For residents, IAT© is a tool to make informed decisions about their life choices (assessing a place they live, deciding to move houses, moving into a new city) based on the accessibility of different types of infrastructure and attraction variety as well as air quality data.
IAT© helps to unveil areas with insufficient provision of services or poor connectivity thus helping city officials to move towards optimal urban policy utilizing minimal resources and to propose strategic solutions for specific territories with their unique drawbacks.
For developers IAT© offers an opportunity to assess brown-fields and select suitable areas for future development with the best infrastructure provision level. It also helps to minimize resources needed for construction, especially for utilities.
Based on our method for Izhevsk IAT©
, the Infrastructure Accessibility Tool© for London is developing the approach further by distinguishing the infrastructure into three types (necessary, social and optional) and adding public transport infrastructure evaluation and ecological situation monitoring. We took the concept of three types of infrastructure from the Turku Urban Research Programme's Research Report "A Sense of Place"
, inspired by work of Jan Gehl. According to report, necessary services are most likely to host routine activities (e.g. schools, shops, grocery stores, etc.), optional are most likely host leisure activities (e.g. gyms, museums, spas, etc.) and social most likely host interpersonal activities (e.g. bars, cafés, clubs, etc.). We changed that classification slightly, leaving the core idea: we reclassified culture and leisure to as a social category and added business services to optional.
Air pollution was assessed for three components: NO2, Pm 10, PM 2.5, NO. These indicators were chosen due to the availability of official modeling data, strong health effect, presence of limits on the volume of pollution adopted in the UK. That pollutants chosen are ones which are known to have an effect on health within London and are able to be predicted with this model. We have identified areas of the city where the average air pollution exceeds the permissible concentration.