A Classification of Multidimensional Open Data for Urban Morphology
A Classification of Multidimensional Open Data for Urban Morphology
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DOI：
10.2148/benv.42.3.382
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发表时间：
2016-10
影响因子：
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通讯作者：
A. Alexiou;A. Singleton;P. Longley
中科院分区：
文献类型：
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作者：
A. Alexiou;A. Singleton;P. Longley
通过地理人口学分类来识别社会空间模式已被证明在一系列学科中都是有用的。虽然大多数这些空间分类系统都包含大量的社会经济属性，但可以说几乎没有关于建筑环境或物理空间属性的输入，并且它们与这种背景下的社会经济概况的关系尚未以任何系统的方式进行评估。本研究利用地理数据科学方法，利用开放数据源中此类空间数据日益增加的可用性，探索邻里特征和其他属性的生成。我们采用 SOM（自组织地图）方法来创建多维开放数据城市形态 (MODUM) 的分类，并测试该输出系统地遵循传统社会经济概况的程度。这种分析还可以提供地理空间物理属性的简化结构，该结构可以进一步用作更复杂的社会经济模型的输入。
Identifying socio-spatial pa erns through geodemographic classification has provenutility over a range of disciplines. While most of these spatial classification systems include a plethora of socioeconomic attributes, there is arguably little to no input regarding attributes of the built environment or physical space, and their relationship to socioeconomic profiles within this context has not been evaluated in any systematic way. This research explores the generation of neighbourhood characteristics and other attributes using a geographic data science approach, taking advantage of the increasing availability of such spatial data from open data sources. We adopt a SOM (Self-Organizing Maps) methodology to create a classification of Multidimensional Open Data Urban Morphology (MODUM) and test the extent to which this output systematically follows conventional socioeconomic profiles. Such an analysis can also provide a simplified structure of the physical properties of geographic space that can be further used as input to more complex socioeconomic models.