田晶, 余梦婷, 任畅, 熊富全. 城市道路网元胞模式分析的网络景观指数分析法[J]. 武汉大学学报 ( 信息科学版), 2018, 43(10): 1588-1594. DOI: 10.13203/j.whugis20150640
引用本文: 田晶, 余梦婷, 任畅, 熊富全. 城市道路网元胞模式分析的网络景观指数分析法[J]. 武汉大学学报 ( 信息科学版), 2018, 43(10): 1588-1594. DOI: 10.13203/j.whugis20150640
TIAN Jing, YU Mengting, REN Chang, XIONG Fuquan. Network-Scape Metric Analysis for Celluar Pattern Analysis in Urban Street Networks[J]. Geomatics and Information Science of Wuhan University, 2018, 43(10): 1588-1594. DOI: 10.13203/j.whugis20150640
Citation: TIAN Jing, YU Mengting, REN Chang, XIONG Fuquan. Network-Scape Metric Analysis for Celluar Pattern Analysis in Urban Street Networks[J]. Geomatics and Information Science of Wuhan University, 2018, 43(10): 1588-1594. DOI: 10.13203/j.whugis20150640

城市道路网元胞模式分析的网络景观指数分析法

Network-Scape Metric Analysis for Celluar Pattern Analysis in Urban Street Networks

  • 摘要: 道路网元胞的组成及其配置构成了特定的网络景观,受启发于元胞和景观格局中斑块的相似性,借鉴景观格局分析中的景观指数分析法,提出了一种城市道路网元胞模式分析的新方法——网络景观指数分析法。该方法基于道路类型生成不同类别的元胞,计算网络景观指数,并通过相关分析与因子分析挖掘主要因子,进而解释主要因子及代表指数在道路网模式分析中的含义。应用该方法计算了中国34个城市街道网络的24个指标,发现了4个主要因子:元胞的空间分布与多样性、元胞最大尺寸与延展性差异、元胞平均延展性和元胞平均尺寸与形状复杂度。反映到道路网中,描述了道路的集聚与分散特征、道路类型的多样性、道路网的规则程度等特征。

     

    Abstract: The networks composition and configuration of the different types of cells in street networks constitute specific network-scapes. Inspired by the similarity between cell in road network and patch in landscape ecology, this paper references landscape metrics in landscape pattern analysis, and proposes a new approach for street networks pattern analysis-network-scape metric analysis. The procedure of the approach is to build cells and assign the types based on types of enclosing roads, and then the metrics of network-scape were computed. An exploratory analysis was performed, in which a correlation analysis and factor analysis are combined. We explained the meanings of main factors and representative metrics in the field of street networks analysis. Through this approach, 24 metrics were computed for 34 Chinese urban street networks, and four main factors were found, which are labeled:spatial distribution and diversity, maximum size and elongation variation, average elongation, and average size and shape complexity. These factors can reflect charac-teristics of street networks, including clustering and dispersion, type disversity, and shape regularity.

     

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