scholarly journals Spatial Information and the Legibility of Urban Form: Big Data in Urban Morphology

2019 ◽  
Author(s):  
Geoff Boeing
Keyword(s):  
Big Data ◽  
Urban Planning ◽  
Urban Form ◽  
Data Science ◽  
Spatial Information ◽  
Smart Cities ◽  
Urban Morphology ◽  
Urban Fabric ◽  
Form Analysis ◽  
Study Sites

Urban planning and morphology have relied on analytical cartography and visual communication tools for centuries to illustrate spatial patterns, propose designs, compare alternatives, and engage the public. Classic urban form visualizations – from Giambattista Nolli’s ichnographic maps of Rome to Allan Jacobs’s figure-ground diagrams of city streets – have compressed physical urban complexity into easily comprehensible information artifacts. Today we can enhance these traditional workflows through the Smart Cities paradigm of understanding cities via user-generated content and harvested data in an information management context. New spatial technology platforms and big data offer new lenses to understand, evaluate, monitor, and manage urban form and evolution. This paper builds on the theoretical framework of visual cultures in urban planning and morphology to introduce and situate computational data science processes for exploring urban fabric patterns and spatial order. It demonstrates these workflows with OSMnx and data from OpenStreetMap, a collaborative spatial information system and mapping platform, to examine street network patterns, orientations, and configurations in different study sites around the world, considering what these reveal about the urban fabric. The age of ubiquitous urban data and computational toolkits opens up a new era of worldwide urban form analysis from integrated quantitative and qualitative perspectives.

scholarly journals Exploring the Influence of Urban Form on Urban Vibrancy in Shenzhen Based on Mobile Phone Data

2018 ◽  
Vol 10 (12) ◽  
pp. 4565 ◽  
Author(s):  
Lingjun Tang ◽  
Yu Lin ◽  
Sijia Li ◽  
Sheng Li ◽  
Jingyi Li ◽  
...  
Keyword(s):  
Big Data ◽  
Mobile Phone ◽  
Urban Form ◽  
City Planning ◽  
Human Perception ◽  
Urban Morphology ◽  
Mobile Phone Data ◽  
Important Indicator ◽  
Spatial And Temporal Scales ◽  
Functional Zones

Urban vibrancy is an important indicator of the attractiveness of a city and its potential for comprehensive, healthy and sustainable development in all aspects. With the development of big data, an increasing number of datasets can be used to analyse urban vibrancy on fine spatial and temporal scales from the perspective of human perception. In this study, we applied mobile phone data as a proxy for local vibrancy in Shenzhen and constructed a comprehensive framework for the factors that influence urban vibrancy, especially in terms of urban morphology and space syntax. In addition, the popular geographically and temporally weighted regression (GTWR) method was used to explore the spatiotemporal relationships between vibrancy and its influencing factors. The spatial and temporal coefficients are presented through maps. The conclusions of this attempt to study urban vibrancy with urban big data have significant implications for helping urban planners and policy makers optimize the spatial layouts of urban functional zones and perform high-quality city planning.

scholarly journals The Nine Forms of the French Riviera: Classifying Urban Fabrics from the Pedestrian Perspective.

2017 ◽  
Author(s):  
Alessandro Araldi ◽  
Giovanni Fusco
Keyword(s):  
Spatial Patterns ◽  
Urban Space ◽  
Metropolitan Area ◽  
Urban Form ◽  
Spatial Organization ◽  
Spatial Relations ◽  
Urban Morphology ◽  
Urban Fabric ◽  
Central Cities ◽  
French Riviera

The Nine Forms of the French Riviera: Classifying Urban Fabrics from the Pedestrian Perspective. Giovanni Fusco, Alessandro Araldi ¹Université Côte-Azur, CNRS, ESPACE - Bd. Eduard Herriot 98. 06200 Nice E-mail: [email protected], [email protected] Keywords: French Riviera, Urban Fabrics, Urban Form Recognition, Geoprocessing Conference topics and scale: Tools of analysis in urban morphology     Recent metropolitan growth produces new kinds of urban fabric, revealing different logics in the organization of urban space, but coexisting with more traditional urban fabrics in central cities and older suburbs. Having an overall view of the spatial patterns of urban fabrics in a vast metropolitan area is paramount for understanding the emerging spatial organization of the contemporary metropolis. The French Riviera is a polycentric metropolitan area of more than 1200 km2 structured around the old coastal cities of Nice, Cannes, Antibes and Monaco. XIX century and early XX century urban growth is now complemented by modern developments and more recent suburban areas. A large-scale analysis of urban fabrics can only be carried out through a new geoprocessing protocol, combining indicators of spatial relations within urban fabrics, geo-statistical analysis and Bayesian data-mining. Applied to the French Riviera, nine families of urban fabrics are identified and correlated to the historical periods of their production. Central cities are thus characterized by the combination of different families of pre-modern, dense, continuous built-up fabrics, as well as by modern discontinuous forms. More interestingly, fringe-belts in Nice and Cannes, as well as the techno-park of Sophia-Antipolis, combine a spinal cord of connective artificial fabrics having sparse specialized buildings, with the already mentioned discontinuous fabrics of modern urbanism. Further forms are identified in the suburban and “rurban” spaces around central cities. The proposed geoprocessing procedure is not intended to supersede traditional expert-base analysis of urban fabric. Rather, it should be considered as a complementary tool for large urban space analysis and as an input for studying urban form relation to socioeconomic phenomena. References   Conzen, M.R.G (1960) Alnwick, Northumberland : A Study in Town-Planning Analysis. (London, George Philip). Conzen, M.P. (2009) “How cities internalize their former urban fringe. A cross-cultural comparison”. Urban Morphology, 13, 29-54. Graff, P. (2014) Une ville d’exception. Nice, dans l'effervescence du 20° siècle. (Serre, Nice). Yamada I., Thill J.C. (2010) “Local indicators of network-constrained clusters in spatial patterns represented by a link attribute.” Annals of the Association of American Geographers, 100(2), 269-285. Levy, A. (1999) “Urban morphology and the problem of modern urban fabric : some questions for research”, Urban Morphology, 3(2), 79-85. Okabe, A. Sugihara, K. (2012) Spatial Analysis along Networks: Statistical and Computational Methods. (John Wiley and sons, UK).

scholarly journals A study on the history of urban morphology in China based on discourse analysis

2017 ◽  
Author(s):  
Limeng Zhang ◽  
Andong Lu
Keyword(s):  
Discourse Analysis ◽  
Urban Planning ◽  
Urban Form ◽  
Urban Morphology ◽  
Town Planning ◽  
Urban Conservation ◽  
Morphological Approach ◽  
History Of ◽  
Urban Issues ◽  
Definition Of

A study on the history of urban morphology in China based on discourse analysis Limeng Zhang¹, Andong Lu¹ ¹School of Architecture and Urban Planning, Nanjing University. Nanjing University Hankou Road 22#, Gulou District, Nanjing, China E-mail: [email protected], [email protected] Key words: urban morphology, terminology, discourse analysis Conference topics and scale: Literature review   (Supported by the Natural Science Foundation of China, Grant No.: 51478215)   Urban morphology is a method widely used in China in the field of urban design and urban conservation. Since its first introduction to the Chinese context about 20 years ago, the key ideas and concepts of urban morphology underwent a significant phenomenon of ‘lost in translation’. Different origins of morphological thoughts, different versions of translation, as well as different disciplinary context, have all together led to a chaotic discourse. This paper reviews the key Chinese articles in the field of urban morphology since 1982 and draws out a group of persistent keywords, such as evolution, axis, urban fringe belt, plan unit and plot, that characterize the morphological approach to urban issues. By reviewing the transformation of the definition of these keywords, this paper aims to generate an evolutionary map of landmark ideas and concepts, based on which, four stages in the development of urban morphology in China can be identified: emergence, growth, maturity, practice. The mapping methodology could be extrapolated to other words, and the obtained evolutionary map could be a basic tool for further study.   References Conzen M. R. G.,  Alnwick, Northumberland: A Study in Town-plan Analysis [M] 1960. ( London, George Philip). J. W. R. Whitehand, and Kai Gu. ‘Urban conservation in China: Historical development, current practice and morphological approach’ [J], Town Planning Review, 2007 (5), 615-642. Duan Jin, and Qiu Guochao. 'The Emergence and Development of Overseas Urban Morphology Study' [J], Urban Planning Forum, 2008(5):34-42. M. P. Conzen, Kai Gu, J. W. R. Whitehand. Comparing traditional urban form in China and Europe: a fringe belt approach [D]. Urban Geography, 2011.

scholarly journals Green Internet of Things and Big Data Application in Smart Cities Development

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Zhai Yang ◽  
Liu Jianjun ◽  
Humaira Faqiri ◽  
Wasswa Shafik ◽  
Alanazi Talal Abdulrahman ◽  
...  
Keyword(s):  
Big Data ◽  
Internet Of Things ◽  
Life Span ◽  
Information And Communication Technologies ◽  
Resource Sharing ◽  
Wireless Sensors ◽  
Data Science ◽  
Raw Materials ◽  
Technological Development ◽  
Smart Cities

This study reveals that increases in the global population command an augmented demand for products and services that calls for more effective ways of using existing natural resources and materials. The recent development of information and communication technologies, which had a great impact on many areas, also had a damaging effect on the environment and human health. Therefore, societies are moving toward a greener future by reducing the consumption of nonrenewable materials, raw materials, and resources while at the same time decreasing energy pollution and consumption. Since information technology is considered a tool for solving ecological difficulties, the green Internet of things (G-IoT) is playing a vital role in creating a sustainable home. Extensive data analysis is required to obtain a valuable overview of the large and diverse data generated by the G-IoT. The gathered information will facilitate forecasting, decision-making, and other activities related to smart urban services and then contribute to the incessant development of G-IoT technology. Therefore, even if sustainable and smart cities become an actuality, the G-IoT approach and the knowledge gained through big data (BD) analysis will make cities more sustainable, safer, and smarter. The goal of this article is to combine innovation in technological development with the main focus on resource sharing in creating cities that improve the quality of life while reducing pollution and realizing more efficient use of the raw materials. In the practice of big data science, it is always of interest to provide the best description of the data under consideration. Recent studies have pointed out the applicability of the statistical distributions in modeling data in applied sciences. In this article, we introduce a new family of statistical models to provide the best description of the life span of the wireless sensors network’s data. Based on the proposed approach, a special submodel called new exponent power-Weibull distribution is studied in detail. The applicability of the proposed model is shown by analyzing the life span of the wireless sensors network’s data.

scholarly journals The Challenge of Big Data and Data Science

2019 ◽  
Vol 22 (1) ◽  
pp. 297-323 ◽  
Author(s):  
Henry E. Brady
Keyword(s):  
Big Data ◽  
Data Science ◽  
Smart Cities ◽  
Video Data ◽  
Cyber Warfare ◽  
Ethical Challenges ◽  
Cyber Terrorism ◽  
Social Scientists ◽  
The Media ◽  
Audio Video

Big data and data science are transforming the world in ways that spawn new concerns for social scientists, such as the impacts of the internet on citizens and the media, the repercussions of smart cities, the possibilities of cyber-warfare and cyber-terrorism, the implications of precision medicine, and the consequences of artificial intelligence and automation. Along with these changes in society, powerful new data science methods support research using administrative, internet, textual, and sensor-audio-video data. Burgeoning data and innovative methods facilitate answering previously hard-to-tackle questions about society by offering new ways to form concepts from data, to do descriptive inference, to make causal inferences, and to generate predictions. They also pose challenges as social scientists must grasp the meaning of concepts and predictions generated by convoluted algorithms, weigh the relative value of prediction versus causal inference, and cope with ethical challenges as their methods, such as algorithms for mobilizing voters or determining bail, are adopted by policy makers.

Bootstrapping Urban Planning

2020 ◽  
pp. 217-246
Author(s):  
Ankur Lohachab
Keyword(s):  
Big Data ◽  
Urban Planning ◽  
Smart Cities ◽  
Big Data Analytics ◽  
Sensitive Information ◽  
Ongoing Research ◽  
Research Issues ◽  
Advantages And Disadvantages ◽  
Efficient Management ◽  
Different Characteristics

Rapid growth of embedded devices and population density in IoT-based smart cities provides great potential for business and opportunities in urban planning. For addressing the current and future needs of living, smart cities have to revitalize the potential of big data analytics. However, a colossal amount of sensitive information invites various computational challenges. Moreover, big data generated by the IoT paradigm acquires different characteristics as compared to traditional big data because it contains heterogeneous unstructured data. Despite various challenges in big data, enterprises are trying to utilize its true potential for providing proactive applications to the citizens. In this chapter, the author finds the possibilities of the role of big data in the efficient management of smart cities. Representative applications of big data, along with advantages and disadvantages, are also discussed. By delving into the ongoing research approaches in securing and providing privacy to big data, this chapter is concluded by highlighting the open research issues in the domain.

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