NEW POTREE SHADER CAPABILITIES FOR 3D VISUALIZATION OF BEHAVIORS NEAR COVID-19 RICH HEALTHCARE FACILITIES
NEW POTREE SHADER CAPABILITIES FOR 3D VISUALIZATION OF BEHAVIORS NEAR COVID-19 RICH HEALTHCARE FACILITIES
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DOI：
10.5194/isprs-archives-xlvi-4-w4-2021-61-2021
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发表时间：
2021-10
期刊：
影响因子：
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通讯作者：
C. Carey;J. Romero;D. Laefer
中科院分区：
文献类型：
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作者：
C. Carey;J. Romero;D. Laefer
抽象。虽然有关人类在COVID-19高发环境中的行为的数据已被捕获并公开发布，但此类数据的空间组成部分以二维形式记录。因此，建筑环境和自然环境的全部作用不能轻易确定。本文介绍了一种机制，用于2020年春季在纽约市离开COVID-19暴露医疗机构的个人的外出行为的三维（3D）可视化。行为数据被提取并投影到周围区域的3D空中激光扫描点云上，该点云由Potree渲染，Potree是一个现成的开源Web图形库（WebGL）点云查看器。结果是建筑环境的3D热图可视化，其指示表现出特定特征的个体的事件位置（例如，男性与女性;公共交通使用者与私家车使用者）。这些可视化使交互式导航能够通过任何支持WebGL的现代Web浏览器访问空间。以这种方式可视化外出行为可以突出指示环境、人类行为和传染性疾病之间的相关性的模式。使用这些工具的发现有可能识别高暴露区域和表面，如门，栏杆和其他物理特征。通过3D空间上下文提供灵活的可视化功能，可以使分析师能够在广泛的用例中快速提供建议和传达重要信息。本文介绍了这样一个应用程序，以提取必要的公共卫生信息，形成本地化的反应，以减少COVID-19感染和传播率在城市地区。
Abstract. While data on human behavior in COVID-19 rich environments have been captured and publicly released, spatial components of such data are recorded in two-dimensions. Thus, the complete roles of the built and natural environment cannot be readily ascertained. This paper introduces a mechanism for the three-dimensional (3D) visualization of egress behaviors of individuals leaving a COVID-19 exposed healthcare facility in Spring 2020 in New York City. Behavioral data were extracted and projected onto a 3D aerial laser scanning point cloud of the surrounding area rendered with Potree, a readily available open-source Web Graphics Library (WebGL) point cloud viewer. The outcomes were 3D heatmap visualizations of the built environment that indicated the event locations of individuals exhibiting specific characteristics (e.g., men vs. women; public transit users vs. private vehicle users). These visualizations enabled interactive navigation through the space accessible through any modern web browser supporting WebGL. Visualizing egress behavior in this manner may highlight patterns indicative of correlations between the environment, human behavior, and transmissible diseases. Findings using such tools have the potential to identify high-exposure areas and surfaces such as doors, railings, and other physical features. Providing flexible visualization capabilities with 3D spatial context can enable analysts to quickly advise and communicate vital information across a broad range of use cases. This paper presents such an application to extract the public health information necessary to form localized responses to reduce COVID-19 infection and transmission rates in urban areas.