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Defining functional urban regions in Bahia, Brazil, using roadway coverage and population density variables

机译:使用道路覆盖率和人口密度变量定义巴西巴伊亚州的功能性城市区域

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摘要

The concept of Functional Urban Regions (FURs), also called Metropolitan Regions (MRs), is not simple. It is clear, though, that they are not simply a combination of adjacent municipalities or areas. Different methods can be used for their definition. However, especially in developing countries, the application of some methods is not possible, due to the unavailability of detailed data. Alternative approaches have been developed based on spatial analysis methods and using variables extracted from available data. The objective of this study is to compare the results of two spatial analysis methods exploring two variables: population density and an indicator of transport infrastructure supply. The first method regards Exploratory Spatial Data Analyses tools, which define uniform regions based on specific variables. The second method used the same variables and the spatial analysis technique available in the computer program SKATER - Spatial "K'luster Analysis by Tree Edge Removal. Assuming that those classifications of regions with similar characteristics can be used for identifying potential FURs, the results of all analyses were compared with one another and with the 'official' MR. A combined approach was also considered for comparison, but none of the results match the existing MR boundaries, what challenges the official definitions.
机译:功能性城市区域(FUR)(也称为大城市区域(MRs))的概念并不简单。但是很明显,它们不只是相邻市政当局或地区的结合。可以使用不同的方法进行定义。但是,由于没有详细数据,特别是在发展中国家,无法应用某些方法。基于空间分析方法并使用从可用数据中提取的变量,已经开发出替代方法。这项研究的目的是比较两种探索两个变量的空间分析方法的结果:人口密度和运输基础设施供应的指标。第一种方法涉及探索性空间数据分析工具,该工具根据特定变量定义统一区域。第二种方法使用相同的变量和计算机程序SKATER中可用的空间分析技术-通过“树边缘去除”进行空间“ K'luster分析”。假设那些具有相似特征的区域分类可用于识别潜在的FUR,则结果所有分析均与“官方” MR进行了比较,也考虑采用一种综合方法进行比较,但结果均不符合MR的现有边界,这对官方定义提出了挑战。

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