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Applied Data Analysis for Urban Planning and Management

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Overview

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This course demonstrates how emerging data sources and analysis methods can be applied to urban planning. It provides practical case studies on big data use in urban environments, including examples of smart cities, climate change adaptation, and more. This course explores how data analysis transforms urban planning, offering insights into modern tools like GIS, big data, and 3D technologies. It equips learners with practical skills to address real-world urban challenges, from climate change to transportation. Designed for students and professionals, it bridges theory and application in a data-driven world. This course is ideal for upper undergraduate and postgraduate students in urban planning, geography, or related fields, as well as professionals in city management or GIS. A basic understanding of urban planning and data analysis is recommended. Learners will gain practical skills to apply data-driven approaches in urban development. This course uses practical examples to explore how urban planners can leverage modern data analysis techniques for better city management. Through case studies and applications, it shows how big data, GIS, and spatial analysis tools can optimize urban planning. This course is based on Applied Data Analysis for Urban Planning and Management, by Alasdair Rae and Cecilia Wong. Copyright ©2021 by Sage Publications Limited. All rights reserved, including rights for text and data mining and training of artificial technologies or similar technologies. Published by Sage Publications Limited, London. Used by arrangement with Sage Publications Limited.

Syllabus

  • Introduction: The Promises and Pitfalls of Data for Urban Planning
    • This module explores the role of data in urban planning, focusing on its limitations, ethical implications, and real-world applications. Learners will gain an understanding of how data can both empower and challenge decision-making in complex urban environments. It also introduces key themes and case studies that shape modern urban analysis.
  • What's New in Urban Data Analytics?
    • This module explores the evolving landscape of urban data analytics, focusing on challenges such as data collection, mining, time-space dynamics, and standardization. Learners will understand how big data and smart city technologies are reshaping urban planning and decision-making processes.
  • Indicators and Urban Planning: The Big Data Opportunities and Challenges
    • This module explores the challenges and opportunities of using big data in urban planning, focusing on data uncertainty, scalable analysis methods, and the development of effective urban indicators. Learners will gain insight into how data can be used to support sustainable urban development and decision-making.
  • Crowdsourced Geographic Information for Urban Planning and Management
    • This module explores the role of crowdsourced geographic information in urban planning and management, focusing on its application in Indonesia. It covers quality standards, community engagement, and real-world case studies to highlight how open data can enhance decision-making and sustainability efforts.
  • Design and Narrative Techniques for Urban Data Visualisation
    • This module explores the design and narrative techniques used in urban data visualisation, focusing on how to create engaging tools that communicate complex information to non-expert audiences. Learners will examine different levels of user interaction, such as exploratory, narrative, and analytics approaches, and analyze real-world examples to understand their impact.
  • City Dashboards and 3D Geospatial Technologies for Urban Planning and Management
    • This module explores the use of city dashboards and 3D geospatial technologies in urban planning and management. Learners will understand how data-driven tools enhance decision-making and public engagement. The content also covers the transition from 2D to 3D visualization for improved urban planning strategies.
  • Data Analytics, Urban Form and Climate Change: The Urban Climate Map
    • This module explores urban climate challenges using frameworks like WUDAPT and LCZ, focusing on understanding urban form, climate impacts, and sustainable planning strategies. Learners will gain insights into data collection, analysis, and the role of urban planning in addressing climate change.
  • Data Analytics and Modelling Accessibility Change of High-Speed Rail Network Development: A Door-to-Door Approach
    • This module explores the impact of high-speed rail (HSR) development on regional accessibility and urban growth. It covers research methods, case studies, and analytical approaches to assess how HSR network expansion affects different cities. Learners will gain insights into evaluating the spatial and economic consequences of transportation infrastructure.
  • Understanding Migrant–Local Neighbourly Relations in Shanghai: Empirical Urban Research in a Data-Sparse Setting
    • This module explores methods for studying intergroup relations in urban China, with a focus on using surveys to analyze migrant and local resident interactions. It covers research design, data collection, and statistical analysis in data-sparse environments. Learners will gain insights into urban social dynamics and empirical research approaches.
  • Conclusion: Beyond Analytics: Planning-Led or Planning-Lag?
    • This module explores the challenges of using data in urban planning, focusing on digital divides, governance issues, and the importance of knowledge know-how for effective data utilization. Learners will gain insights into how data systems can support or hinder planning efforts, especially in times of crisis.

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