资源科学 ›› 2016, Vol. 38 ›› Issue (1): 41-49.doi: 10.18402/resci.2016.01.05

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城市土地利用类型与行业单位空间布局关系研究——以吉林省通化市中心城区为例

李文博1(), 王冬艳1, 李红1(), 姜珊1, 石璞1,2, 刘蜀涵1, 陆红3   

  1. 1.吉林大学地球科学学院,长春 130061
    2. Institute of Terrestrial Ecosystems,Swiss Federal Institute of Technology Zurich;CH-8092 Zürich,Switzerland
    3.吉林大学公共计算机教学与研究中心,长春 130061
  • 收稿日期:2015-05-18 修回日期:2015-08-17 出版日期:2016-01-25 发布日期:2016-01-25
  • 作者简介:

    作者简介:李文博,男,吉林长春人,博士生,主要研究方向为土地资源评价与规划管理。E-mail:finehighman@sina.cn

  • 基金资助:
    基金项目:国家自然科学基金资助项目(41201158)

The distribution relationship between urban land-use type and industry units in the central urban area of Tonghua City

LI Wenbo1(), WANG Dongyan1, LI Hong1(), JIANG Shan1, SHI Pu1,2, LIU Shuhan1, LU Hong3   

  1. 1. College of Earth Sciences,Jilin University,Changchun 130061,China
    2. Institute of Terrestrial Ecosystems,Swiss Federal Institute of Technology Zurich,CH-8092 Zürich,Switzerland
    3. Center for Computer Fundamental Education,Jilin University,Changchun 130061,China
  • Received:2015-05-18 Revised:2015-08-17 Online:2016-01-25 Published:2016-01-25

摘要:

掌握区域行业信息以及土地利用类型与行业空间分布之间的联动关系,是指导行业用地供给和实现行业用地集约利用的前提之一。本文基于空间自相关理论,以吉林省通化市中心城区为例对城市地类与行业单位的空间自相关性与空间布局进行梳理,得出结论:①通化市中心城区各地类与行业单位分布均呈空间正相关,Moran’s I系数均随权重距离的增加而减小;在相同尺度条件下,工矿仓储用地、住宅用地、商服用地、公共管理与公共服务用地4种主要地类空间结构性较强;批发和零售业,公共管理、社会保障和社会组织,其他商业与服务业空间结构性较弱;制造业,其他工业与采矿业,其他公共管理服务业基本呈随机分布;②依据行业单位在空间分布特征上均具有明显的相似性与行业产业共性,将其划分为二产行业(制造业,其他工业与采矿业)、三产行业(批发和零售业,其他商业与服务业)和无产行业(公共管理、社会保障和社会组织,其他公共管理服务业)大类进行调控和布局;③通化市中心城区行业类型与落位地类HH聚集区属性基本相符,但存在多数单位落位于与自身行业属性不一致的土地类型区;针对存在合理但与用地属性不符行业单位,设立缓冲混合用地区,并限制行业单位的错误落位现象;④通化市支柱行业中,黑色金属冶炼和压延加工业单位空间集聚现象明显,规划区域内工矿仓储用地应逐步集中,引导形成规模工业区;医药制造业与葡萄酒制造业用地向外迁移出中心区域,行业带上形成主要行业用地聚集点以发挥产业集聚优势。

关键词: 行业用地, 产业结构, 空间自相关, 通化市

Abstract:

Reasonable industry land-supply and intensive industry land-use are formed on the premise of knowing about details of regional industry and distribution relationships between land and industry units. Here,we report the spatial autocorrelation conditions of urban land and industry units and their spatial distribution using the central urban area of Tonghua City as an example. We found that the distribution of urban land and industry units shows a positive spatial autocorrelation and that Moran’s I decreases with an increase in weighted distance. Spatial autocorrelation of mining warehouse land,residential land,commercial services land and public management-services land is significant,as is wholesale and retail,public management social security and folk organizations and other commercial service industry units. Manufacturing,mining and other public service industry units distribute randomly across the study area. All industry units can be incorporated into secundiparity units,tertiary industry units and nonprofit units;in correspondence with mining warehouse land,commercial services land and public management-service land respectively. The attributes of industry units in Tonghua mostly match the land they are located within. Hybrid functional areas should be established for mismatches with reasonable existence,but most mismatches should be avoided by strengthening industry land-use review. Designation and regulation of pillar industry land-use would support and guide industrial development based on regional industry structure. The future spatial distribution of Tonghua steel-smelting units should be more focused and eventually form a scale industrial land zone. Pharmacy and wine-making industry land should be transferred outside the central area and gradually gather in the pillar industry band.

Key words: industry land, industrial structure, spatial autocorrelation, Tonghua City