Work precincts are recognized for their significant role as generators of employment and associated commerce within urban areas. This study describes a method for analyzing the physical characteristics of urban work precincts in promoting the health and wellbeing of their occupants. The following physical parameters are analyzed: public transport accessibility, green and blue spaces, food environments, fitness facilities, supermarkets, and grocery stores. The parameters are assessed using quantitative spatial analysis based on street network data, as well as point of interest data acquired from OpenStreetMap (OSM). The streets and their intersections are stored in the OSM database as links and nodes, respectively. The evaluation of the performance metrics involves measuring the street network distance from each node to the closest node of interest for each parameter. The metrics are then combined, forming an urban health and wellbeing index (UHWI), which can be used to compare the performance of different precincts. The method was tested by investigating four work precincts in Sydney, Australia, all hosting a large office building belonging to the same business institution. Our results identified two of the four precincts with a high UHWI and resulted in the identification of one underperforming precinct.

工作区因其在城市地区创造就业和相关商业的重要作用而得到认可。本研究描述了一种分析城市工作区的物理特征以促进其居住者的健康和福祉的方法。分析了以下物理参数：公共交通可达性、绿色和蓝色空间、食物环境、健身设施、超市和杂货店。使用基于街道网络数据的定量空间分析以及从 OpenStreetMap (OSM) 获取的兴趣点数据来评估参数。街道及其交叉口分别作为链接和节点存储在 OSM 数据库中。性能指标的评估涉及针对每个参数测量从每个节点到最近的感兴趣节点的街道网络距离。然后将这些指标结合起来，形成一个城市健康和福祉指数 (UHWI)，可用于比较不同区域的表现。该方法通过调查澳大利亚悉尼的四个工作区进行了测试，所有办公区都拥有属于同一商业机构的大型办公楼。我们的结果确定了四个具有高 UHWI 的区域中的两个，并最终确定了一个表现不佳的区域。都拥有属于同一商业机构的大型办公楼。我们的结果确定了四个具有高 UHWI 的区域中的两个，并最终确定了一个表现不佳的区域。都拥有属于同一商业机构的大型办公楼。我们的结果确定了四个具有高 UHWI 的区域中的两个，并最终确定了一个表现不佳的区域。