Objective well-being level (OWL) composite indicator for sustainable and resilient cities

Abstract

Well-being is a critical element of the 2030 Agenda for Sustainable Development Goals. Given the complexity of the concept of well-being, it follows that its measurement requires complex, multivariate methods that can characterize the physical, economic, social and environmental aspects along with the mental state of a city. Although it is not sufficient to carry out settlement-level analyses to make cities inclusive, safe, resilient and sustainable. It is necessary to understand patterns within settlements. This work aims to present how the urban macrostructure of urban well-being indicators can be estimated based on GIS-based multilayer analysis. Open-source data, e.g. road networks, points of interest, green spaces and vegetation, are used to estimate urban well-being parameters such as noise levels, air quality and health-related impacts supplemented by climate models to assess urban resilience and sustainability. The proposed methodology integrates 24 models into six categories, namely walkability, environment, health, society, climate change and safety, which are weighted based on a multilevel Principal Component Analysis to minimize information loss for aggregated composite indicators. The study revealed two main components of the macrostructure related to well-being in the studied city: one related to the geometrical features and the other can be derived from the structure of the natural environment. In Veszprém a natural restoration of the detached house area, industrial area and downtown is recommended including developments with green and blue infrastructural elements and nature-based solutions.