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Automated recognition of urban objects for morphological urban analysis

机译:自动识别城市对象以进行形态学城市分析

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摘要

It has often been suggested that the physical structure of traditional urban settlements represents a time-tested response to the climatic constraints of a given location, particularly in hot-arid or other regions that are characterized by thermally harsh conditions. To test this premise, vernacular urban forms have been analyzed to identify patterns of built morphology which might have developed as a response to prevailing climatic conditions. This approach is often based on visual analysis and subjective and qualitative recognition of climate-related patterns. The current paper presents an alternative approach, using a quantitative methodology to support the systematic and automated recognition of urban morphological patterns. A parametric GIS model was developed for automated recognition of urban objects, employing the ability of GIS to recognize contextual relations among objects and perform a context-based recognition using basic rules that apply to the organization of urban form. The model was statistically tested for its accuracy with satisfying results. A case study is presented to demonstrate the workability of the model and its potential as a quantitative and systematic tool for quantitatively describing the morphology of urban surfaces for urban climate analysis. As a parametric model, it can be modified and applied to a large number of case studies for developing and updating databases of urban morphology, and these can serve as a basis for the recognition of morphological patterns in urban form.
机译:经常有人提出,传统城市住区的物理结构代表了对给定位置的气候限制的时间考验的响应,特别是在热干旱或以热恶劣条件为特征的其他地区。为了测试这一前提,已对白话城市形式进行了分析,以识别可能是对主要气候条件的响应而形成的建筑形态模式。这种方法通常基于视觉分析以及对气候相关模式的主观和定性认识。当前的论文提出了一种替代方法,使用定量方法来支持系统自动识别城市形态模式。开发了用于自动识别城市对象的参数化GIS模型,该模型利用GIS的能力识别对象之间的上下文关系,并使用适用于城市形式组织的基本规则执行基于上下文的识别。对模型进行统计检验,结果令人满意。进行了案例研究,以证明该模型的可行性及其作为定量和系统工具定量描述城市表面形态以进行城市气候分析的潜力。作为参数模型,可以将其修改并应用于大量案例研究,以开发和更新城市形态数据库,这些可以作为识别城市形态模式的基础。

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