关键词：公共空间、活动模式、城市可持续发展、网络指数、图像理论
摘 要：本研究探讨了如何产生对预测性用户流模型的需求，这种模型使设计师能够预测公共空间中的人类活动。研究通过观察、采访和照片分析收集数据，以评估现状和回答研究问题。这些数据有两个目的：第一，这些数据有两个目的：第一，根据几个月的实际数据，校准准确的用户活动模式，检查人类活动与空间之间的关系；第二，因为数据是纵向的，来测试我们的预测有多准确。如果城市知道活动模式的变化发生在哪里，以及这些变化在哪里影响公共空间的物理维度，它就可以优先投资更好的公共区域，并要求开发商为更好的公共空间做出贡献，而不是拓宽道路。
Abstract:This study examined how to generate demand for predictive user flow models, which enable designers to anticipate human activity in public spaces. Data were collected via observations, interviews, and photo analysis to assess the status quo and answer study questions. These data serve two purposes: first, to calibrate an accurate user activity pattern, based on actual data for many months, to examine the relationship between human activities and space, and second, because the data is longitudinal, to test how accurate our forecast is. If the city knows where changes in activity patterns occur and where those changes affect the physical dimension of public space, it can prioritize investments in better public areas and ask developers to contribute to better public spaces rather than broader roadways.
Key: Public space, Activity model/ pattern, Urban sustainable development, Network indices, Graph theory
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