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 pr...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.展开更多
文摘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.
