The impact of Built Environment Characteristics on Metropolitans Energy Consumption: An Example of Greater Cairo Metropolitan Region

The spatially heterogeneous and double-edged effect of the built environment on commuting distance: Home-based and work-based perspectives

Rich literature has examined the impact of the built environment on commuting distance. Linear models assume that the influence of the built environment is spatially homogeneous. However, given the spatial heterogeneity of urban space, conclusions might be different or even be contrary. The influence of the built environment might also be different by home and work locations. To explore the spatially heterogeneous effect of the built environment from both home-based and work-based perspectives, this study applied large-scale cellular cellphone data in Guangzhou, China. Commuting was measured by decay parameters of probabilistic distributions of commuting distances. Geographically weighted regression models were applied to examine the spatially heterogeneous effect, differentiated by home-based and work-based perspectives. Results confirmed that the impact of the built environment on commuting distance is spatially heterogeneous. The urban space is classified into clusters of central areas, inner suburbs, and outer suburbs. Results also revealed the double-edged effect of the built environment. Residential population, recreation facilities, and mixed development are residence-attractive factors that increase the home-based commuting distance and decrease the work-based commuting distance. Work population and transport facilities are work-attractive factors that decrease home-based commuting distance and increase work-based commuting distance. The results further provide evidence to support area-based policies in urban planning practice.

Deep learning: To better understand how human activities affect the value of ecosystem services-A case study of Nanjing

The value of ecosystem services is affected by increasing human activities. However, the anthropogenic driving mechanisms of ecosystem services are poorly understood. Here, we established a deep learning model to approximate the ecosystem service value (ESV) of Nanjing City using 23 socioeconomic factors. A multi-view analysis was then conducted on feasible impact mechanisms using model disassembly. The results indicated that certain factors had their own significant and independent effects on ESV, such as the proportion of water areas in the land-use structure and the output value of the secondary industry. The proportion of ecological water should be increased as much as possible, whereas the output value of the secondary industry should be reasonably controlled in Nanjing. Other intrinsically related factors were likely to be composited together to affect ESV, such as industrial water consumption and industrial electricity consumption. In Nanjing, simultaneously optimizing socio-economic factors related to city size, resources, and energy use efficiency likely represents an effective management strategy for maintaining and enhancing regional ecological service capabilities. The results of this work suggest that deep learning is an effective method of deepening studies on the prediction of ESV trends and human-driven mechanisms.

Traffic impact studies committed to sustainability: The case of Rio de Janeiro

This article investigates whether the traditional approaches to Traffic Impact Studies (TISs) have evolved to meet the current needs of a society increasingly concerned with sustainability, especially in Brazil. For this purpose, we conducted a comprehensive literature review to identify the main sustainability aspects that should be covered by these studies, including the most suitable analytic techniques for this purpose, in particular for traffic simulation. We then prepared a proposal for classifying traffic impact studies and applied it in a specific case, in the city of Rio de Janeiro, the study of the Porto Maravilha port district revitalization project. This enabled understanding the current state of the practice of these studies in the country, indicating they are in general very poor, justifying the need for improvements.