Abstract

Today, there is a growing interest in designer-led assessment efforts focused on social performance. While this interest has led to significant developments in our understanding of how people occupy urban public space, the spatial data-collection methodologies that are currently being employed are similar to those used in early foundational studies. This paper explores how advancements in digital automation might expand the designer toolbox and, in turn, help to inform design decision making. To do this, the paper unpacks a recent research project that experimented with an automated tabulation technique using computer vision to visualize the spatial distribution of urban public space users. The goal of the computer-vision output is to help designers observe and identify common social patterns across ten plazas in New York City. A key finding from the study is that the automated data-collection technique employed does not fully replace manual techniques, but is complementary.

摘要

如今，人们越来越关注以设计师为主导的针对社会绩效的评估工作。尽管这种兴趣已导致我们对人们如何占用城市公共空间的理解有了重大发展，但当前正在使用的空间数据收集方法与早期基础研究中使用的方法相似。本文探讨了数字自动化的进步如何扩展设计器工具箱，进而帮助告知设计决策。为此，本文展开了一个最近的研究项目，该项目使用计算机视觉自动制表技术来可视化城市公共空间用户的空间分布。计算机视觉输出的目标是帮助设计人员观察和识别纽约市十个广场中的常见社交模式。