Measuring Human-Scale Living Convenience through Multi-Sourced Urban Data and a Geodesign Approach: Buildings as Analytical Units

Living convenience, as a perceptual quality of life, is gradually playing an increasingly important role in the context of seeking livable cities. A high degree of living convenience positively affects urban vitality, livability, and daily physical activities. However, it is hard to achieve a quantitative measurement of this intangible, subjective issue. This study presents a data-informed analytical approach to measuring the human-scale living convenience using multi-sourced urban data and geodesign techniques. Firstly, according to classical theories, living convenience is translated as the co-presentation of accessed number and diversity of urban facilities. Based on that, this study applies multi-sourced urban data, including points of interest (PoIs), buildings, and street networks, to compute the living convenience of each building in the 15 min community-life circle. Through the geoprocessing tools developed by ArcGIS API for Python (ArcPy), the living convenience of millions of buildings in an entire city can be computed efficiently. Kaifeng City from Henan Province, China, is selected as the case study, and the verification from local experts in urbanism shows high accuracy. The capacity to measure intangible perception exhibits the potential for this analytical approach in urban planning practices. Several explorations have been conducted in this direction, including analyzing the spatial heterogeneity in Kaifeng City and planning decision support for bus station arrangement. In short, this study contributes to the development of human-centered planning by providing continuous measurements of an 'unmeasurable' quality across large-scale areas. Insights into the perceptual-based quality and detailed mapping of living conveniences in buildings can assist in efficient planning strategies toward more livable and sustainable urbanism.