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Herausgeber: 
  • Michael Batty
  • David S. Jones
  • Ali Cheshmehzangi
  • Zaheer Allam
  • City Information Modelling 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 2 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   i.d.R. innert 5-10 Tagen versandfertig
    Veröffentlichung:  März 2025  
    Genre:  EDV / Informatik 
     
    Bauingenieur-, Vermessungs- und Bauwesen / bigdata / BuildingInformationModelling/BIM / CityInformationModelling/CIM / Computeranwendungen in Industrie und Technologie / Kommunal-, Regional- Landes und Lokalregierung / Optimization / Smartcities
    ISBN:  9789819990160 
    EAN-Code: 
    9789819990160 
    Verlag:  Springer 
    Einband:  Kartoniert  
    Sprache:  English  
    Dimensionen:  H 235 mm / B 155 mm / D 15 mm 
    Gewicht:  417 gr 
    Seiten:  272 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    This is the first book focused on City Information Modelling (CIM) that puts together a collection of recent studies related to concepts and trends in CIM, application and digitization processes/methods, and frameworks and practices of CIM. This emerging topic is important to various research and practice under sectors of the built environment, civil engineering, urban planning, urban design, and urban management. CIM aligns well with smart cities, data-driven urban analytics and optimization, information-based city planning, and future development paradigms. City Information Modelling provides global case study examples in three parts. At first, the contributors offer several examples of 'Concepts and Trends', where CIM is explored further in urban management, urban sustainability, and big data studies. In the second part, the book offers various examples of application and digitization processes or methods related to urban planning and design practices. In the third part, the contributors delve into several examples of CIM frameworks and practices critical to contemporary research, planning and design paradigms, and future practices. This collection is a niche resource for various stakeholders, particularly urban scientists, urban analytics, urban practitioners, and researchers. It will also be a valuable collection for those who work with information-based models, urban optimization models, and big data analytics, particularly from policy and practice perspectives. The findings of this collection help direct future research in CIM and suggest opportunities for big-data urban research, integrated urban models, and holistic frameworks in sustainable cities, smart cities, and future cities.

      



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