Abstract In his classic book “The Image of the City” Kevin Lynch used empirical work to show how different elements of the city were perceived: such as paths, landmarks, districts, edges, and nodes. Streets, by providing paths from which cities can be experienced, were argued to be one of the key elements of cities. Despite this long standing empirical basis, and the importance of Lynch's model in policy associated areas such as planning, work with user generated content has largely ignored these ideas. In this paper, we address this gap, using streets to aggregate filtered user generated content related to more than 1 million images and 60,000 individuals and explore similarity between more than 3000 streets in London across three dimensions: user behaviour, time and semantics. To perform our study we used two different sources of user generated content: (1) a collection of metadata attached to Flickr images and (2) street network of London from OpenStreetMap. We first explore global patterns in the distinctiveness and spatial autocorrelation of similarity using our three dimensions, establishing that the semantic and user dimensions in particular allow us to explore the city in different ways. We then used a Processing tool to interactively explore individual patterns of similarity across these four dimensions simultaneously, presenting results here for four selected and contrasting locations in London. Before drilling into the data to interpret in more detail, the identified patterns demonstrate that streets are natural units capturing perception of cities not only as paths but also through the emergence of other elements of the city proposed by Lynch including districts, landmarks and edges. Our approach also demonstrates how user generated content can be captured, allowing bottom-up perception from citizens to flow into a representation.

中文翻译：

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伦敦街道：使用 Flickr 和 OpenStreetMap 构建城市的交互式图像

摘要 在他的经典著作《城市形象》中，凯文林奇使用实证工作来展示城市的不同元素是如何被感知的：例如路径、地标、地区、边缘和节点。街道通过提供可以体验城市的路径，被认为是城市的关键要素之一。尽管有这个长期存在的经验基础，以及 Lynch 模型在政策相关领域（如规划）中的重要性，但使用用户生成的内容在很大程度上忽略了这些想法。在本文中，我们解决了这一差距，使用街道来聚合与超过 100 万张图像和 60,000 个人相关的过滤用户生成内容，并从三个维度探索伦敦 3000 多条街道之间的相似性：用户行为、时间和语义。为了进行我们的研究，我们使用了两种不同的用户生成内容来源：（1）附加到 Flickr 图像的元数据集合和（2）来自 OpenStreetMap 的伦敦街道网络。我们首先使用我们的三个维度探索相似性的独特性和空间自相关性的全球模式，确定语义和用户维度特别允许我们以不同的方式探索城市。然后，我们使用处理工具以交互方式同时探索这四个维度上的各个相似性模式，在此展示伦敦四个选定且对比鲜明的地点的结果。在深入研究数据以进行更详细的解释之前，确定的模式表明，街道是自然单元，不仅可以将城市感知为路径，还可以通过林奇提出的城市其他元素的出现，包括地区、地标和边缘来捕捉城市的感知。我们的方法还演示了如何捕获用户生成的内容，允许公民自下而上的感知流入表示。