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E-raamat: Intelligence for Future Cities: Planning Through Big Data and Urban Analytics

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  • Formaat: PDF+DRM
  • Sari: The Urban Book Series
  • Ilmumisaeg: 02-Jun-2023
  • Kirjastus: Springer International Publishing AG
  • Keel: eng
  • ISBN-13: 9783031317460
  • Formaat - PDF+DRM
  • Hind: 271,08 €*
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  • Formaat: PDF+DRM
  • Sari: The Urban Book Series
  • Ilmumisaeg: 02-Jun-2023
  • Kirjastus: Springer International Publishing AG
  • Keel: eng
  • ISBN-13: 9783031317460

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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).
Introduction.- Part 1: Digital cities.- Hybrid smartness: Seeking a
balance between top-down and bottom-up smart city approaches.- Interpreting
the smart city through topic modelling.- The venue code: digital
surveillance, spatial (re)organization, and infrastructural power during the
COVID pandemic in China.- The platformization of public participation:
Considerations for urban planners navigating new engagement tools.- Part 2:
Mobility futures.- Shared micro-mobility: A panacea or a patch for our urban
transport problems?- Understanding bikeability: Insight into the cyclingcity
relationship using massive dockless bike-sharing records in Beijing.-
Disclosing the impact of micro-level environmental characteristics on
dockless bikeshare trip volume: A case study of Ithaca.- A planning support
system for boosting bikeability in Seoul.- Integrating big data and a travel
survey to understand the gender gap in ride-hailing usage: evidence from
Chengdu, China.- Urban airspace route planningfor advanced air mobility
operations.- Part 3: Fine-scale urban analysis.- Eyes on the Street:
Estimating natural surveillance along Amsterdams city streets using
street-level imagery.- Automatic evaluation of street-level walkability based
on computer vision techniques and urban big data: A case study of Kowloon
West, Hong Kong.- Promoting sustainable travel through a web-based tourism
support system.- Applying the Aurin walkability index at the metropolitan and
local levels by sex and age in Australia.- Predicting urban heat island
mitigation with random forest regression in Belgian cities.- A framework to
probe the uncertainties in urban cellular automata modeling with multilevel
density for the Wallonia region, Belgium.