGWR modelinfluencing factors
PACS:
F326.25
DOI:
10.3969/j.issn.1001-4616.2024.04.005
Abstract:
The analysis of spatial differentiation characteristics and influencing factors of forestry enterprises promotes the overall development of the forestry industry,thereby laying a solid foundation for ecological civilization and economic and social development. Utilizing data from forestry enterprises in China,this paper explores the spatial differentiation characteristics using spatial analysis methods such as average nearest neighbor,local Moran index,and hotspot analysis,compares the precision of results from ordinary least squares(OLS)model and multi-scale geographically weighted regression(MGWR)model,and explores the spatial heterogeneity of factors influencing the distribution of forestry enterprises revealing the influence of different factors. The results show that:(1)The spatial agglomeration of forestry enterprises in China is evident,and the degree of agglomeration has been increasing in recent years.(2)Changes in the local correlation characteristics of forestry enterprises in China are more pronounced,with the distribution quantity of hotspot agglomerations in the Northeast and Southwest shrinking considerably,and hotspot agglomerations in the Southeast consistently maintaining a large-scale.(3)Regarding factors influencing the distribution of forestry enterprises,the number of residents,the number of authorized patents,green land area,garden area,and forest area positively influence distribution. Conversely,highway density and the total amount of imports and exports are mainly negatively correlated with the number of forestry enterprises. Forestry enterprises are more influenced by resource distribution and market demand. Highway traffic does not favor the location of forestry enterprises. The results of this study can support the optimization of the spatial layout of forestry enterprises in China and provide references for the formulation of forestry industry policies and industrial planning.

References:

[1]范水生,陈涵. 林业碳汇产品的意涵特征和价值实现[J]. 学术界,2023(12):195-203.
[2]杨霄. 中国林业对外直接投资、技术创新与林业产业结构升级研究[D]. 北京:北京化工大学,2020.
[3]吕洁华,张滨,张洪瑞. 基于灰色发展决策的林业产业类型的识别研究:以黑龙江省为例[J]. 林业经济问题,2014,34(3):236-242.
[4]赵俊,李滨兵. 浅谈林业企业的社会责任及其信息披露[J]. 经济研究导刊,2018(15):9-10.
[5]申英. 加强生态林业保护促进林业可持续发展的探讨[J]. 现代农业研究,2022,28(7):74-76.
[6]刘婧,甄峰,张姗琪,等. 新一代信息技术企业空间分布特征及影响因素:以南京市中心城区为例[J]. 经济地理,2022,42(2):114-123.
[7]余颖,刘青,李贵才. 深圳高新电子信息企业空间格局演化及其影响因素[J]. 世界地理研究,2020,29(3):557-567.
[8]公维民,张志斌. 西北内陆中心城市生产性服务企业空间格局演变与区位选择:以兰州市为例[J]. 经济地理,2021,41(2):82-91.
[9]宋昌耀,罗心然,席强敏,等. 超大城市生产性服务业空间分工及其效应分析:以北京为例[J]. 地理科学,2018,38(12):2040-2048.
[10]沈静,王少谷,周楚平. 环境公正视角下广州市污染企业分布与区域人口社会特征的时空关系研究[J]. 地理研究,2022,41(1):46-62.
[11]马晓敏,张志斌,公维民,等. 兰州市制造业空间格局演化及驱动因子识别[J]. 地理科学,2023,43(3):519-529.
[12]余军,章坤,谢朝武. 厦门市数字经济核心企业空间分布格局演化及影响因素[J]. 人文地理,2023,38(2):126-136.
[13]王庆晔. 吉林省农产品物流企业时空演变及其影响因素分析[D]. 长春:吉林农业大学,2024.
[14]杨洋,乔家君,郭远智,等. 广东省瞪羚企业空间分布特征及驱动机制[J]. 经济地理,2022,42(8):112-122.
[15]熊友云,张明军,刘园园,等. 中国农业产业化龙头企业空间分布特征:以国家级重点龙头企业为例[J]. 地理科学进展,2009,28(6):991-997.
[16]白如山,章君吉,韦玉秀,等. 阜阳市农业龙头企业空间分布特征挖掘[J]. 阜阳师范学院学报(自然科学版),2019,36(2):95-100.
[17]蒋辉,刘兆阳. 中国农业产业化龙头企业空间分布特征及其影响因素[J]. 吉首大学学报(社会科学版),2020,41(6):94-101.
[18]夏永红,沈文星. 中国林产工业集聚水平测度及演进趋势与产业经济增长:基于 2003—2016年数据的实证分析[J]. 世界林业研究,2018,31(6):42-46.
[19]孔凡斌,王宁,徐彩瑶. 山区林业产业发展对城乡收入差距的影响机制:基于就业与收入中介效应的视角[J]. 自然资源学报,2024,39(1):62-83.
[20]贺灿飞,王文宇,朱晟君. “双循环”新发展格局下中国产业空间布局优化[J]. 区域经济评论,2021(4):54-63.
[21]胡亚丹,徐建华,李治洪. 上海市休闲农业布局及影响因素分析[J]. 长江流域资源与环境,2017,26(12):2023-2031.
[22]向雁,陈印军,侯艳林,等. 河北省休闲农业的空间分布及影响机制[J]. 地理科学,2019,39(11):1806-1813.
[23]王国权,王欣,王金伟,等. 创意休闲农业的空间分布格局及影响因素:以江苏省为例[J]. 江苏农业学报,2021,37(1):219-229.
[24]倪红红,马强,卜元坤,等. 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.
[25]陈进栋,韦素琼,游小珺,等. 基于企业数据的大陆台资农业及农产品加工企业空间分布及机理的比较[J]. 中国农业资源与区划,2024,45(2):156-169.
[26]高姝,刘纪平,郭文华,等. 北京市房地产价格空间分布变化研究[J]. 测绘科学,2021,46(9):150-156.
[27]赵飞,廖永丰. 突发自然灾害事件网络舆情传播特征及影响因素研究[J]. 地球信息科学学报,2021,23(6):992-1001.
[28]杨佳明,安睿,仝照民,等. 基于多尺度地理加权回归的建成环境对通风潜力的影响研究:以武汉市主城区为例[J]. 南京师大学报(自然科学版),2023,46(4):29-39.
[29]OSHAN T M,LI Z,KANG W,et al. MGWR:a python implementation of multiscale geographically weighted regression for investigating process spatial heterogeneity and scale[J]. ISPRS international journal of geo-information,2019,8(6):269.
[30]FOTHERINGHAM A S,YANG W,KANG W. Multiscale geographically weighted regression(MGWR)[J]. Annals of the American association of geographers,2017,107(6):1247-1265.
[31]张城铭,翁时秀,保继刚. 1978年改革开放以来中国旅游业发展的地理格局[J]. 地理学报,2019,74(10):1980-2000.

Memo

Memo:
-
Last Update: 2024-12-15