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Understanding intra-urban human mobility patterns and their potential driving forces are vital to city planning and commercial site selection. In this paper, we first investigate the functions of urban regions and how different region types dynamically influence people's trip decisions. Furthermore, we characterize urban circadian rhythms by time-vary inter-regional transition probabilities between these regions with different functions, and integrate them into intervening opportunity model to predict human mobility. Public transportation card data in Shanghai are used to demonstrate the effectiveness of the model in terms of station passenger flows, travel time and trip flux. By taking regional function into consideration, the proposed model significantly improved the prediction accuracy. Quantitative analysis ulteriorly indicates that trip intentions and regional features are critical elements in trip flux prediction, especially in the afternoon and evening when people have an abundance of opportunities to travel by their own volition. When the function of a certain region changes, our model is able to make reasonable predictions accordingly. The results indicate the importance of considering individual travel motivation and regional function in modeling human mobility. The proposed model could serve as a guide for popularity and trip flux prediction in urban planning and reconstruction.

The rapid progress of urbanization has expedited the process of urban planning, e.g., new residential, commercial areas, which in turn boosts the local travel demand. We propose a novel "off-deployment traffic estimation problem", namely, to foresee the traffic condition changes of a region prior to the deployment of a construction plan. This problem is important to city planners to evaluate and develop urban deployment plans. However, this task is challenging. Traditional traffic estimation approaches lack the ability to solve this problem, since no data about the impact can be collected before the deployment and old data fails to capture the traffic pattern changes. In this paper, we define the off-deployment traffic estimation problem as a traffic generation problem, and develop a novel deep generative model TrafficGAN that captures the shared patterns across spatial regions of how traffic conditions evolve according to travel demand changes and underlying road network structures. In particular, TrafficGAN captures the road network structures through a dynamic filter in the dynamic convolutional layer. We evaluate our TrafficGAN using a large-scale traffic data collected from Shenzhen, China. Results show that TrafficGAN can more accurately estimate the traffic conditions compared with all baselines.

Green spaces are integral components of urban environments, as they provide numerous health benefits to people. However, urban green spaces are often inequitably distributed. Understanding the rela...

This thesis project defines the role of a ‘third place’ as an informal public space and an essential part of the urban landscape, as well as citizens’ daily lives. Such spaces help the urban growth to integrate with the lives of the people, allowing for our diverse community to come together and nourish new kinds of relationships that are rather hard to obtain in private or commercialized spaces. Our cities are increasingly deprived of such spaces due to changes in our urban planning structure. Culture of commerce has put a lot of pressure on urban areas replacing the program of present and potential public areas for private functions. With the introduction of online communication and creation of social networks most social encounters take place in cyberspace. These technologies allow for easy and constant virtual information exchanges eliminating the need for physical contact, therefore changing the patterns of social interaction. Aiming to bring us closer together, these technologies began to physically isolate our society even more. As members of our society enter into the virtual world of these technologies everywhere they go, they began to isolate themselves from others in the physical realm. This thesis project aims to redefine the physical role of a ‘third place’ in the context of a modern society that has been affected by virtual communication technologies and increasing privatization of urban public spaces. A new form of a ‘third place’ will be designed to create a sense of place within a community, enhance and bring back the presence of people in the city, engage diverse social groups in physical activities and improve their social interaction.

Collaboration and decision-making of humans usually entails logical reasoning that is expressed through discussions and individual arguments. Where collaborative work uses geo-spatial information and where decision-making has a spatial connotation, argumentation will include geographical references. Argumentation maps have been developed to support geographically referenced discussions and provide a visual access to debates in domains such as urban planning. The concept of argumentation maps provides for explicit links between arguments and the geographic objects they refer to. These geo-argumentative relations do not only allow for cartographic representation of arguments, but also support the querying of both, space and discussion. Combinations of spatial queries and retrieval of linked arguments provide a powerful way of analyzing and summarizing the current state of a debate. In this chapter, we provide an overview of the original argumentation model and we discuss related research and application development. We also link argumentation mapping to related concepts in geographic visualization, spatial decision support systems, and public participation GIS under the umbrella of collaborative GIS. Geographic Information Systems, Public Participation GIS, Collaborative GIS, Spatial Decision Support Systems, Argumentation Maps, Spatial Planning, User Interface.

Argumentation Maps support participants in geographically referenced debates as they occur, for example, as part of urban planning processes. In a quasi-naturalistic case study, 11 student participants discussed planning issues on the University of Toronto downtown campus. The analysis of this case study focuses on general usability aspects of an Argumentation Map prototype, such as cost of entry, efficiency, interactivity, and connectivity. By applying usability analysis methods from the field of human-computer interaction, we evaluate the learnability, memorability, and user satisfaction with this tool’s functionality. Our findings indicate that the participants were generally satisfied, but we include specific suggestions for improving the functionality of Argumentation Maps, e.g., with respect to map navigation, display of discussion contributions, and online status of participants. On a more general level, this case study contributes to the methods spectrum of research into participatory spatial decision support systems as an example of user testing in a realistic decision-making context.

Groundwater exists in underground aquifers and is largely hidden and intangible to water users. As such, groundwater models are one of the main vehicles through which groundwater is made legible. They are critical for water supply planning purposes. However, models are imperfect representations of limited data and contain much uncertainty, posing challenges for the water supply planning process. In this paper, we draw on a case from the Greater Chicago area to examine efforts by the authors and the Illinois State Water Survey to engage with local water managers to develop future water supply scenarios. Much of this area has been dependent upon the Cambrian-Ordovician Aquifer System for over 150 years. Over this period, water levels have declined by over 300 m and aquifers are expected to be unviable by 2030. Here we advance the growing field of participatory groundwater modelling (PGM) to identify forms of uncertainty and their influence on understandings of water supply and risk perceptions of depletion. Conceptually, we draw on the idea of models as world builders, where uncertainties are elucidated through knowledge production in the act of model building, while model development is simultaneously influenced by expectations, beliefs, and ambiguity surrounding those using the models. Through planning meetings and focus group discussions between groundwater modelers and water supply stakeholders, we identify four forms of interconnected uncertainty that hinder planning efforts: 1) hydrogeologic uncertainty, 2) modelling uncertainty; 3) water demand uncertainty; and 4) urban planning uncertainty. We describe our PGM efforts to reduce uncertainty and find stakeholder perceptions are as important as model uncertainties in water management decisions. Participatory modelling is effective in reducing and clarifying these four forms of uncertainty, particularly applied to short-term management decisions in a rapidly changing system. We conclude that future participatory modelling efforts need to focus on reducing communication barriers between scientists and local users.

In this paper we use an anti, intra and inter-categorical intersectional approach, and ethnographic enquiry in Dhaka, Bangladesh, to nuance debate over gender and participation in urban water, sanitation and hygiene (WASH) projects in low-income settlements. We make three claims. First, that a mismatch exists between how ‘women’ are framed and targeted in WASH projects and everyday experience characterised by the unequal distribution of benefits and burdens. Second, the likelihood of participation and leadership in WASH projects differs between women according, especially, to age, income, marital and occupancy status, social and political relationships. Third, the same interconnected leaders - including married ‘power couples’ - are involved in all development projects, with implications for the consolidation of power and authority. We call for urban development research, policy and practice to better engage with difference and the conflicting roles certain women and men play in NGO management, local politics and broader claim-making.

Sixty years before Brasília, Belo Horizonte was constructed as Brazil’s first modern planned city (1894-1897). This article focuses on the role of land development in shaping inequality in Belo Horizonte, the first of four major planned cities in Brazil. In Belo Horizonte, political backers and urban planners viewed controlled land development as providing a clean break with the past and creating an industrial, Eurocentric modern future in the wake of the abolition of slavery (1888) and the end of Brazil’s post-independence empire (1889). This article argues that more so than the architecture of its buildings or its urban plan, Belo Horizonte modeled an “architecture of capital” in which creating an urban property market both emerged from and was tasked with producing the city’s racialized narrative of modernity and progress. Belo Horizonte’s emphasis on land speculation gave rise to one of Brazil’s first favelas, comprised of the workers tasked with constructing the city.

Diverse physical features of urban areas alongside socio-demographic characteristics affect car ownership, and hence the daily mobility choices. As a case of sustainable mobility, we explore how various urban environments and socio-demographics associate with the spatial and social distribution of household car ownership and carlessness in the Helsinki Metropolitan Area, Finland. Three urban fabrics characterizing the study area are established based on the transportation mode (walking, public transportation, or automobile) the physical urban environment primarily supports. The national level Monitoring System of Spatial Structure and Urban Form database, and the National Travel Survey (2016) are utilized to further include spatial and socio-demographic variables into our analysis across these fabrics. Our results show that households with and without cars differ in terms of residential distance to the city center, neighborhood density, house type, and socio-demographic profiles. Single pensioners and students are most likely to be carless, whereas families represent the opposite. Within the carless households the differences are also evident between different groups. For the more affluent households residing in dense and well-connected areas, and mostly possessing driver’s licenses, carlessness is presumably a choice. Contrarily, many other carless households represent the less affluent often located in the more distant, low-density, and less accessible areas, while also possessing less driver’s licenses, making carlessness more of a constraint, as the local urban fabric does not support such lifestyle. Consequently, carless households should be increasingly recognized as a focus group in sustainable urban planning in terms of identifiable best practices and potential vulnerability.

The study of human mobility is crucial due to its impact on several aspects of our society, such as disease spreading, urban planning, well-being, pollution, and more. The proliferation of digital mobility data, such as phone records, GPS traces, and social media posts, combined with the predictive power of artificial intelligence, triggered the application of deep learning to human mobility. Existing surveys focus on single tasks, data sources, mechanistic or traditional machine learning approaches, while a comprehensive description of deep learning solutions is missing. This survey provides a taxonomy of mobility tasks, a discussion on the challenges related to each task and how deep learning may overcome the limitations of traditional models, a description of the most relevant solutions to the mobility tasks described above, and the relevant challenges for the future. Our survey is a guide to the leading deep learning solutions to next-location prediction, crowd flow prediction, trajectory generation, and flow generation. At the same time, it helps deep learning scientists and practitioners understand the fundamental concepts and the open challenges of the study of human mobility.

Urban development is often confronted with a lack of available space. Brownfield sites offer great potential for sustainable urban planning because of their often-central location and the benefits associated with their redevelopment. Although the interest in brownfield regeneration has led to a lot of research on this topic, there is not yet a comprehensive review of brownfield research. In this review, we analyze the research on brownfields and provide a picture of the published case studies. We focus primarily on brownfields research in the United States, Europe, and People’s Republic of China. This exploratory research is based on an analysis of the published scientific literature available in the Web of Science database. Initially used in North America, the term “brownfield” quickly became popular in the rest of the world, particularly in Europe. However, with the exception of the United States, there is no specific legislation for these sites; their protection is often based indirectly on directives or laws related to soil pollution, biodiversity, or the environment. The perception of the potential use of brownfield sites varies considerably from one part of the world to another, and international collaborations among researchers from different parts of the world remain limited. Most of the described reuses of brownfield sites are forms of soft reuse (53%), and the type of reuse of a site depends more on the surrounding urbanization levels and the specific region than on the past use of a brownfield site. Despite the continued interest in the rehabilitation of these sites, especially due to the increasing demand for nature in the city following the COVID-19 crisis, many questions regarding the future of brownfield sites remain unanswered. The factors influencing their successful redevelopment are unclear, and further research is urgently needed to ensure a truly sustainable re-use of these sites.

Given the cultural and environmental potential presented by historical water infrastructures in urban contexts, this article states the evidence of a not much documented urban phenomenon in Portugal, the refurbishment of water heritage protected areas motivated by European-based regeneration projects. By employing a case-study design, four good practices -placed in Evora, Lisbon, Braga and Guimaraes-are chosen to enlighten this growing and aware trend. The assets located there -the Agua de Prata Aqueduct, the Aguas Livres Aqueduct, the Sete Fontes water-supply system and the Zona de Couros industrial area, respectively-are geographical, historical and culturally characterised, while the projects that concern them are documented by visiting the areas and analysing the available sources. Then, open-data platforms and heritage protection decrees are processed to graphically code the topography, hydrology, urban land use, infrastructures, landmarks and protected areas, employing QGIS free software for Geographic Information Systems. As a result, the four practices are documented, discussed and compared. A table assesses and summarises their pre-existing and currently added values and a series of diagrams illustrates the landscape changes generated. These graphics validate the practices and update the status of the assets, enhancing the rediscovery of the existing landscapes and showing the main challenges and future opportunities faced by these areas.

Problem setting. Spatial development of Ukraine today is characterized by the presence of serious problems and negative trends, including inequalities of socio-economic development of some regions and settlements, inconsistency of social, economic, urban and environmental aspects of their development.State and local governments solve these problems by developing and implementing spatial development strategies. However, very few of such strategies met the real challenges and needs of local communities, were implemented or integrated.Recent research and publications analysis. Such Ukrainian scientists as O. Berdanova, B. Bezzubko, V. Vakulenko, G. Vasylchenko, Z. Gerasymchuk, O. Kary, V. Mamonova, O. Karlova, I. Parasyuk, A. Tkachuk and some others should be noted among the researchers of strategic planning and territorial development. Some national scientists devoted their research to relevant aspects of project management in territorial development, such as O. Amosha, V. Babayev, O. Bezugly, Z. Varnaliy, S. Vovkanych, S. Ghazaryan, A. Galchynsky, V. Geets, Z. Gerasymchuk, B. Danylyshyn, M. Dolishniy, T. Zayats, O. Kavtysh, I. Katsai, G. Litosh, O. Medvedeva, V. Molokanova, O. Novikova, O. Pidkuyko, S. Pisarenko, V. Rach, O. Rossoshanska, V. Seminozhenko, S. Chernov and some others.A number of methodological documents for spatial development planning have also been developed as part of EuropeAid technical assistance programs and projects.Highlighting previously unsettled parts of the general problem. Previous research has paid almost no attention to the identification of specific entities that are currently involved in the spatial development of Ukraine. The lack of clearly defined development “recipients” deprives the developed strategic documents of any specific vector of their implementation. This greatly complicates the functioning of the spatial development system in our country and reduces its efficiency. Therefore, the aim of the study is to propose a method of spatial development entities analysis in order to identify the actors who now provide implementation of measures in the field of spatial development in Ukraine.Paper main body. According to the proposed method, the first stage of the spatial development entities analysis is the establishment of landowners as potential assets users for the implementation of development measures. The next analyzed group of participants includes the subjects of urban planning, namely – customers of buildings construction and reconstruction, which are contained in the Unified Register of documents certifying the commissioning of completed facilities. The third group of spatial development entities studied includes investors who provide financing for spatial development activities. Statistical data on capital investments by sources of financing were obtained from the State Statistics Service of Ukraine.Certain spatial development entities are clearly divided into the public or private sphere, as project management approaches and methods in these areas have traditionally differed significantly. According to the developed method, the analysis of current entities in Ukrainian spatial development was carried out.Conclusions of the research and prospects for further studies. Obtained results of the analysis allow us to establish the representatives of the private sector as the main players in the spatial development in Ukraine. They own almost three quarters of Ukraine’s land. They are the most active participants in urban development, and they are the ones who provide more than 87% of capital investments with their own funds. That is, spatial development must be strategically attractive primarily for the private sector. Therefore, a topical area for further research may be the search of mechanisms for reconciling the strategic priorities established by the authorities in spatial development strategies with the strategic priorities of private structures as the main actors in spatial development.

Urban municipal infrastructures play an essential role in urban social and economic development. However, the imbalance between the supply and demand of urban municipal infrastructures appears a common problem in cities. This presents an urgent need for a proper method to investigate the carrying capacity of urban municipal infrastructures in the process of pursuing sustainable urban development. In line with this background, this paper defines the concept of urban municipal infrastructures carrying capacity (UMICC) and establishes an improved method for investigating this capacity. The performances of UMICC are designed to four levels, namely, Low-Utilization, Medium-Utilization, High-Utilization, and Over-Utilization. The effectiveness of this method is proven through an empirical analysis by using the data collected from 35 large cities in China. The empirical results reveal that the utilization intensity of UMICC has been decreasing in recent years in the large Chinese cities, in which UMICC carrier has been increasing at a higher speed than that of UMICC load. In particular, some better-developed cities present a “Low-Utilization” performance level, which is considered that urban policy-makers in some metropolises in China should pay more attention to the better utilization of existing municipal infrastructures. By applying the improved UMICC method introduced in this study, decision-makers can identify the specific areas that affecting the UMICC performance, thus tailor-made policy can be designed for improving UMICC performance by adjusting UMICC carrier and load.

Understanding relationships between urban structure patterns and air pollutants is key to sustainable urban planning. In this study, we employ a mobile monitoring method to collect PM2.5 and BC data in the city of Philadelphia, PA during the summer of 2019 and apply the Structure of Urban Landscapes (STURLA) methodology to examine relationships between urban structure and atmospheric pollution. We find that PM2.5 and BC vary by STURLA class, and some classes exhibit significant difference in pollution concentrations. We also find that the proportions in which STURLA components are present throughout the urban landscape can be used to predict the spatial distribution of urban air pollution. Among frequently sampled STURLA classes, gpl (grass, pavement, and low-rise buildings) hosted the highest PM2.5 concentrations on average (16.60 ± 4.29 µg/m3), while tgbwp (trees, grass, bare soil, water, pavement) hosted the highest BC concentrations (2.31 ± 1.94 µg/m3). Furthermore, STURLA combined with machine learning modeling was able to correlate PM2.5 (R2= 0.68, RMSE 2.82 µg/m3) and BC (R2 = 0.64, RMSE 0.75 µg/m3) concentrations with urban landscape composition and interpolate concentrations throughout the city. These results demonstrate the efficacy of the STURLA methodology in modeling relationships between air pollution and urban structure patterns.

The spatial time series generated by city sensors allow us to observe urban phenomena like environmental pollution and traffic congestion at an unprecedented scale. However, recovering causal relations from these observations to explain the sources of urban phenomena remains a challenging task because these causal relations tend to be time-varying and demand proper time series partitioning for effective analyses. The prior approaches extract one causal graph given long-time observations, which cannot be directly applied to capturing, interpreting, and validating dynamic urban causality. This paper presents Compass, a novel visual analytics approach for in-depth analyses of the dynamic causality in urban time series. To develop Compass, we identify and address three challenges: detecting urban causality, interpreting dynamic causal relations, and unveiling suspicious causal relations. First, multiple causal graphs over time among urban time series are obtained with a causal detection framework extended from the Granger causality test. Then, a dynamic causal graph visualization is designed to reveal the time-varying causal relations across these causal graphs and facilitate the exploration of the graphs along the time. Finally, a tailored multi-dimensional visualization is developed to support the identification of spurious causal relations, thereby improving the reliability of causal analyses. The effectiveness of Compass is evaluated with two case studies conducted on the real-world urban datasets, including the air pollution and traffic speed datasets, and positive feedback was received from domain experts.