Environment and Planning B: Urban Analytics and City Science

Open data have come of age with many cities, states, and other jurisdictions joining the open data movement by offering relevant information about their communities for free and easy access to the public. Despite the growing volume of open data, their use has been limited in planning scholarship and practice. The bottleneck is often the format in which the data are available and the organization of such data, which may be difficult to incorporate in existing analytical tools. The overall goal of this research is to develop an open data-based community planning support system that can collect related open data, analyze the data for specific objectives, and visualize the results to improve usability. To accomplish this goal, this study undertakes three research tasks. First, it describes the current state of open data analysis efforts in the community planning field. Second, it examines the challenges analysts experience when using open data in planning analysis. Third, it develops a new flow-based planning support system for examining neighborhood quality of life and health for the City of Atlanta as a prototype, which addresses many of these open data challenges.

The question of whether multilevel buildings are memorized as volumetric map or collection of floors is central to spatial cognition and wayfinding studies about multilevel buildings. The stacked-floor buildings used in previous studies may limit people’s ability to integrate floors into a volumetric mental map. In this study, we assessed wayfinding and cognitive performances of 31 participants in a multilevel shopping mall with five atriums which provided adequate visual access and smooth floor transitions. (1) In the wayfinding task, we observed path choice for 31 participants in this mall. The participants’ choice for all path segments, also vertical path segments, clearly gravitated toward the most accessible spaces in the whole building, rather than most accessible space within individual floors. (2) Participants were also asked to identify the locations where they can see maximum number of stores. The identified locations can be reliably predicted by objectively measured three-dimensional visibility information, but not two-dimensional visibility information. (3) In the pointing task, participants can accurately point to out-of-sight targets in the same floor and in the different floor, in both azimuth and elevation direction. In sum, those findings suggest that people can memorize a multilevel atrium building as a volumetric map. This study also demonstrates the usefulness of developing three-dimensional configurational variables to explain human spatial behavior and spatial cognition.

Cellular automata-based models have traditionally employed regular grids to represent the geographical environment when simulating urban growth or land use change. Over the last two decades, the scientific community has introduced the use of other spatial structures in an attempt to represent the processes simulated by these models more realistically. Cadastre parcels are a good choice when simulating urban growth at local scales, where pixels or regular cells do not represent the geographic space properly. Furthermore, the implementation and calibration of key factors such as accessibility and suitability have not been sufficiently explored in models employing irregular structures.

This paper presents a fully calibrated model to simulate urban growth: Model for Urban Growth simulation using Irregular Cellular Automata. The model uses the irregular structure of the cadastre and its smallest unit: the cadastral parcel. The factors included are based on the traditional Neighbourhood, Accessibility, Suitability and Zoning Status modelling schema, frequently employed in other models. Each factor was implemented and calibrated for the irregular structure employed by the model, and a new approach was explored to introduce a random component that would reproduce illegal growth. Several versions of Model for Urban Growth simulation using Irregular Cellular Automata were produced to calibrate the model within the period 2000–2010. The results obtained from the simulations were compared against observed growth for 2010, adapting the traditional confusion matrix to irregular space. A new metric is proposed, called growth simulation accuracy, which measures how well the model locates urban growth.

This paper examines the importance of place-making in economic development by evaluating the relationship between specific urban design features – based on Jacobs’ “four generators of diversity” and Ewing and Cervero’s “Five-D’s” – and business sales volume. Despite the increased recognition of the importance of walkable urbanism in recent years, relatively little research has assessed the potential economic development benefits of walkable places. While a few authors have assessed the impact of urban design on property values, this paper fills a gap by examining links between components of walkable built environments and individual business characteristics. This paper uses a Hierarchical Linear Modeling framework to explicitly look at the relationship between neighborhood built environment features at the Census tract level and the sales volume per employee of individual businesses in 2010. The cities of Phoenix and Boston are used as contrasting study sites in order to inspect how larger regional characteristics influence the built environment–performance link. The results indicate that specific features of walkable built environments are positively associated with business performance. However, the relationship between walkable built environments and business performance varies considerably depending on the type of business and city-level context being studied, indicating that significant nuance must be used when considering place-based economic interventions. Although no causal statements can be made about the built environment and business performance, the results of this paper indicate that (in some contexts) design-based place-making initiatives could be used to generate sustainable local economic development.

There has been a recent shift in England towards empowering citizens to shape their neighbourhoods. However, current methods of participation are unsuitable or unwieldy for many people. In this paper, we report on ChangeExplorer, a smart watch application to support citizen feedback, to investigate the extent to which digital wearables can address barriers to participation in planning. The research contributes to both technology-mediated citizen involvement and urban planning participation methods. The app leverages in-situ, quick interactions encouraging citizens to reflect and comment on their environment. Taking a case study approach, the paper discusses the design and deployment of the app in a local planning authority through interviews with 19 citizens and three professional planners. The paper discusses the potential of the ChangeExplorer app to address more conceptual issues, and concludes by assessing the degree to which the technology raises awareness of urban change and whether it could serve as a gateway to more meaningful participatory methods.

Fast urbanization is a common feature of many developing human societies. In many cases, past and present, explosive population growth in cities outstrips the rate of provision of housing and urban services and leads to the formation of informal settlements or slums. Slums are extremely varied in terms of their histories, infrastructure, and rates of change, but they share certain common features: informal land use, lack of physical accesses, and nonexistent or poor quality urban services. Currently, about 1 billion people worldwide live in slums, a number that could triple by 2050 if no practical solutions are enacted to reverse this trend. Underlying most problems of slums is the issue of lack of physical accesses to places of work and residence. This prevents residents and businesses from having an address, obtaining basic services such as water and sanitation, and being helped in times of emergency. Here, we show how the physical layout of any neighborhood can be classified quantitatively in terms of its access topology in a way that is independent of its geometry. Topological indices capturing levels of access to structures within a city block can then be used to define a constrained optimization problem, whose solution generates an access network that makes each structure in the settlement accessible to services with minimal disruption and cost. We discuss the general applicability of these techniques to several informal settlements in developing cities and demonstrate various technical aspects of our solutions. Finally, we discuss how these techniques could be used on a large scale to speed up human development processes in cities throughout the world while respecting their local identity and history.

There is a lack of understanding of how certain characteristics of the urban environment influence an individual’s spatial cognition and familiarity with surrounding areas, and, subsequently, their travel behaviours and how these change over time. This paper aims to address this research gap in exploring the dynamics of individuals’ spatial cognitions by observing the changes of respondents’ familiar areas over time, and investigating the possible determinants that constitute respondents’ familiar areas. Panel data, containing two-week travel diaries and maps of familiar areas, were collected in four different waves over a seven-month period for 55 individuals in Stockholm, Sweden. The reported familiar areas for each individual were digitised into quantifiable variable form and further analysed by applying dynamic binary probit and linear regression models. The results show that, while familiar area is largely influenced by one’s previous knowledge of the area, it is also continuously corrected by events in between. Different land use characteristics have different impacts on different social groups’ travel patterns, thus contributing to the variability in the size of one’s familiar areas.

Many studies have demonstrated that the effect of urban street spatial shape on sound propagation cannot be ignored. Most previous studies are based on idealised spatial models and but not systematically and comprehensively examine the real and complex street space. This paper takes the actual streets of a high-density city as research objects, select reliable spatial parameters, obtain the acoustic propagation data using computer simulation, identify the sound propagation characteristics and establish sound propagation models of urban streets. In total, 144 samples have been tested, 13 spatial parameters, including the width information, height information, section information and plan information of streets, have been selected, and three acoustic indices, which include the sound attenuation, reverberation time and early decay time, have been analysed in this paper. The sound propagation in the urban street is consistent with the propagation characteristics of the semi-free sound field, i.e. the sound attenuation is linearly correlated with the logarithm of the sound propagation distance. This linear correlation becomes more pronounced for the greater Plan enclosure degree and more even distribution of façades. The trend of sound attenuations decreases with the increasing Cross-sectional enclosure degree, increasing Plan enclosure degree in the Near Zone or decreasing Vehicle lane width. Reverberation time is primarily distributed between 1.0 s and 3.0 s and tends to be stable when the propagation distance increases. The mean reverberation time increases with the increasing Mean façade height, Sidewalk width, Cross-sectional enclosure degree in the Near Zone or Standard deviation of Plan enclosure degree in the Near Zone. The typical early decay time distribution curve is clearly divided into two areas along the propagation direction. In the first area, the early decay time value is notably small and nearly equals zero. With a sudden increase, the early decay time maintains at a relatively stable value in the second area (stable area) of 0 to 3.0 s. The mean early decay time in the stable area increases with the increasing Vehicle lane width, increasing Cross-sectional enclosure degree or decreasing Standard deviation of Plan enclosure degree in the Near Zone.

Regional designing is employed to envision regional futures that aim to guide decisions on the environment in the region over a longer period of time. However, longitudinal studies on the long-term use and effect of regional designing are lacking. This paper investigates the impacts of regional designing in the complex and fragmented setting of a cross-border region. Since the late 1980s, the region was subject to four regional design episodes that each had different impacts: from a new perception of the region to initiating regional collaboration and effects on the Dutch professional debate. The study showed that regional designing is a powerful means to overcome difficulties that arise from the fragmented setting of a cross-border region. Moreover, it revealed that the context in which regional designing is embedded determines in what areas regional designing will have its impact. Both plans and people are important in the transference of regional design outcomes to other planning arenas and conditions, such as status and available funding, improve the chances of transference.

Global regression models, such as Ordinary Least Squares, are generally used to explore driving factors of surface urban heat island (SUHI) effects across large cities on a national level, but issues of spatial non-stationarity or local variations have rarely been taken into account. Our study quantifies SUHI effects for 274 cities in China with MODIS LST products and explores spatially varying relationships between SUHI intensity (SUHII) and their driving factors using geographically weighted regression (GWR). The results show that GWR models have stronger explanatory power and lower spatial autocorrelations of residuals compared with ordinary least square models; the application of GWR models finds that the relationships between SUHII and the driving factors vary across China. Spatially varying coefficients from GWR models could contribute to the development of local-specific urban planning or policies in different regions. The findings from our investigation suggest that GWR has the potential to serve as a useful tool for environmental investigations on a national scale.