Understanding complex urban systems : integrating multidisciplinary data in urban models
著者
書誌事項
Understanding complex urban systems : integrating multidisciplinary data in urban models
(Understanding complex systems / founding editor, J.A. Scott Kelso)(Springer complexity)
Springer, c2016
大学図書館所蔵 全2件
  青森
  岩手
  宮城
  秋田
  山形
  福島
  茨城
  栃木
  群馬
  埼玉
  千葉
  東京
  神奈川
  新潟
  富山
  石川
  福井
  山梨
  長野
  岐阜
  静岡
  愛知
  三重
  滋賀
  京都
  大阪
  兵庫
  奈良
  和歌山
  鳥取
  島根
  岡山
  広島
  山口
  徳島
  香川
  愛媛
  高知
  福岡
  佐賀
  長崎
  熊本
  大分
  宮崎
  鹿児島
  沖縄
  韓国
  中国
  タイ
  イギリス
  ドイツ
  スイス
  フランス
  ベルギー
  オランダ
  スウェーデン
  ノルウェー
  アメリカ
注記
Includes bibliographical references and index
内容説明・目次
内容説明
This book is devoted to the modeling and understanding
of complex urban systems. This second volume of Understanding Complex Urban
Systems focuses on the challenges of the modeling tools, concerning, e.g., the
quality and quantity of data and the selection of an appropriate modeling
approach. It is meant to support urban decision-makers-including municipal
politicians, spatial planners, and citizen groups-in choosing an appropriate
modeling approach for their particular modeling requirements. The contributors
to this volume are from different disciplines, but all share the same goal:
optimizing the representation of complex urban systems. They present and
discuss a variety of approaches for dealing with data-availability problems and
finding appropriate modeling approaches-and not only in terms of computer
modeling.
The selection of articles featured in this volume reflect
a broad variety of new and established modeling approaches such as:
- An argument for using Big Data methods in
conjunction with Agent-based Modeling;
- The introduction of a participatory approach
involving citizens, in order to utilize an Agent-based Modeling approach to
simulate urban-growth scenarios;
- A presentation of semantic modeling to enable a
flexible application of modeling methods and a flexible exchange of data;
- An article about a nested-systems approach to
analyzing a city's interdependent subsystems (according to these subsystems'
different velocities of change);
- An article about methods that use Luhmann's system
theory to characterize cities as systems that are composed of flows;
- An article that demonstrates how the Sen-Nussbaum
Capabilities Approach can be used in urban systems to measure household well-being
shifts that occur in response to the resettlement of urban households;
- A final article that illustrates how Adaptive Cycles
of Complex Adaptive Systems, as well as innovation, can be applied to gain a
better understanding of cities and to promote more resilient and more
sustainable urban futures.
目次
Introduction.- Combining
Agent-Based Modeling with Big Data Methods to Support.- Urban Development
Simulator: How Can Participatory Data Gathering Support Modeling of Complex
Urban Systems.- Bypassing Data Unavailability
in Urban Systems Modeling.- Big Data? No Data. How to Pro-actively Deal
With Unexpected Change in Cities Where (Big) Data is Not
Available.- Conceptualizing the Urban System as a System of Flows.- Operationalizing
the Capabilities Approach for Modeling Household Welfare Shifts in Urban
Systems: A Special Focus on the Transportation Outcomes of Urban
Resettlement.- Interventions in Complex Urban Systems: How to Enable
Modeling to Account for Disruptive Innovation.
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