Against the paucity of information on urban parcels in China, we propose a method to automatically identify and characterize parcels using OpenStreetMap (OSM) and points of interest (POI) data. Parcels are the basic spatial units for fine-scale urban modeling, urban studies, and spatial planning. Conventional methods for identification and characterization of parcels rely on remote sensing and field surveys, which are labor intensive and resource consuming. Poorly developed digital infrastructure, limited resources, and institutional barriers have all hampered the gathering and application of parcel data in China. Against this backdrop, we employ OSM road networks to identify parcel geometries and POI data to infer parcel characteristics. A vector-based cellular automata model is adopted to select urban parcels. The method is applied to the entire state of China and identifies 82 645 urban parcels in 297 cities. Notwithstanding all the caveats of open and/or crowd-sourced data, our approach can produce a reasonably good approximation of parcels identified using conventional methods, thus it has the potential to become a useful tool.
There is a long-running debate in the planning literature about the effects of the built environment on travel behavior and the degree to which apparent effects are due to the tendency of households to self-select into neighborhoods that reinforce their travel preferences. Those who want to walk will choose walkable neighborhoods, and those who want to use transit will choose transit-served neighborhoods. These households might have walked or used transit more than their neighbors wherever they lived. Most previous studies have shown that individual attitudes attenuate the relationship between the residential environment and travel choices, and so the effect of the built environment on travel may be overestimated. But there are other researchers who argue the reverse, claiming that residential preferences reinforce built environmental influences. This study assesses the relative importance of the built environment and residential preferences/travel attitudes for a sample of 962 households in the Greater Salt Lake region using structural equation modeling. For the sake of simplicity, we extracted two factors using principal component analysis, one representing the built environment and the other representing residential preferences/attitudes. Our findings are consistent with the view that the neighborhood built environment and residential preferences both influence household's travel, that the built environment is the stronger influence, and that the built environment affects travel through two causal pathways, one direct and the other indirect, through attitudes.
Understanding individual daily activity patterns is essential for travel demand management and urban planning. This research introduces a new method to infer individuals' activities from their mobile phone traces. Using Metro Boston as an example, we develop an activity detection model with travel diary surveys to reveal the common laws governing individuals' activity participation, and apply the modeling results to mobile phone traces to extract the embedded activity information. The proposed approach enables us to spatially and temporally quantify, visualize, and examine urban activity landscapes in a metropolitan area and provides real-time decision support for the city. This study also demonstrates the potential value of combining new big data such as mobile phone traces and traditional travel surveys to improve transportation planning and urban planning and management.
One of the important bottlenecks to the wider adoption of planning support systems is a lack of evidence about whether they improve planning processes. In addition, existing research does not include field studies with high context validity. This paper fills this gap in the literature by reporting the results from a field study evaluating the performance of a planning support systems used for sketch planning as part of a land use planning project in metropolitan Austin, Texas, USA. Participants reported high levels of learning and dialog quality, the two chosen planning support systems performance measures. A regression analysis finds both are related to the ability of planning support systems to change participants’ perceptions. In addition, as suggested by learning theory, the planning support systems performance outcomes are significantly related to participants’ identity as a planner and meeting attendance, but are not related to gender or educational attainment. Finally, for the planning support systems studied here, participation in the planning support systems creation is less important than other factors in explaining planning support systems performance. The paper contributes to efforts to develop and implement robust measures of planning support systems performance and links concept of planning support systems performance to broader theories of learning.
Do policies to encourage compact, mixed use, pedestrian-friendly land-use patterns reduce driving? Not necessarily. Understanding how the built environment affects travel patterns is complex, not least because households may choose their neighborhoods on the basis of how they expect to get around. Some scholars have argued that ignoring this process of residential sorting, or ‘self-selection’, causes overestimates of built-environment influences and leads to false optimism about the efficacy of land-use policies in influencing travel. But others have suggested that residential self-selection provides a strong argument for using land-use policies to expand the supply of development that may facilitate lower automobile use. We argue that previous work on both sides of the argument has neglected to think through the myriad ways that residential choice could affect estimates of built-environment effects. In this paper we provide a more rigorous theory of residential self-selection, identifying a set of five household, market, and policy factors that are critical to understanding the residential self-selection problem, along with research questions that correspond to these factors. We explain why observed relationships between travel and the built environment could be misleading, causing either overestimates or underestimates, depending on the nature and context of residential choice. We illustrate with scenarios that show how different plausible assumptions about residential choice will bias, in different directions, estimates of the built environment's effects on travel; and we argue the need for research to focus not just on those independent estimates but, critically, upon the market and policy context that influences residential sorting.
Urban open spaces are considered as spatial residuals of the expansion of built areas. The environmental impact of the resulting land-cover pattern and associated ecosystem services are frequently evaluated at a crude spatial resolution only. However, wild animals use remaining interconnected fine-grain open spaces as an infrastructure for movement. In this paper, we traced the evolution of an open-space system in Haifa, Israel, and examined the impact of urban morphology on size and distribution of open spaces at different spatial resolutions. At a 30 m resolution, our analysis indicated fragmentation and increasing partial elimination of open spaces. Over time the connectivity declined at a diminishing rate, yet the network did not disintegrate into separate components. The evolution analysis implied that in crude resolution, the open space network is threatened. At a 5 m resolution, our analysis showed that Haifa remains porous to animal movement. Using combined multiple least-cost paths through the urban landscape of heterogeneous permeability, we illustrated extensive connectivity among open spaces. Backyards and other urban in-between spaces complemented the seminatural open-space network connectivity, enabling wildlife movement between habitat patches and thus survival in an urbanized environment.
In the pursuit of the communicative, collaborative and participatory planning processes advocated by academic planning literature, a practice has evolved that translates abstract objectives into practical workforms. Planning literature proposes many objectives that can be met by less top-down methods of generating ideas and making decisions. Little is known about how such objectives are translated into practical methods applied. This paper presents an inventory of practices that is meant to validate and supplement available theories on communicative planning. It concentrates on a specific part of the planning process: the moment where optional solutions to a problem are being generated, not by each stakeholder in isolation, but specifically by groups of stakeholders in constructive designerly interaction with each other. We interviewed 11 experienced professionals from the Netherlands who use interactive design sessions on a regular basis. This paper reports on their responses to questions about skills needed by session leaders, what types of venues are best to use, how to behave during sessions, requirements for participants to contribute, roles of governments and what explains the eventual effects of session outcomes. Although every session still needs to be tailor-made, based on practical wisdom and sensitivity to context, this study reveals recurring hands-on principles for organizing an effective dialogue for exploring solution space.
In this paper, we explore the route beyond the conventional, linear attitude within planning and its rationality debate. We combine our theoretical reasoning with a multiscale approach and with fractal-like argumentation which results in a frame of conditions which is supported by the outline of a theoretical conceptual simulation model which would also allow non-linear, iterative simulations of the urban space. The understanding of autonomous non-linear spatial development has a direct impact on planning. Addressing the underlying thinking behind Haken's synergetics we develop a framework within which the interdependencies between different levels of scale are key. We are aware that bottom-up and top-down processes often have a mutual influence on one another. We therefore propose a conceptual simulation model for planning where conditions have an impact at various levels of scale. In coherence with the idea of the dynamic behaviour of the system after a planning decision was made', this feedback gives us information on the surviving and non-surviving planning scenarios and decisions and is reminiscent of systems which are open to self-organizing pattern formation. Our reasoning with regard to planning and decision-making and their multilevel consequences is strongly influenced by the arguments presented in complexity studies.
Planning researchers and practitioners are adapting to new and evolving planning cultures that require new skills and techniques. This paper examines the introduction of qualitative research methods, traditionally developed as part of anthropology, sociology, and psychology disciplines, to planning students. We present an analysis of qualitative research methods' courses that were instructed to planning students. The paper portrays three principles of planning discipline that are in tension with a more constructive interpretation of the socio-spatial realities. We then offer several pedagogical inputs to qualitative methodology education for planners and how it could contribute to new and developing planning environments.
Assessing a territory's fire proneness is fundamental when planning and undertaking effective forest protection and land management. Accurate methods to estimate the risk of fire ignition in natural environments have been proposed over the last decades and digital mapping has been used to identify critical areas. The Canadian Forest Fire Weather Index is a well-known fire danger rating index created and improved during the last 45 years by the Canadian Forest Service. The goal of this paper is twofold. Firstly, we evaluated whether the Forest Fire Weather Index is an adequate instrument to predict fire ignition in Alpine and sub-Alpine areas using quite a large dataset of meteorological and forest fire data collected in the Lombardy region (Northern Italy) between 2003 and 2011. By means of a spatial binary regression model, we demonstrated that Forest Fire Weather Index has a significant impact on the probability of fire ignition. Since this approach allows us to account for other characteristics of the territory in order to provide a more accurate estimate of the spatial wildfire dynamics at a moderately large scale, the second goal of the paper aims at creating a model to assess fire risk occurrence using the Forest Fire Weather Index and land use information. It has been found that ignition can easily occur in large forested areas whereas denser urban areas are less exposed to fire since they usually have no fuels to ignite. Nevertheless, since human activity has a direct impact on fire ignition human presence, it fosters ignition in forested areas. Finally, the model, including these spatial dimensions, has been employed to derive a probability map of fire occurrences at 1.5 km resolution, which is a fundamental instrument to develop optimal prevention and risk management policy plans for the decision maker.
Cities appear to display similar features and mechanisms across different geographies. This phenomenon seems to hold despite planning intentionality. In questioning the nature of this behaviour, an attempt is made in this paper to examine how cities retrieve their relational dependencies between street structures and other form-function attributes after the imposition of large-scale planning interventions. For the purpose of this investigation, indices of accessibility and form-function data are binned in a grid layer to enable mapping dependencies between these variables in Manhattan and Barcelona. Ordinal Regression models are fitted to empirical data in order to identify the effect of planning on urban dependencies. To reveal how these dependencies build up in time, we model and visualise a dependency network that captures the spatiotemporal relationships between accessibility and form-function variables in Manhattan (1880–2010). The hypothesis is that where planning interventions are more dominant, the natural organisation that couples urban dependencies will be destabilized. The results confirm the hypothesis true for some form-function variables and within certain grid resolutions. The dependency network representing urban transformations in Manhattan explained some aspects of temporality in the relationships between the network structure of streets, street width, building height, land values and retail land uses. The models presented in this paper are thought to highlight regularities in the growth and change of Manhattan and Barcelona. An explanatory theory on how cities display this convergent behaviour is thought to be vital for urban design and planning policies.
This study explores the direct rebound effect, which indicates the degree of increase in travel demand caused by the increasing vehicle efficiency in the private passenger transport sector. Different from the usual effect, here the direct rebound effect is not assumed to be the same for the entire population. To determine when rebound occurs and who is suffering, two types of triggers, which may lead to different rebound effects among the population, are investigated: vehicle efficiency and travel demand. The quantile regression method is adopted to measure the rebound effect and differentiate it with respect to vehicle efficiency and travel demand. Considering that the rebound effect might have diverse performance in different cities, a comparative analysis between Beijing and Tokyo is conducted. Drawing on the data collected in a household energy consumption survey in Beijing and Tokyo in 2009, the models are estimated and the results reveal significant heterogeneity of the direct rebound effect both in Beijing and Tokyo, but with a much more complicated form in Beijing. For travelers in Beijing, rebound only occurs to those people whose cars are less efficient than 15–18 km/L, and the magnitude of the rebound effect is between 31.8% and 60.2%, varying across travelers with different travel demands. In comparison, in Tokyo, only travelers with low and medium kilometers traveled have the rebound effect, and the effect is inversely related to their travel demand, ranging between 17.1% and 92.3%. The above-identified inter-city and intra-city difference in the rebound effect could contribute to the population and a spatially specific policy scheme in practice.
Cost–benefit analysis is considered as an effective means for the government to avoid failures in public projects. However, once cost–benefit analysis becomes mandatory and residents expect a public project to be established based upon it, there is a potential for a dynamic inconsistency problem to arise, where dynamic inconsistency is defined as a difference in the optimal policy before and after a certain time. Taking as an example the coastal levee improvement policy in the city of Rikuzentakata in Japan, the present study clarifies the mechanism behind the dynamic inconsistency problem that is attributable to mandatory cost–benefit analysis and also discusses quantitatively the influence of the dynamic inconsistency problem on social welfare. In addition, through examining the quantitative result, we indicate that, in the projects where the improvement cost increases gradually with the scale, the inefficiency of the dynamic inconsistency problem is incurred on a larger scale.
In this paper we tackle a fundamental and long-time challenge in urban geography, to uncover a functionally differentiated global city network. To this day, the empirical investigation of a global multifunctional city network remains a challenge given the scarcity of appropriate relational and multifunctional data sources. To overcome this research gap, we present an interdisciplinary network modelling approach that integrates methods from geographic information science with social network analysis, including automated semantic analyses.We apply our modelling framework to a globally available, user-generated database (ie, Wikipedia), still underutilized in urban geography and planning research. The proposed visual analytical investigation of the multifunctional world city network also includes a systematic evaluation to assess the robustness of the proposed approach, and the adequacy of crowd-sourced databases for scientific uses. By example, we discuss economical and political relations of a latent multifunctional global city network which we uncovered with our data-driven approach. Our results not only empirically replicate previously well-established world city network theory, but also generate new research questions about multiple functions of cities, as hypothesized in world city network research. Furthermore, we showcase the potential of coupling text-based user-generated data analysis with geovisual analytics for scientific investigations in urban studies.
There is a growing interest in post-industrial landscape redevelopment and public participation in urban planning process. This study examined the public preference on post-industrial land transformation projects. A semi-qualitative methodology was used throughout the application of a questionnaire and interviews. Data on public perception of post-industrial landscape that incorporates significant environmental, cultural and historic assets were collected from 450 residents. Results illustrate that community attitudes to brownfield regeneration projects are positive. Urban growth should consider the redevelopment of derelict and/or abandoned areas instead of consuming new green areas. The results illustrated that, according to public perception, the most important aspect in the redevelopment of the study area is the creation of multifunctional areas, and that this aspect is statistically related with touristic activities, mobility and accessibility, use of renewable energies, environmental education, economic redevelopment, and safety/security. The researchers suggest that coupling the information gathered throughout the public preference process with the intrinsic characteristics of each landscape is helpful in understanding community expectations in order to inform urban regeneration projects that consider the economic, environmental and cultural functions of sites.
Home to over half the world's population, cities are the drivers of the global economy and the primary influencers of the Earth's sustainability. Thus, the burden of sustainable economic development falls ever more on cities, with many global organizations and governments calling for the promotion of green' economies. Yet how does a city move from its current economic structure to a green economy? Using detailed occupational data for US cities, we develop a green jobs index based on the network of interdependencies between occupational specializations. Using this index we quantify how close a city's current economy is to the green economy. We further show that movement or transition through this occupation space' toward a green economy is a slow and difficult process, with the average annual movement towards a green economy across all US cities being close to zero. Such difficulty is uncorrelated with a city's current population size, density, per capita GDP, per capita income, or even the city's current green jobs index. Furthermore, the structure of occupational interdependencies gives rise to suboptimal movements towards the green economy.
Dhaka, the capital of Bangladesh, is expected to be one of the five largest cities of the world by 2025 in terms of population. The rapid urban growth experienced by the city in the recent decades is one of the highest in the world. Urban expansion of Dhaka was slow in the 1950s, but strong growth followed the independence of Bangladesh in 1971. To understand Dhaka city growth dynamics and to forecast its future expansion by the year 2030, a self-modifying cellular automata Slope, Land use, Exclusion, Urban extension, Transportation and Hillshade model was used in this research using satellite images from 1989 to 2014. This model showed two interesting findings. First, approximately an additional 20% of the metropolitan area will be converted into built-up land by 2030 amounting to about 177 sq km. Second, the spatial trend of sprawl will be towards the north and north-west. The interpretation of depicting the future scenario as demonstrated in this research will be of great value to urban planners and decision makers, for the future planning of Dhaka.
Urban parks are community assets, providing people places to play and rest. Access to parks in urban environments promotes social equity and improves quality of life for surrounding neighborhoods. In this context, social equity is related to accessibility, i.e. the possibility of walking or biking from home to a public park, giving people who do not have access to a variety of entertainment an option that is a public good. This paper examines the spatial distribution of urban parks in the city of Curitiba, Brazil, and how it relates to the socio-economic conditions of surrounding neighborhoods. Curitiba is known for its urban parks; however, no systematic study has been conducted to verify which neighborhoods enjoy park access within walking distance and what the socio-economic differences are between the better and worse served neighborhoods. In addition, we investigate if access to green open space has improved between the last two decennial census, a period marked by unprecedented socio-economic affluence in Brazil. Research questions, to be addressed using spatial analysis, focus on equitable distribution, and spatial evolution of parks and social equity. Variables include measurable walking distances from census tracts to parks, income data from the 2000 and 2010 Brazilian decennial censuses, and qualitative data of urban parks in Curitiba. Findings offer recommendations for future implementation of additional parks in Curitiba so that all areas of the city have adequate green open space and all citizens have equal access to recreation and leisure opportunities.
The increased availability of transit schedules from web sites or travel planners as well as more disaggregate data has led to a growing interest in creating individual public transportation accessibility measures. However, used extensively, standard GIS software does not have direct capabilities to integrate transit schedules into multimodal networks and measure space–time-based accessibility. This has caused authors to either simplify travel time elements or develop tools to overcome these challenges. In this paper we aim to describe and implement a method that enables integrating time-table data from a travel planner into a multimodal network model using simple SQL (structured query language) programming and standard GIS. The method presented here integrates all parts of travelling by public transportation from individual home addresses to all reachable transit stops within different travel time thresholds. The method is used successfully to create a multimodal travel-time network model of the Capital Region of Denmark comprising bus, train, light rail, metro, and ferry as well as integrating walking or cycling to stops. Here, the individual accessibility is defined as accessibility areas. The accessibility areas are created at morning rush hour for a study population of 29 447 individuals and a few examples of accessibility areas are presented. The results show a big difference in individual public transportation accessibility in the region. In addition, how the transit network is accessed, whether it is at the nearest stop or at all stops within 1 km walking distance or 3 km cycling distance, leads to very different accessibility areas.
