Abstract: Compact development is one of the most effective solutions for sustainable urbanization under the rapid growth of the urban population. Great efforts have been made to measure urban physical compactness while limited attention has been paid to functional zoning of urban areas. Here, we introduce a novel index, called the functional compactness index (FCI), to quantify urban functional compactness through the integration of geospatial data sources, including Points of Interest (POIs) data, Road Network of OpenStreetMap (RNO) data, and National Polar-orbiting Partnership (NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) nighttime light data. The FCI does not require the analysis of the grid scale and thus, is technically simpler than conventional compactness index (CI). We examined the effectiveness of FCI on estimating urban compactness under four land use scenarios and in four Chinese cities. The results suggest that: (1) the FCI can comprehensively reflect the intensity of human activity, the differentiation between residential zones and other functional zones, and the mixing degree of different functional zones; (2) the FCI is not affected by the service radius of residential zones; (3) the FCI can reflect the overall and local-scale functional compactness of a city; and (4) the FCI can be used to effectively compare spatial characteristics of functional compactness among different cities. In conclusion, the FCI considers the rationality of urban functional layout, which not only is helpful for urban planning, but also enriches the quantitative methods of urban compactness evaluation.

Abstract: The prevalence of overweight and obesity are increasing in many African countries and hence becoming regional public health challenges. We employ satellite-based night light intensity data as a proxy for urbanization to investigate the relationship between urbanization and women's body weight. We use two rounds of the Demographic and Health Survey data from Nigeria. We employ both nonparametric and parametric estimation approaches that exploit both the cross-sectional and longitudinal variations in night light intensities. Our empirical analysis reveals nonlinear relationships between night light intensity and women's body weight measures. Doubling the sample's average level of night light intensity is associated with up to a ten percentage point increase in the probability of overweight. However, despite the generally positive relationship between night light intensity and women's body weight, the strength of the relationship varies across the assorted stages of night light intensity. Early stages of night light intensity are not significantly associated with women's body weight, while higher stages of nightlight intensities are associated with higher rates of overweight and obesity. Given that night lights are strong predictors of urbanization and related economic activities, our results hint at nonlinear relationships between various stages of urbanization and women's body weight.

Abstract: This paper focuses on the methodology for estimating total freight transport activity (FTA) for three countries — China, India and Saudi Arabia — with the objective of building on current state-of-the-art transportation modeling in three key areas: Studying the relationship between nighttime lights (NTL) and FTA allows for an estimation of full transportation datasets for countries where only a few observation points exist or where data is unavailable. Establishing the foundation for future work on how to use this approach in transport flow estimation (origin-destination matrices). Determining whether this approach can be used globally, given the coverage of the satellite data used. The paper uses the KAPSARC Transport Analysis Framework (KTAF), which estimates transport activity from freely available global data sources, satellite images and NTL. It is a tool for estimating freight transport activity that can be used in models to measure the impact of an accelerated transport policy planning approach. The methodology offers a solution to inadequate data access and allows for scenario building in policy planning for transportation. This approach allows for quick estimation of the effects of policy measures and economic changes on transportation activities at a global level. The paper also includes a detailed guide on how to replicate the methodology used in this analysis.