Journal of Geo-information Science, Volume. 22, Issue 5, 1033(2020)

The Calculation and Visual Optimization Method of Spatial Dynamic Agglomeration Evolution of Urban Creative Industries

Qi ZHOU and Changchun GAO*
Author Affiliations
  • Donghua University, Sunrise School of Business Administration, Shanghai 200051, China
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    Figures & Tables(20)
    Visual flow chart of dynamic clustering DBICP image in urban creative industry zone
    Visual flow chart of dynamic clustering DBICP image in urban creative industry zone
    Extraction results of DBSCAN algorithms
    Spatial Clustering and Merging Strategy of DBICP Algorithms
    Comparison of clustering 1effect before and after improvement of DBICP algorithm(Putuo District, Shanghai)
    DBICP algorithm clustering optimization effect
    DBICP algorithm Threshold color value planning optimization
    DBICP Optimal path demonstration images
    Pattern flow chart of ant colony algorithm
    Average path length and best path length effect diagram
    A preliminary linear trajectory of creative industry spatial agglomeration based on DBICP algorithm
    Image visualization based on browser strategy
    E-charts spatial aggregation dynamic interface search results in Putuo District, Shanghai
    E-charts spatial agglomeration dynamic global interface search results in Pudong District, Shanghai
    E-charts spatial aggregation dynamic global interface search results in Xujiahui District, Shanghai
    • Table 1. Index set of key influencing factors based on spatial dynamic agglomeration of Urban Creative Industry Zone

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      Table 1. Index set of key influencing factors based on spatial dynamic agglomeration of Urban Creative Industry Zone

      主范畴与核心范畴关系因素符号属性指标说明
      Q1投资需求因素Investment当前投资环境的总需求量,随企业组织创新行为而改变
      Q2企业数量因素Number of enterprises该模型中考虑的各创意产业区内企业的迁徙数目
      Q3租金水平因素Rent租赁办公空间需要的资金
      Q4交通车辆因素transportation随着创意园核心区域辐射半径车流量变化而变化
      Q5教育水平因素Education随着创意园区内企业技术教育水平的变化而变化
      Q6消费要求因素Consumption随着创意园区内消费客群水平的变化而变化
      Q7零售产值因素Retail outp value随着创意园区内总体财政支持水平的变化而变化
    • Table 2. Attribute classification of traffic flow gate types

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      Table 2. Attribute classification of traffic flow gate types

      序号属性说明
      1KKID卡口ID
      2DIRECTION、FXBH方向编号
      3VEHICLE TYPE车辆类型
      4LICENSE PLATE NUMBER车牌号
      5PEAK TRAVEL HOURS出行峰值\小时
      6KK TYPE卡口类型
      7LNG经度
      8LAT纬度
    • Table 3. Data selection of traffic flow

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      Table 3. Data selection of traffic flow

      卡口类型坐标位置(选取骨干路网)经纬度/ °(选取骨干路网)出行高峰合计/(辆/h)
      交通十字卡口1KKID01外环高速与沪嘉高速交叉口121.365°E, 31.293°N西向东4705 东向西3225 南向北4641 北向南3927
      2KKID02 真南路与古浪路交叉口121.371°E, 31.290°N西向东2886 东向西2140 南向北1414 北向南2954
      3KKID03 真北路与真南路交叉口121.399°E, 31.274°N西向东3970 东向西5288 南向北5905 北向南4444
      4KKID04 桃浦路与曹杨路交叉口121.410°E, 31.267°N西向东4293 东向西2777 南向北3500 北向南6121
      5KKID05 桃浦路与真北路交叉口121.399°E, 31.265°N西向东4473 东向西2940 南向北3803 北向南6484
      6KKID06 武宁路与真北路交叉口121.398°E, 31.251°N西向东5348 东向西4949 南向北5100 北向南6222
      7KKID07 武宁路与梅岭北路交叉口121.405°E, 31.247°N西向东3888 东向西4112 南向北6001 北向南4885
      8KKID08 武宁路与曹杨路交叉口121.415°E, 31.251°N西向东3230 东向西4029 南向北5949 北向南5181
      9KKID09 武宁路与东新路交叉口121.425°E, 31.247°N西向东3511 东向西5390 南向北4717 北向南4481
      10KKID10 宁夏路与金沙径路交叉口121.419°E, 31.237°N西向东2900 东向西4227 南向北5100 北向南4213
      11KKID11 泸定路与金沙径路交叉口121.261°E, 31.393°N西向东4143 东向西4920 南向北5028 北向南4009
      12KKID12 泸定路与云岭东路交叉口121.393°E, 31.228°N西向东4440 东向西3889 南向北4005 北向南3900
      13KKID13 镇坪路与光复西路交叉口121.438°E, 31.251°N西向东4200 东向西3592 南向北5504 北向南3742
      14KKID14 沪太路与志丹路交叉口121.438°E, 31.278°N西向东4760 东向西3300 南向北5800 北向南4172
      15KKID15 武宁路与中宁路交叉口121.419°E, 31.251°N西向东3242 东向西3121 南向北4839 北向南4416
    • Table 4. Preliminary geographic information of POI BUBBE-SET spatial aggregation (Putuo District)

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      Table 4. Preliminary geographic information of POI BUBBE-SET spatial aggregation (Putuo District)

      kkType卡口类型地理区域经纬度/ °搜索条目数量/个
      卡口12M50创意园集聚区域121.393°E, 31.228°N667 890
      卡口13长风创意园集聚区域121.438°E, 31.251°N4 328 761
      卡口3上海金沙3131创意园121.398°E, 31.251°N3 897 201
      卡口6上海艺法创意园121.415°E, 31.251°N3 654 980
    • Table 5. Comparisons and evaluation based on several algorithms

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      Table 5. Comparisons and evaluation based on several algorithms

      指标说明公式编号参数计算值
      城市区域动态集聚连接度评估创意产业空间集聚的成熟度,路径连接度越高,网络越成熟J=2MN(7)N为区域地理网络中的节点数量,Mi为第i节点邻接的边数,J为网络总边数5.01
      城市区域动态集聚非直线系数两点间地理空间距离与其直线距离的比值,越接近1连接越便捷R=msubsupmsubsupLÜmsubsupmsubsupSÜ(8)Lij表示节点i到节点j的地理路径实际长度,Sij表示节点i和j间直线距离1.63
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    Qi ZHOU, Changchun GAO. The Calculation and Visual Optimization Method of Spatial Dynamic Agglomeration Evolution of Urban Creative Industries[J]. Journal of Geo-information Science, 2020, 22(5): 1033

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    Paper Information

    Received: Nov. 5, 2019

    Accepted: --

    Published Online: Nov. 12, 2020

    The Author Email: GAO Changchun (qiweekend@163.com)

    DOI:10.12082/dqxxkx.2020.190661

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