Integrated multivariate data analysis for Urban Sustainability Assessment, a case study of Casablanca city

Abstract

• The satellite images and census data are good information sources for urban management and development. • The PCA method is robust, flexible, and provides an accurate outcome in the case of a large number of indicators. • The population density is one of the main driving forces of urban sustainability. • The urban sustainability is inadequate in 50% of Casablanca city containing two-thirds of the whole urban population. In the last few years, the world's urban population has significantly increased and it is expected to undergo a continuous accelerated growth. This urban revolution confronts us with real challenges to promote urban sustainable development and has significant effects on socioeconomic development and the urban environment. This research suggests an approach to assess urban sustainability (US) based on the integration of census information, GIS, and remote-sensing data, which can support urban planners and decision-makers in broad environmental and socioeconomic perspectives. Five environmental indices retrieved from Landsat-8 imagery were coupled with eight general census socioeconomic indicators using Principal Component Analysis (PCA). PCA produced three components, and each one was considered a unique urban sustainability aspect covering social, economic, and/or environmental dimensions. Furthermore, the obtained result was exploited to develop a synthetic US index at the commune level with the main aim to assess urban sustainability and its spatial distribution. The outcome depicts that the US is adequate in 50% of Casablanca city, which contains nearly the third of the urban population. This research remains so promising and can be considered by urban planners as a reference to take necessary actions to improve sustainability, resilience, and well-being in the most vulnerable communes.