Environment and Planning B: Urban Analytics and City Science

Building height is one of the most important determinants of streetscapes. According to zoning regulations in countries such as Japan, building heights are indirectly controlled by the floor area ratio (FAR). The maximum FAR and the building coverage ratio (BCR) represent the main tools of zoning regulations, which legally regulate building shapes and volumes based on plot sizes at the district scale. If plot sizes and shapes are uniform due to zoning regulations, uniform building shapes (both their plane shapes and heights) may emerge. However, in Japan, plot sizes and shapes are not only non-uniform but irregular. Furthermore, the plot is a conceptually and analytically ambiguous concept and data regarding plot shapes and building heights are unavailable. Therefore, it is difficult to understand the relationship between variations in building heights and zoning regulations. These issues prompt the following research question: How can we estimate building height distribution under zoning regulations at the district scale? To answer this question, plot shapes are objectively defined as area Voronoi cells whose generators are building polygons and road networks. Then, the following two analyses are carried out in downtown districts of the Tokyo metropolitan region. First, the relationship between plot sizes, BCR and building heights is analysed. It is found that building heights scale sub-linearly to plot sizes. Second, following this relationship, the probability density function of building heights under zoning regulations is theoretically derived as a log-normal distribution, primarily estimated from building density, road network density, average road width, BCR and FAR. This is compared with the empirical distribution of discretised building heights and the difference is investigated. Furthermore, how to harmonise variations in building heights is discussed by considering their opportunities and external costs. These findings are expected to provide urban planners with a theoretical basis for creating harmonious streetscapes.

The distance between home and school considerably influences the probability of children’s walking or biking to school (termed Active School Travel) which is a significant opportunity to promote their daily physical activity. This study investigated the shortest routes from home to school of primary school students and how the route distance can be shortened at the household level in Nanjing, China. We found that gated urban form results in significantly roundabout routes to school. In 2016, China issued the Opening and Prohibiting Gated Communities policy, subsequently the Healthy Cities Initiative, etc. which may leverage cities towards more healthy and sustainable transformations. In the light of these policies, we hypothesised that providing through access as management option, and opening new entries as reengineering option, would shorten school travel distance with minor costs. The scenario analysis shows that such management and reengineering adaptions would provide shorter and potentially less exposed routes for students. This study identifies how the existent urban form works against active school travel, and proposes how salutogenic pathways may be created in the gated urban form. The study, with transferability to other cities, can assist urban designers and policy makers in piloting urban (re)form incrementally and pragmatically to prompt active travel to schools.

The topology characteristic and effectiveness of city network play critical roles in guiding transportation infrastructure planning and construction. From empirical evidence of three types of transportation infrastructure in China’s urbanization process—railway, civil aviation, and highway—we propose a new city network construction method based on the transportation infrastructure links between cities. Degree centrality, closeness centrality, and betweenness centrality are selected as measuring indicators for analyzing the topology characteristic of the China city network, and the shortest path length is used to measure the effectiveness of the China city network from the node level and the overall level. Based on public and open data and combining analysis methodologies, we explore the topology characteristic and effectiveness of the China city network. The analysis results show that the topology characteristic of the China city network presents disequilibrium on geographical distribution. Network node effectiveness is positively correlated to the economic development level of cities in the China city network, and different sub-networks present different overall network effectiveness. The analysis results of the Dalian–Yantai subsea tunnel show that although the effectiveness of the China city network can be greatly improved through increasing links between cities with no direct link, transportation infrastructure planning and construction has different impacts on the topology characteristic of the China city network. The topology characteristic and effectiveness of each city in the China city network should be considered comprehensively in the process of transportation planning and construction.

Obtaining the time and space features of the travel of urban residents can facilitate urban traffic optimization and urban planning. As traditional methods often have limited sample coverage and lack timeliness, the application of big data such as mobile phone data in urban studies makes it possible to rapidly acquire the features of residents’ travel. However, few studies have attempted to use them to recognize the travel modes of residents. Based on mobile phone call detail records and the Web MapAPI, the present study proposes a method to recognize the travel mode of urban residents. The main processes include: (a) using DBSCAN clustering to analyze each user’s important location points and identify their main travel trajectories; (b) using an online map API to analyze user’s means of travel; (c) comparing the two to recognize the travel mode of residents. Applying this method in a GIS platform can further help obtain the traffic flow of various means, such as walking, driving, and public transit, on different roads during peak hours on weekdays. Results are cross-checked with other data sources and are proven effective. Besides recognizing travel modes of residents, the proposed method can also be applied for studies such as travel costs, housing–job balance, and road traffic pressure. The study acquires about 6 million residents’ travel modes, working place and residence information, and analyzes the means of travel and traffic flow in the commuting of 3 million residents using the proposed method. The findings not only provide new ideas for the collection and application of urban traffic information, but also provide data support for urban planning and traffic management.

Empirical study of road traffic collision (RTCs) rates is challenging at small geographies due to the relative rarity of collisions and the need to account for secular and seasonal trends. In this paper, we demonstrate the successful application of Hidden Markov Models (HMMs) and Generalised Additive Models (GAMs) to describe RTCs time series using monthly data from the city of Edinburgh (STATS19) as a case study. While both models have comparable level of complexity, they bring different advantages. HMMs provide a better interpretation of the data-generating process, whereas GAMs can be superior in terms of forecasting. In our study, both models successfully capture the declining trend and the seasonal pattern with a peak in the autumn and a dip in the spring months. Our best fitting HMM indicates a change in a fast-declining-trend state after the introduction of the 20 mph speed limit in July 2016. Our preferred GAM explicitly models this intervention and provides evidence for a significant further decline in the RTCs. In a comparison between the two modelling approaches, the GAM outperforms the HMM in out-of-sample forecasting of the RTCs for 2018. The application of HMMs and GAMs to routinely collected data such as the road traffic data may be beneficial to evaluations of interventions and policies, especially natural experiments, that seek to impact traffic collision rates.

This study applies a new methodology using the location of tweets from creatives to study where economic creativity takes place in a city. Based on a Twitter network in Brighton and Hove (United Kingdom), a creative hub, we identify freelancers and entrepreneurs in the creative industries that form the ‘core’ of the ‘creative class’ but have rarely been captured in existing spatial research. We use a comprehensive geodatabase of ‘Points-of-Interest’ and Census of Population residence and workplace locations to match tweets with types of places. Findings show that practices of economic creativity are less spatially clustered in central parts of the city and more spatially distributed across the city than studies that used business register data or cluster approaches suggested. Residential areas, which proxy for home locations, have a high incident of creative activities besides urban amenities and coworking spaces. It is concluded that local economic development should support the creation and maintenance of attractive places of social interactions across the city to foster creativity and innovation which has become even more important with the surge in homeworking due to Covid-19.

Urban hotspots can be used to model the structure of urban environments and to study or predict various aspects of urban life. An increasing interest in the analysis of urban hotspots has been triggered by the emergence of pervasive technologies that produce massive amounts of spatio-temporal data including cell phone traces (or Call Detail Records). Although hotspot analyses using cell phone traces are extensive, there is no consensus among researchers about the process followed to compute them in terms of four important methodological choices: city boundaries, spatial units, interpolation methods, and hotspot variables. Using a large-scale CDR dataset from Mexico, we provide an interpretable systematic spatial sensitivity analysis of the impact that these methodological choices might have on the stability of the hotspot variables in both static and dynamic settings.

Urban cartography enables us to trace the historical and spatial evolution of human settlements, but it also furnishes us with the opportunity to obtain and analyse urban data from the perspective of the present day. Urban plans drafted for the reform and expansion of a city can provide us with valuable urban information about the planned use of new public space. In Western Europe, the historical cartography of Barcelona (Spain) maps the city’s mid-nineteenth century urban expansion project designed to fulfil egalitarian, social and hygienist goals. Here, using geographic information system tools, we digitize Barcelona’s cartography so as to create an urban dataset based on the city’s urban plans – the Cerdà Plans (1859 and 1863) – and to estimate its public space typology. Social centres, hospitals, green spaces, residential areas and communication infrastructures are identified and metrised, and urban public open spaces are analysed using various urban indicators. The urban data thus obtained represent a notable advance on attempts to quantify Cerdà’s original project. The importance attached to public space (>75%) and to both communication infrastructure and urban public open spaces is indicative of the desire to create a new city and to break with the values of old Barcelona. In short, the data obtained serve to undertake a detailed comparison with the present-day reality of Barcelona.

Despite growing studies on the distinction between morphological and functional polycentricity, the present methods for identifying polycentricity often focus on the morphological dimension due to a lack of information about intra-urban functional flows, and are limited by the multifarious nature of people’s spatiotemporal interactions. This study proposes a new approach, examining the degree of polycentricity in Shanghai at the intra-urban level using passive mobile phone data. A series of polycentricity indicators are used and are benchmarked against previous studies. Notably, we found that people’s daily movements within a subcenter indicate that morphological polycentricity is also at play in Shanghai. We conclude that morphological and functional polycentricity may coexist at the intra-urban level, and that a mobile phone data approach can offer an alternative method to elucidate both the morphological and functional features of subcenters.

Switzerland’s widely adopted spatial policy rejects the use of new land in favour of promoting the densification of existing buildings or brownfield developments. However, to date there has not been an assessment of the volumetric building reserves that are still available within the current building regulatory framework. This paper addresses this lacuna using a case study of the agglomeration of Lausanne. An automated spatial policy model with particular focus on building density and its volume in residential and mixed-use areas allows for building policy to be quantified, assessed and evaluated on a countrywide scale since it takes the location of the building lot into consideration and cross-references it with the correct building regulation. Three-dimensional comparison allows us to identify whether the maximum volume permitted under the building regulation is greater than the current existing building volume. For the test case, spatial policy model identified 38 hectares of available square metres for densification (‘building surplus’ in the context of existing buildings, either in the form of extending existing buildings or infill development) and 93 hectares of square metres available for new developments (brownfield development of vacant or derelict open land) of residential and mixed-use buildings. At the same time, almost all areas are allocated beyond Lausanne’s inner-city boundaries.

One of the key concepts underlying the science of spatial planning refers to the role of development corridors as a planning instrument to potentially restructure economic space. Although strong evidence exists that corridors are regarded as important spatial development instruments that channel economic development, counter-arguments indicate the need for more diversified strategies at regional and national levels, as well as a greater awareness of agglomeration economies to allow for the integration of corridors as strategic and supporting networks. Drawing on fundamental literature, a regional corridor model was developed with the aim to establish a spatial framework through which corridor development can be integrated as strategic and supporting networks to support the notion of ‘sustainable spatial- and settlement planning’, i.e. the appropriate compilation and administration of policies affecting spatial organisation at local, regional and national levels. Based on the empirical research, regional and national governments could, through the RCM, develop a realistic spatial perspective on long-term settlement patterns and investment opportunities which could transform economic space development and seek to connect the potential of urban systems in economic development.

Environmental noise affects life and health within urban environments through interfering with sleep, rest, study and personal communication. Noise mapping is an important issue of local authorities but due to its requirements (staff, costs and frequency), the available data are limited or outdated. Our aim was to involve people with smartphones in the mapping process and to determine the accuracy of the measurements performed with these devices in a natural environment. The main questions were whether the measured data were dependent on the type of applied software and smartphones. We tested three software (Noise Watch, Noise Meter and Sound Level Meter) and 12 different smartphones. We evaluated the measurements with hypothesis testing and correlation analysis. Although the accuracy of smartphones was below the professional equipment, measurements can be conducted easily due to their availability; thus, a reliability analysis is important. We found that comparison between professional devices and smartphones in a laboratory was misleading as it lacks the environmental factors biasing the measurements. The best method to compare the measurements carried out with smartphones and professional Noise Meters was to use large number of measuring points in a heterogenic outdoor environment where the noise ranged from the low to large values. We revealed that both the applied software and smartphones have relevant effect on the measurements, and, although it is possible to use these devices for noise mapping, one should consider not to apply different software and smartphones. Accordingly, crowdsourcing is not a reliable data collection method because: (1) measurements should be supervised, (2) smartphones’ accuracy should be tested and (3) measurement circumstances should be the same. If any of these requirements are violated, the quality of the resulting maps can be questioned.

New mobility services that facilitate multimodal options are important for strategic urban transport systems planning. Part of this strategy is municipal investment in urban mobility hubs to increase access to mobility services. We present a new evaluation framework and algorthim to locate and assess the sustainability and equity impacts of hubs in cities. Scenarios are used to evaluate hub investment strategies in different cities that prioritize (1) current mode split, (2) high transit capacity, and (3) multimodal services. From an equity perspective, high transit capacity and multimodal hub strategies include more low-income areas than current mode split, which covers middle-income areas most. Travel times to access the nearest hub in Portland by low-income households is ∼20–40 min compared to high-income households requiring ∼25–30 min. Seattle and Vancouver perform better requiring ∼15–20 min for low-income compared to ∼25–35 min for high-income households. Multimodal hubs are the most efficient requiring ∼15–20 minutes to reach compared to ∼15–30 minutes for high capacity and current mode split scenarios. From a sustainability perspective, ∼10%–50% of the population cannot reach a hub within 30 minutes by public transit compared to <10% by car, and travel time to reach the nearest hub in all three cities by car is <20 min compared to ∼20–40 min by public transit. Between all cities, low-income households representing ∼2%–15% of the total population have no access to a hub by public transit within 30 min compared to high-income households representing ∼1%–3% of the total population. Only in Portland are there low-income households not able to reach a hub by car, and in each city, all high-income households can reach at least one hub by car within 30 min. Our results show how municipalities can strategically invest in public transit and multimodal options to increase the frequency, quality, and overall mobility for low- and medium-income households and improve access to essential amenities for more vulnerable citizens. Municipalities can use our hub evaluation framework to explore alternative transport investment scenarios and spatially locate urban hubs to meet future travel demand, increase adoption of multimodal services, and improve equitable access for all citizens.

The study of street network patterns is beneficial in understanding the layout or physical form of a city. Many studies have analyzed street network patterns, but the similarity and/or difference of street network patterns across a country or region are rarely quantitatively understood. To fill this gap, this research proposes a quantitative analysis of street network patterns nationwide. Specifically, the street network patterns across a country or region were first mapped, and then the relationship between such patterns and various landscape factors (calculated based on global open data) was quantitatively investigated by employing three regression models (ordinary least squares, spatial lag model, and spatial error model). Not only the whole region of China but also its subregions were used as study areas, which involved a total of 362 prefecture-level cities and 2081 built-up areas for analysis. Results showed that (1) similar street network patterns are spatially aggregated; (2) a number of factors, including both land-cover and terrain factors, are found to be significantly correlated with street network patterns; and (3) the spatial lag model is preferred in most of the application scenarios. Not only the analytical method and data can be applied to other countries and regions but also these findings are useful for understanding street network patterns and their associated urban forms in a country or region.

In recent decades, research has paid attention to the atmospheric ways computer-generated imagery (CGI) marks the experience of future urban design. What has been addressed in the generic abbreviation CGI has, however, exclusively concerned visualisations that communicate with stakeholders beyond designers and architects. Based on fieldwork within an urban design lab, the paper differentiates among the range of CGI used by urban designers. Focusing on collage, which forms one kind of CGI that has received scant attention in scholarly literature, I demonstrate its key function as an epistemological in-house work-in-progress tool that helps designers to refine their vision and to identify the atmosphere of future urban spaces. Based on New Aesthetics, collaging atmosphere is characterised by a physiognomic approach to urban space that selectively addresses aesthetic characteristics. Hence, the paper tackles a discussion that points towards cautious handling of the communicative scope of collages that can be well complemented by other types of CGI before entering a constructive dialogue with clients.

The general transit feed specification is becoming a popular data format for the publication of public transport schedules, making possible the collection of a nation-wide public transport schedule dataset, which enables monitoring of transit supply at an up-to-date and more precise level across a country than previously possible. In this paper, we use general transit feed specification data to measure local-scale public transport availability across England based on service frequency and spatial proximity to public transport stops/stations. Moreover, to demonstrate the usefulness of public transport availability measures, we examine inequalities of public transport provision and identify areas at risk of transport poverty across England. Furthermore, we estimate population (number of households) who are likely to suffer from transport poverty, accounting for public transport availability, time-based job accessibility by public transport or walking, household income and car ownership levels. Based on the criteria, we have used to identify public transport risk, we find that investment in the development of public transport services should prioritise West Midlands, East of England, South East and South West as those regions have more households who are likely to suffer from transport poverty. This paper contributes by (1) defining more comprehensive transit availability measures than existing measures at a variety of geography levels and (2) integrating fours aspects (i.e. public transport availability, job accessibility by public transport or walking, household income and car availability) to analyse transport poverty comprehensively.

Fair spatial distribution of services has always been a challenge for urban planners to supply sufficient accessibility for individuals and to consider the needs of vulnerable social groups. Nevertheless, equity assessment literature has mostly focused on measuring the accessibility through distance-based variables, and social stratification based on just income, as well. Accordingly, this study intends to employ an accessibility measure that considers non-distance-based variables along with distance-based ones. It uses multi-criteria decision-making to propose an accessibility index to assess vertical and horizontal equity of residents’ accessibility to a range of public facilities, in the district 6 of Tehran, Iran. Therefore, using the integration of geographical information system-based spatial analysis, wider people specification, and the Gini coefficient, this measure proposes a novel framework to examine the equity level of individuals belonging to the lower, middle, and upper social classes. Results imply a 0.228 Gini index for horizontal equity, which indicates a low level of inequity among residents. Besides, for vertical equity evaluation, Gini index of 0.097, 0.249, and 0.167, respectively, for lower, middle, and upper groups show people in the lower class experience very low levels of inequity, therefore higher accessibility is well distributed among groups with higher social needs. This approach can help planners to choose the right analysis method and prioritize urban decisions toward the equitable distribution of facilities.

Although various hierarchical structures have been investigated with respect to the different elements of urban form, the hierarchical spatial order of access from streets to plots and buildings has not been adequately explicated and objectively assessed. In this article, a new method, access structure, is presented to bridge this knowledge gap. Based on Krop’s generic multilevel diagram of urban form, different types of access structure are developed and symbolically represented. They are then quantitatively measured and compared using three metrics and an associated ternary diagram. Subsequently, the new method is tested first in analysing the internal structure of an individual urban block and then in distinguishing urban blocks with different structural characteristics. Eight urban blocks across the city of Nanjing, China, are selected as case examples. The results show that access structure is capable of accurately describing and evaluating complex spatial relationships between streets, plots and buildings. Access structure is potentially a useful method for studying the complex emerging built form of rapidly changing cities, especially in developing countries such as China.

Industry cluster development is important to stimulate regional economy. Conventional spatial methods for detecting industry clusters use a pairwise manner to infer the co-location relationships of multiple industrial types or instances, which increases the difficulty of interpreting the results. This study proposes to use co-location patterns (CPs) mining method to directly capture the co-location of multiple industrial types from the bottom up without any conditions of data relations defined a priori. The method is applied in Dongguan, China, to investigate the industry cluster patterns at an intra-urban scale. At the city level, the results show prevalent CPs of information communication and technology industry and other associated sectors. At the sub-regional level, however, approximately 41% of the industrial CPs are different from those obtained at the city level. The local features of sub-regional industry clusters are associated with productions of, for instance, sporting goods and toys, digital instrument and office equipment, machine parts and woodware, and textile-related products.

In this article, a new method called spatial amplifier filtering is proposed. The presented method is related to Moran eigenvector filtering and allows the accentuation of spatial structures in heterogeneous data sets. The spatial amplifier filtering technique is based on the inclusion of certain eigenvectors of a spatial weights matrix into a regression model. The application of this method can be seen as a pre-processing step prior to subsequent analyses, and to separate different types of spatially correlated components in a data set. For this purpose, three different types of the so-called spatial amplifiers are proposed, each consisting of different subsets of eigenvectors of the weights matrix. These amplifiers can either emphasise the positive or negative spatial autocorrelation, or spatial structuring in general. In this way, it is possible to make desired spatial structures more visible, especially in spatially highly mixed data sets, whereby the focus here is on geosocial media data. In the empirical part of the article, it is first shown why georeferenced social media data are difficult to handle from a spatial analysis perspective, motivating the need for the method proposed. Subsequently, the technique of amplifier filtering is applied to two data sets: a census data set from Brazil and Twitter data from London. The results obtained show that the method is capable of strengthening existing spatial structures and mitigating potentially disturbing spatial randomness patterns and other nuisances. This facilitates the interpretation especially of the Twitter data used. While the analysis of the unfiltered Twitter data with established methods reveals little information about possible spatial structures in the tweets, the filtered data offer a much clearer picture with distinguishable clusters. In addition, the method also provides insights into the internal irregularity of spatial clusters and thus complements the toolbox for investigating spatial heterogeneity.

A large proportion of European inhabitants live in dispersed urban settlements, much of which is labelled as sprawl, defined by monofunctional, low-density areas. However, there is increasing evidence that this may be an overly simplistic way of describing territories-in-between (TiB). This paper defines and maps functional mix in six dispersed urban areas across Europe, applying a method that goes beyond existing land-use-based mixed-use indicators but considers functional mixing on the parcel level. The paper uses data on the location of economic activities and the residential population. It concludes that, in eight cases from four European countries, mixed-use is widespread and that more than 65% of inhabited areas are mixed. Moreover, the paper relates functional mixing to specific settlement characteristics: permeability, grain size, centrality and accessibility, and connectivity. This demonstrates that functional mixing is not the result of local urban morphology or planning instruments, but of the multi-scalar qualities of a location. Therefore, there is a requirement to coordinate planning and design through different scales if mixed-use areas are to be seen as one strategy for achieving greater sustainability in the spatial development of dispersed areas.

Relative accessibility is a widely studied approach that recognizes access to major locations as subjective and shaped by individual circumstances (e.g., individual preferences, habits, and cultural norms). One missing element in the knowledge base is how relative accessibility can be effectively mapped for decision-making. To fill the research gap, this paper evaluates whether cartograms are an appropriate tool for mapping relative accessibility, taking the city of Zaragoza, Spain as a case study. The research design included three phases: (i) elaboration of grid-based maps on relative non-motorized accessibility; (ii) elaboration of cartograms on relative non-motorized accessibility; (iii) an end-user evaluation with 30 local practitioners to analyze the effectiveness of cartograms to map relative accessibility compared to grid-based maps. Participants signaled that diffusion-based cartograms could be complementary to grid-based maps, providing better visualization of spatial dissimilarity patterns of accessibility between population groups. However, participants noted greater difficulty in identifying Dorling cartograms as an effective technique for mapping relative accessibility. The paper closes with a review of the strengths and weaknesses of the potential application of these visualization techniques in the field of accessibility planning.