Deriving a Measure for the Environmental Quality of Life of an Ultra-Dense Urban Setting

Abstract

Abstract Quality of life (QOL) is a multidimensional term that encompasses all social, economic, and environmental aspects. While social and economic indicators are readily available in standard census statistics, there is no consensus on environmental indicators due to the broad range of measures available. Environmental aspects of QOL vary depending on the physical setting (spatial), satisfaction (rating), and preference (value). Physical settings can be objectively measured, but rating and value involve personal judgment. This study proposes a measure of the physical environment that allows for flexibility in adjusting personal preferences. The study area consisted of 89 neighborhoods in Hong Kong, representing different degrees of urbanization, that were spatially spread out. The spatial unit of a neighborhood was fixed at 800m x 800m to ensure consistent and meaningful comparisons. The study utilized Geographic Information System (GIS) and Remote Sensing (RS) methods to process four domains of urban morphological characteristics at the neighborhood level from digital maps, aerial photographs, and satellite images: (i) education-health-recreation facilities, (ii) street patterns, (iii) compatible land use diversity, and (iv) building density. Principal Component Analysis was used to further reduce the dimensionality of each domain and derive an Environmental Quality Sub-index (EQ-I) that can be standardized and adjusted based on personal value and preference. The neighborhood EQ-I enables both quantitative and qualitative comparisons through visual graphics. This study illustrates a methodological approach to collapsing multiple variables into a single index and accounting for the differential contribution of weights based on value preference. The method employs direct and objective measures that can be adapted and replicated in other cities to offer standardized yet personalized scores for regional and international comparisons.