arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2005.02272physics.soc-ph
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基于空间熵的城市增长与形态模型

Modeling Urban Growth and Form with Spatial Entropy

Yanguang Chen

摘要:

熵是定义分维的物理基础之一,广义分维是由Renyi熵定义的。利用分形维数可以描述城市的生长、形态和空间复杂性。许多分形模型和测量已被提出用于城市研究。然而,分形维数应用的前提是要找到城市的标度关系。在没有标度性的情况下,我们可以利用熵函数和测量。本文主要研究如何用空间熵来描述城市增长。通过与城市分维增长模型的类比,可以推导出一对熵增长模型,并构造一组基于熵的测度来描述城市增长过程和增长模式。首先,利用逻辑斯蒂函数和玻尔兹曼方程来模拟城市增长的熵增长曲线。其次,采用基于空间熵的一系列指标来表征城市形态。将多重分形维数谱推广到空间熵谱。结论如下。熵与分维在城市研究中既有交叉又有不同的应用领域。因此,对于给定的空间测量尺度,为了简单起见,分形维数通常可以用空间熵代替。本文所提出的城市空间熵模型和度量方法对于将熵和分维纳入城市空间分析的同一框架,理解城市空间复杂性具有重要意义。

英文摘要:

Entropy is one of physical bases for fractal dimension definition, and the generalized fractal dimension was defined by Renyi entropy. Using fractal dimension, we can describe urban growth and form and characterize spatial complexity. A number of fractal models and measurements have been proposed for urban studies. However, the precondition for fractal dimension application is to find scaling relations in cities. In absence of scaling property, we can make use of entropy function and measurements. This paper is devoted to researching how to describe urban growth by using spatial entropy. By analogy with fractal dimension growth models of cities, a pair of entropy increase models can be derived and a set of entropy-based measurements can be constructed to describe urban growing process and patterns. First, logistic function and Boltzmann equation are utilized to model the entropy increase curves of urban growth. Second, a series of indexes based on spatial entropy are used to characterize urban form. Further, multifractal dimension spectrums are generalized to spatial entropy spectrums. Conclusions are drawn as follows. Entropy and fractal dimension have both intersection and different spheres of application to urban research. Thus, for a given spatial measurement scale, fractal dimension can often be replaced by spatial entropy for simplicity. The models and measurements presented in this work are significant for integrating entropy and fractal dimension into the same framework of urban spatial analysis and understanding spatial complexity of cities.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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