A Model to Analyze Industrial Clusters to Measure Land Use Efficiency in China

Land Pub Date : 2024-07-16 DOI:10.3390/land13071070
Yanzhe Cui, Yingnan Niu, Yawen Ren, Shiyi Zhang, Lindan Zhao
{"title":"A Model to Analyze Industrial Clusters to Measure Land Use Efficiency in China","authors":"Yanzhe Cui, Yingnan Niu, Yawen Ren, Shiyi Zhang, Lindan Zhao","doi":"10.3390/land13071070","DOIUrl":null,"url":null,"abstract":"An understanding of how land use efficiency and industrial clusters interact helps one to make informed decisions that balance economic benefits with sustainable urban development. The emergence of industrial clusters is a result of market behavior, while the determination of administrative boundaries is a result of government behavior. When these two are not consistent, it can lead to distortions in the allocation of land resources. However, current research on industrial development and land use efficiency is based on agglomeration within administrative regions rather than on industrial clusters. This study addresses this gap by identifying industrial clusters based on the spatial distribution of enterprises and analyzing their impact on land use efficiency. This study uses the density-based spatial clustering of applications with noise (DBSCAN) algorithm to identify industrial clusters, the convex hull algorithm to study their morphology, and spatial econometrics to measure the relationship between land use efficiency and the scale of industrial clusters. The results indicate the following: (1) the density of manufacturing industry (MI) clusters is significantly higher than that of information technology industry (ITI) clusters, and larger industrial clusters tend to be more circular in shape; (2) there is a positive correlation between the scale of industrial clusters and land use efficiency, and industrial clusters with varying levels of land use efficiency are interspersed throughout; (3) significant differences exist between the boundaries of industrial clusters and administrative regions, which could lead to biases when analyzing land use efficiency based on administrative regions. This study provides theoretical support for government policies on improving land use efficiency in China.","PeriodicalId":508186,"journal":{"name":"Land","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Land","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3390/land13071070","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

An understanding of how land use efficiency and industrial clusters interact helps one to make informed decisions that balance economic benefits with sustainable urban development. The emergence of industrial clusters is a result of market behavior, while the determination of administrative boundaries is a result of government behavior. When these two are not consistent, it can lead to distortions in the allocation of land resources. However, current research on industrial development and land use efficiency is based on agglomeration within administrative regions rather than on industrial clusters. This study addresses this gap by identifying industrial clusters based on the spatial distribution of enterprises and analyzing their impact on land use efficiency. This study uses the density-based spatial clustering of applications with noise (DBSCAN) algorithm to identify industrial clusters, the convex hull algorithm to study their morphology, and spatial econometrics to measure the relationship between land use efficiency and the scale of industrial clusters. The results indicate the following: (1) the density of manufacturing industry (MI) clusters is significantly higher than that of information technology industry (ITI) clusters, and larger industrial clusters tend to be more circular in shape; (2) there is a positive correlation between the scale of industrial clusters and land use efficiency, and industrial clusters with varying levels of land use efficiency are interspersed throughout; (3) significant differences exist between the boundaries of industrial clusters and administrative regions, which could lead to biases when analyzing land use efficiency based on administrative regions. This study provides theoretical support for government policies on improving land use efficiency in China.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
衡量中国土地利用效率的产业集群分析模型
了解土地使用效率和产业集群如何相互作用,有助于人们做出明智的决策,在经济效益和城市可持续发展之间取得平衡。产业集群的出现是市场行为的结果,而行政边界的确定则是政府行为的结果。当这两者不一致时,就会导致土地资源分配的扭曲。然而,目前有关工业发展和土地使用效率的研究都是基于行政区域内的集聚,而非产业集群。本研究根据企业的空间分布确定产业集群,并分析其对土地使用效率的影响,从而弥补了这一空白。本研究使用基于密度的带噪声应用空间聚类(DBSCAN)算法识别产业集群,使用凸壳算法研究产业集群的形态,并使用空间计量经济学测度土地利用效率与产业集群规模之间的关系。研究结果表明(1)制造业(MI)产业集群的密度明显高于信息技术产业(ITI)产业集群的密度,且规模较大的产业集群更趋向于圆形;(2)产业集群规模与土地利用效率之间存在正相关关系,且不同土地利用效率水平的产业集群穿插分布;(3)产业集群边界与行政区域之间存在显著差异,这可能导致基于行政区域分析土地利用效率时出现偏差。本研究为中国政府提高土地利用效率的政策提供了理论支持。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Management Impacts on Non-Native Smooth Brome (Bromus inermis Leyss.) Control in a Native Fescue Grassland in Canada Grassland Ecosystem Services: Their Economic Evaluation through a Systematic Review The Impact of Social Capital on Community Resilience: A Comparative Study of Seven Flood-Prone Communities in Nanjing, China Mapping the Functional Structure of Urban Agglomerations at the Block Level: A New Spatial Classification That Goes Beyond Land Use Per Capita Land Use through Time and Space: A New Database for (Pre)Historic Land-Use Reconstructions
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1