Environment and Planning B: Urban Analytics and City Science

Mitigating carbon emission efforts in urban planning and design phase have become increasingly popular due to climate change. However, it is difficult to verify whether the carbon mitigation target could be achieved for a new city in the absence of quantitative analysis methods. About 100 new cities have emerged every year in the past decades, yet few of them employed low carbon strategies within proper prediction methods. In response, this paper offers an integrated analysis method of assessment and mitigation for urban carbon dioxide (CO₂) of new cities. Building sector, transportation sector, and green land sector are considered as urban CO₂ sources and sink. Life cycle analysis was employed in building sector to estimate its emissions. Based on the current and predicted emission data, a mitigation goal was then set and allocated efficiently through different sectors. To elaborate on this process, a case study of Shanghai Lingang New City was presented. The urban low carbon roadmap was planned and a variety of recommendations concerning policy were offered to assist the local government and policy makers in order to achieve the low carbon development goal as well.

Behaviorally, regret-based choice models implicitly assume that individuals anticipate the amount of attribute-level regret by comparing the attribute levels of a considered choice alternative against the attribute levels of the best or all other choice alternatives. Arguing that the amount of effort depends on attribute variation and number of paired comparisons, we suggest a way of incorporating the effects of these factors into two regret-based choice models. The cognitive effort involved in anticipating the amount of regret in paired comparisons of choice alternatives is incorporated into the scale of the regret function of each alternative. Because more cognitive effort causes higher randomness in the assessment of the amount of regret (i.e. higher variance of error terms), the cognitive effort is expressed as a flexible heteroscedastic scale factor, which is a decreasing function of attribute variation and number of paired comparisons. The models are applied to two different data sets, and compared with a heteroscedastic multinomial logit model. Estimation results of the suggested flexible heteroscedastic random regret models show a significant improvement in predictive performance over their homoscedastic formulations. A similar but smaller improvement is obtained for multinomial logit models. These results imply that the conventional assumption of identically distributed error terms underlying random regret models may not sufficiently reflect the process of anticipating the amount of regret.

This paper discusses a project on the completion of a database of socio-economic indicators across the European Union for the years from 1990 onward at various spatial scales. Thus the database consists of various time series with a spatial component. As a substantial amount of the data was missing a method of imputation was required to complete the database. A Markov Chain Monte Carlo approach was opted for. We describe the Markov Chain Monte Carlo method in detail. Furthermore, we explain how we achieved spatial coherence between different time series and their observed and estimated data points.

Urban sprawl is now a common and threatening phenomenon in Europe, severely affecting environmental and economic sustainability. An analytical characterization and measurement of urban sprawl are required to gain a better understanding of the phenomenon and to propose the possible solutions. Traditional factor analysis techniques, especially Principal Component Analysis and Factor Analysis, have been commonly used. In this paper, we additionally test Independent Component Analysis with the aim to obtain a multidimensional characterization of the sprawl phenomenon. We also use Bayesian Factor Analysis to obtain a single (unidimensional) measuring index of sprawl, which also allows us to obtain the uncertainty of the inferred index, in contrast to traditional approaches. All these techniques have been applied to study the phenomenon of urban sprawl at the municipality level in Valencia, Spain using a wide set of variables related to the characteristics and patterns of urban land use.

In today's developed world, the ability of a city to generate good experiences for its residents and visitors is a main aspect of its attractiveness. A good city is considered to be one in which people feel secure, relaxed, and happy. This article explores the factors that influence the subjective momentary experiences of individuals in the city, while focusing on the impact of spatial variables on these experiences; 91 students living in Jerusalem, Israel, were asked to repeatedly self-report four dimensions of episodic experience, namely, sense of security, happiness, annoyance, and sense of comfort. Reports were sent in real time using a smartphone application during an eight-month period. The results, based on over 5000 experience samples, indicate that subjective momentary experiences, particularly sense of comfort and sense of security, are highly influenced by situational variables and environmental characteristics including type of activity and environment, place characteristics, and company. Surprisingly, personality variables which are considered to be a main determinant of wellbeing and general life satisfaction were found to be non-significant in the multilevel models that were implemented. This finding further supports the notion that momentary experiences greatly differ from general evaluations of subjective wellbeing.

Which urban form factor most affects household electricity consumption? This study investigated the relationships between urban density, community layout, and land use factors and household electricity consumption simultaneously, along with building characteristics and demographic indicators. The study site involved 231 communities located in the former provincial area of Tainan City, Taiwan. Due to the area’s subtropical climate, air conditioning accounts for approximately 40% of the total yearly household electricity consumption. Of the urban form factors examined, greater population density was most strongly associated with lower household electricity consumption, followed respectively by greater urban canyon narrowness, or higher height to width ratios, and greater percentages of vacant space and building land use. Notably, both urban canyons and building land use percentages were associated with decreased consumption only after increasing past threshold levels, specifically a 1.5 height to width ratio and 40.7%, respectively. In addition, building characteristics, namely smaller household living areas and greater building age, were most strongly connected with lower household electricity consumption. In contrast, larger household living areas were linked with decreased household electricity consumption/floor area, revealing the importance of lower energy intensities of sizable scales. Of the demographic indicators studied, higher percentages of older adults were associated with lower household electricity consumption. Concerning urban form, the findings suggest that to reduce residential energy usage in a subtropical climate, buildings should be clustered to maximize the inter-building shadows resulting from narrower urban canyons, while simultaneously increasing non-built land use percentages in the adjacent areas.

This article reports a multi-scale analysis of polycentric urban development in 22 Chinese city-regions. Using fine-grained population data, our analysis contrasts polycentric development patterns at multiple geographical scales. We present a typology of Chinese city-regions based on both (1) their inter-city polycentricity and (2) the intra-city polycentricity of the individual cities that comprise these urban regions. Overall, we find only limited levels of association between inter-city and intra-city polycentricity. The Pearl River and Yangtze River Deltas have high levels of inter-city and intra-city polycentricity. Most city-regions in Central and Western China are characterized by a primate urban system and low levels of inter-city polycentricity. We hypothesize the major economic, political, and geographical processes underlying observed patterns.

The objective is to automate the design of residential layouts as an aid for planners dealing with complex situations. The algorithm COmputational Urban Layout Design, applied to sites with various shapes, is guided by the goal of many mutually accessible residences and can be set to generate orthogonal or irregular road layouts. Using biological principles of genomic equivalence, conditional differentiation and induction, it grows from an embryonic ‘adaptive cell’ into a plan. Cells are ‘genetically identical’ with full development potential and can simultaneously lay roads and residential lots, using the gene set to change cell expression and adapt to local contexts. Cells can be seen as self-propagating agents that sort out their dependencies through local interactions.

When COmputational Urban Layout Design is set to grow a non-orthogonal layout, the plan has winding roads and irregular residential lots. Such a plan achieves the objective of relatively high residential density and accessibility, leading to walkable and coherent communities.