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An automated and adaptable approach for characterizing and partitioning cities into urban structure types

机译：一种自动化和适应性方法，用于将城市分区和分区城市结构类型

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摘要

Recently a growing number of investigations is dealing with the characterization and partitioning of urban agglomerations into urban structure types (USTs) based on remote sensing data. Since the USTs of interest are usually chosen with respect to the research question, application and type of urban agglomeration there is a need for a flexible and adaptable approach for automatic UST classification. In this study we identify the commonalities of published approaches and derive requirements and tasks to deal with in UST classification. Based on this, we focus on the development of a UST classification system that is highly automated, flexible and adaptable to enable a wide applicability.
机译：最近，越来越多的调查是根据遥感数据的表征和分区城市凝聚到城市结构类型（USTS）。由于兴趣的UST通常是关于研究问题，所应用和城市集群的应用和类型需要一种灵活和适应性的自动UST分类方法。在这项研究中，我们确定了在UST分类中识别出版方法的共同性并导出要求和任务。基于此，我们专注于开发高度自动化，灵活，适应性的UST分类系统，以实现广泛的适用性。

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