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2023 | Buch

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Intelligence for Future Cities

Planning Through Big Data and Urban Analytics

herausgegeben von: Robert Goodspeed, Raja Sengupta, Marketta Kyttä, Christopher Pettit

Verlag: Springer Nature Switzerland

Buchreihe : The Urban Book Series

Enthalten in: Springer Professional "Wirtschaft+Technik" , Springer Professional "Technik" , Springer Professional "Wirtschaft"

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Über dieses Buch

This book contains a selection of the best papers presented at the Computational Urban Planning and Urban Management (CUPUM) conference, held in June 2023 at McGill University in Montreal, Quebec. Major themes of this book are smart cities, urban big data, and shared mobility. This book also contains chapters with cutting-edge research on urban modeling, walkability and bikeability analysis, and planning support systems (PSS).

Inhaltsverzeichnis

Frontmatter

Chapter 1. Introduction

Abstract

This introductory chapter provides a summary of the book’s contents. The book is organized into three parts: Digital Cities, Mobility Futures, and Fine-scale Urban Analysis. The chapters contain innovative research about smart cities, urban platforms, bikeability, ride-hailing, walkability, planning support systems, urban heat mitigation, and urban growth modeling. The 16 chapters are to be presented at the 2023 Computational Urban Planning and Urban Management conference at McGill University in June.

Robert Goodspeed, Raja Sengupta, Marketta Kyttä, Christopher Pettit

Digital Cities

Frontmatter

Chapter 2. Hybrid Smartness: Seeking a Balance Between Top-Down and Bottom-Up Smart City Approaches

Abstract

The idea of smart cities has been the subject of a range of views in recent years. A review of the terms and concepts around the “smart city” reveals three distinct ways of making urban development “smart”: a techno-centric approach (top-down), a social-centric approach (bottom-up), and a socio-technical approach (in-between). While each direction is significant in its own way, we argue that it is crucial to support an alternative, integrated idea of the smart city through “hybrid smartness.” In this new approach to smart cities, both top-down and bottom-up smart ideas are balanced, and recognized. It is the interweaving of both ideas that ensures an urban development model that promotes equity and sustainability. This hybrid thinking approach can thus inform the wider planning discourse that is usually trapped between top-down and bottom-up extremes.

Mennatullah Hendawy, Iasmin Fernanda Kormann da Silva

Chapter 3. Interpreting the Smart City Through Topic Modeling

Abstract

The Canadian Smart Cities Challenge grant program provided a unique opportunity to investigate what communities across Canada mean when they propose becoming a smart city. We investigated the utility of human-centered machine learning to analyze 137 grant proposals submitted to this program, containing approximately 1.5 million words. We explored whether results generated by topic modeling aligned with or differed from standard smart city definitions in the literature and current urban applications of topic modeling. The analysis resulted in three main findings. First, the prevalence of topics describing rural, regional and Indigenous communities challenged conventional definitions of “city” in the smart city. Second, context (e.g., local culture and language) inferred what constitutes smart, although smartness was not focused on technical innovations. Finally, our abductive approach generated new insights missing from conventional smart city research methods, including 40 percent of finalists and all four winning cities being identified as most representative users of topics.

Zhibin Zheng, Renée E. Sieber

Chapter 4. The Venue Code: Digital Surveillance, Spatial (Re)organization, and Infrastructural Power During the Covid Pandemic in China

Abstract

China has insisted on a zero-Covid policy for almost three years, deploying many disciplinary containment measures and surveillance tools. This chapter examines a surveillance tool called the “venue code” which is claimed to improve contact tracing of Covid outbreaks. My research is based on ethnography and discourse analysis of online textual and visual materials, capturing the integration of the venue code into China’s Covid containment regime. I analyze four aspects of the practice: bureaucratic structures, integration, spatial (re)organization, and technologies. I argue that the venue code mediates residents’ experience of cities and restricts urban mobility through the introduction of physical and digital infrastructure, while granting local actors more power. By doing so, this study draws attention to the ways in which the responsibility for achieving the zero Covid objective was shifted onto local actors and Chinese citizens, and state presence in communities and despotic power were strengthened.

Xiaoling Chen

Chapter 5. The Platformization of Public Participation: Considerations for Urban Planners Navigating New Engagement Tools

Abstract

Professional urban planners have an ethical obligation to work in the public interest. Public input and critique gathered at public meetings and other channels are used to inform planning recommendations to elected officials. Pre-pandemic, the planning profession worked with digital tools, but in-person meetings were the dominant form of public participation. The pandemic imposed a shift to digital channels and tools, with the result that planners’ use of technology risks unitizing public participation. As the use of new platforms for public participation expands, we argue it has the potential to fundamentally change participation, a process we call platformization. We frame this as a subset of the broader emergence of platform urbanism. This chapter evaluates six public participation platforms, identifying how the tools they provide map onto key participation frameworks from Arnstein (1969), Fung (2006), and IAP2 (2018). Through this analysis, we examine how the platformization of public participation poses ethical and scholarly challenges to the work of professional planners.

Pamela Robinson, Peter Johnson

Mobility Futures

Frontmatter

Chapter 6. Shared Micro-mobility: A Panacea or a Patch for Our Urban Transport Problems?

Abstract

Shared micro-mobility, including station-based bike-sharing and dock-less bike-/scooter-sharing, experienced phenomenal growth in the past decade in cities across the globe. It is low traffic impact, eco-friendly, and associated with a healthy lifestyle. Cities see it as a viable solution to solve issues related to congested, polluted, and auto-centric urban transport. In this chapter, I overview the history of shared micro-mobility. I then broadly summarize the existing research on shared micro-mobility systems around the world and explore how shared micro-mobility has transformed urban transport for its users. Using an empirical case from the city of Brisbane, Australia, I demonstrate the usage and limitations associated with shared micro-mobility trip big data. Lastly, I narrate two possible scenarios of the shared micro-mobility future. I conclude the chapter with a call for collaborations between cities, vendors, and researchers to make shared micro-mobility work for our future urban transport.

Zhenpeng Zou

Chapter 7. Understanding Bikeability: Insight into the Cycling-City Relationship Using Massive Dockless Bike-Sharing Records in Beijing

Abstract

Cycling records from emerging dockless bike-sharing services provide new opportunities to gain insight into the interactions between multiple fine-scale cycling characteristics and built environmental elements. Using Beijing as an example and the street as the analytic unit, this study examined the associations between three cycling characteristics and spatial visual elements while controlling for other built environmental features. The results showed that most visual elements were significantly associated with cycling characteristics, but their performance differs across models for trip distance, speed, and volume. The results also indicated that individuals riding long distances or at fast speeds preferred streets with more sky and greenery views. Likewise, wider streets with less spatial disorder, tended to have a higher riding volume. The findings can enhance the understanding of cycling behaviors and promote the implementation of urban design for more bikeable streets.

Enjia Zhang, Wanting Hsu, Ying Long, Scott Hawken

Chapter 8. Disclosing the Impact of Micro-level Environmental Characteristics on Dockless Bikeshare Trip Volume: A Case Study of Ithaca

Abstract

Although prior literature has examined the impact of the built environment on cycling behavior, the focus has been confined to macro-level environmental characteristics or limited objective features. The role of perceived qualities measured from visual surveys is largely unknown. Using a large amount of dockless bikeshare trajectories, this study maps the cycling trip volume at the street segment level. The research evaluates the micro-level objective features and perceived qualities along the cycling routes using street view imagery, computer vision, and machine learning. Through several regression models, the strengths of both micro-level environment characteristic groups are comprehensively analyzed to reveal their impacts on cycling volume at the street level. Overall, objective features exhibit higher predictive power than perceived qualities, while perceived qualities can complement objective features. The research justifies the significant impacts of micro-level environment characteristics on cycling route choices. It provides a valuable reference for urban planning toward a sustainable cycling-friendly city.

Qiwei Song, Wenjing Li, Jintai Li, Xinran Wei, Waishan Qiu

Chapter 9. A Planning Support System for Boosting Bikeability in Seoul

Abstract

The popularity of cycling has increased because it is conceived to be a much safer and environmentally friendly travel mode than automobiles and mass transit. As a result, shared-bike programs have gained attention among academics and policymakers. While inefficacies and other deficits in shared-bike programs have been described in the literature, so have these programs’ significant environmental, health, and economic benefits. The authors of this study developed a planning support system (PSS) to boost the efficacy and performance of the shared-cycling system in Seoul, Korea, using a developed bikeability index. First, they employed the Massachusetts Institute of Technology urban network analysis (UNA) and other spatial and statistical analyses to generate the model’s input dataset. Second, the authors built the bikeability index using geographically weighted regression (GWR) analysis. Using the index, the authors evaluated Seoul’s shared-bike system performance and identified important global and local variables affecting its efficacy. Based on these variables, the authors developed change scenarios. Finally, the authors used the planning support system to simulate these scenarios in multiple iterations until they reached a metric solution using the PSS feedback loop process.

Madiha Bencekri, Donggyun Ku, Doyun Lee, Seungjae Lee

Chapter 10. Integrating Big Data and a Travel Survey to Understand the Gender Gap in Ride-Hailing Usage: Evidence from Chengdu, China

Abstract

Improving transport systems to increase women's access to social opportunities and essential facilities has been key to reducing gender inequality. Studies have examined the gendered nature of travel from the perspective of a mismatch between women’s needs and availability of transport services, including fragmentized activity space, low affordability, and sensitization to safety. However, minimal attention has been given to the gender gap in the age of ride-hailing. Thus, this paper examines the nexus between gender and ride-hailing usage from the aspect of activity space and affordability. Two key questions are explored: (a) Are women dependent on ride-hailing? (b) If ride-hailing serves women differentially, how does this gender difference in the use of ride-hailing services occur? An innovative integration of big data and a travel survey is developed to examine such questions in Chengdu, China. Survey results and modelling analysis indicate that gender gaps in mobility is relatively mitigated by ride-hailing.

Si Qiao, Anthony Gar-On Yeh, Mengzhu Zhang

Chapter 11. Urban Airspace Route Planning for Advanced Air Mobility Operations

Abstract

This chapter aims to explore methods and procedures for route planning in urban air space for Advanced Air Mobility (AAM) operations using a 3D GIS environment. Route planning for urban air space through data analytics is produced to support planners in decision-making by visualizing the key influential factors in a 3D urban environment. Having defined two use cases for the City of Atlanta, different data types are needed to account for those factors and are introduced and tested. The use case for the Atlanta Aerotropolis has represented the need to plan a short-distance inner-city AAM network to serve as a public transportation network. In contrast, the other use case is a remote terminal shuttle service for the Atlanta airport. Recommendations on validating and optimizing the AAM networks are made at the end of this chapter.

Xi Wang, Perry Pei-Ju Yang, Michael Balchanos, Dimitri Mavris

Fine-Scale Urban Analysis

Frontmatter

Chapter 12. “Eyes on the Street”: Estimating Natural Surveillance Along Amsterdam’s City Streets Using Street-Level Imagery

Abstract

Neighborhood safety and its perception are important determinants of citizens’ health and well-being. Contemporary urban design guidelines often advocate urban forms that encourage natural surveillance or “eyes on the street” to promote community safety. However, assessing a neighborhood’s level of natural surveillance is challenging due to its subjective nature and a lack of relevant data. We propose a method for measuring natural surveillance at scale by employing a combination of street-level imagery and computer vision techniques. We detect windows on building facades and calculate sightlines from the street level and surrounding buildings across forty neighborhoods in Amsterdam, the Netherlands. By correlating our measurements with the city’s Safety Index, we also validate how our method can be used as an estimator of neighborhood safety. We show how perceived safety varies with window level and building distance from the street, and we find a non-linear relationship between natural surveillance and (perceived) safety.

Timo Van Asten, Vasileios Milias, Alessandro Bozzon, Achilleas Psyllidis

Chapter 13. Automatic Evaluation of Street-Level Walkability Based on Computer Vision Techniques and Urban Big Data

A Case Study of Kowloon West, Hong Kong

Abstract

The walkability of an urban environment is a critical aspect of urban design and planning, and has a direct impact on the quality of life for residents. Therefore, it is essential to conduct a systematic evaluation of the pedestrian environment to improve the walkability of a city. In recent years, there has been a growing emphasis on the application of automated evaluation methods, incorporating artificial intelligence and urban big data analysis. This study proposes a systematic walkability evaluation index with automated measurement capabilities, and corresponding measurement pipelines utilizing computer vision techniques as well as urban big data. To demonstrate the utility of the proposed index and measurement methods, this study conducts a systematic measurement of street-level walkability in the Kowloon West of Hong Kong as a case study.

Lu Huang, Takuya Oki, Sachio Muto, Hongjik Kim, Yoshiki Ogawa, Yoshihide Sekimoto

Chapter 14. Promoting Sustainable Travel Through a Web-Based Tourism Support System

Abstract

In Japan, distributed travel is recently promoted in order to prevent both the problems associated with overtourism and the spread of the COVID-19 pandemic in urban tourist destinations. The present study developed a tourism support system by integrating web-geographic information system (Web-GIS), recommendation system and social network services (SNS). The system has two unique key functions (the functions of tourism congestion display and tourist attraction recommendation) in order to promote distributed travel during the sightseeing planning stage. The system was operated for six weeks targeting Kamakura City in Kanagawa Prefecture, Japan. The evaluation results for the system performance revealed that the function of tourism congestion display can promote tourism that takes congestion periods and areas into consideration. It also showed that the function of tourist attraction recommendation can provide users with novel tourist attraction recommendations and achieve high levels of intent to visit recommended tourist attractions.

Yudai Kato, Kayoko Yamamoto

Chapter 15. Applying the AURIN Walkability Index at the Metropolitan and Local Levels by Sex and Age in Australia

Abstract

Apart from the ever-growing body of research aiming to develop novel walkability assessment tools, conducting systematic literature reviews on these planning support tools has been emerging as a new research theme in the field of urban analytics. While the walkability index of the Australian Urban Research Infrastructure Network (AURIN) has been used in several studies in the last decade, there is still a need for comprehensive application and correlation analyses of this tool at different geographical scales and with various socio-demographics and walking behaviours as covariates. To analyse the level of responsiveness of this tool, this study applies it at two different national and metropolitan scales comparing the walkability of 175 Local Government Areas in all States and Territories as well as 3047 neighbourhoods in the Greater Adelaide Metropolitan Area. Although the body of knowledge criticises using large units of analysis in the walkability assessments, the AURIN Walkability Index (AWI) is more representative at the national level. Furthermore, in each unit of analysis, the walk-to-work behaviour of females and the youngest age groups demonstrate the strongest associations with the walkability scores.

Arsham Bassiri Abyaneh, Andrew Allan, Johannes Pieters, Sekhar Somenahalli, Ali Soltani

Chapter 16. Predicting Urban Heat Island Mitigation with Random Forest Regression in Belgian Cities

Abstract

An abundance of impervious surfaces like building roofs in densely populated cities make green roofs a suitable solution for urban heat island (UHI) mitigation. Therefore, we employ random forest (RF) regression to predict the impact of green roofs on the surface UHI (SUHI) in Liege, Belgium. While there have been several studies identifying the impact of green roofs on UHI, fewer studies utilize a remote-sensing-based approach to measure impact on Land Surface Temperatures (LST) that are used to estimate SUHI. Moreover, the RF algorithm, can provide useful insights. In this study, we use LST obtained from Landsat-8 imagery and relate it to 2D and 3D morphological parameters that influence LST and UHI effects. Additionally, we utilise parameters that influence wind (e.g., frontal area index). We simulate the green roofs by assigning suitable values of normalised difference-vegetation index and built-up index to the buildings with flat roofs. Results suggest that green roofs decrease the average LST.

Mitali Yeshwant Joshi, Daniel G. Aliaga, Jacques Teller

Chapter 17. A Framework to Probe Uncertainties in Urban Cellular Automata Modelling Using a Novel Framework of Multilevel Density Approach: A Case Study for Wallonia Region, Belgium

Abstract

Urban expansion models are widely used to understand, analyze and predict any peculiar scenario based on input probabilities. Modelling and uncertainty are concomitant, and can occur due to reasons ranging from–discrepancies in input variables, unpredictable model parameters, spatio-temporal variability between observations, or malfunction in linking model variables under two different spatio-temporal scenarios. However, uncertainties often occur because of the interplay of model elements, structures, and the quality of data sources employed; as input parameters influence the behavior of cellular automaton (CA) models. Our study aims to address these uncertainties. While most studies consider neighborhood effects, timestep and spatial resolution, our study uniquely focuses on the susceptibility of multi density classes and varying cell size on uncertainty. Hence this chapter offers a theoretical elucidation of the concepts, sources, and strategies for managing uncertainty under various criteria as well as an algorithm for enumerating the model’s accuracy for Wallonia, Belgium.

Anasua Chakraborty, Ahmed Mustafa, Hichem Omrani, Jacques Teller

Backmatter

Titel: Intelligence for Future Cities
herausgegeben von: Robert Goodspeed
Raja Sengupta
Marketta Kyttä
Christopher Pettit
Verlag: Springer Nature Switzerland
Electronic ISBN: 978-3-031-31746-0
Print ISBN: 978-3-031-31745-3
DOI: https://doi.org/10.1007/978-3-031-31746-0