Data-driven design for Architecture and Environment Integration

Rapid urbanization and related land cover and land use changes are primary causes of climate change, and of environmental and ecosystem degradation. Sustainability problems are becoming increasingly complex due to these developments. At the same time vast amounts of data on urbanization, constructi...

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Main Authors: Defne Sunguroğlu Hensel, Jakub Tyc, Michael Hensel
Format: Article
Language:English
Published: Stichting OpenAccess 2022-05-01
Series:Spool
Subjects:
Online Access:https://spool.ac/index.php/spool/article/view/195
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author Defne Sunguroğlu Hensel
Jakub Tyc
Michael Hensel
author_facet Defne Sunguroğlu Hensel
Jakub Tyc
Michael Hensel
author_sort Defne Sunguroğlu Hensel
collection DOAJ
description Rapid urbanization and related land cover and land use changes are primary causes of climate change, and of environmental and ecosystem degradation. Sustainability problems are becoming increasingly complex due to these developments. At the same time vast amounts of data on urbanization, construction and resulting environmental conditions are being generated. Yet it is hardly possible to gain insights for sustainable plan-ning and design at the same rate as data is generated. Moreover, the complexity of compound sustainability problems requires interdisciplinary approaches that address multiple knowledge fields, multiple dynamics and multiple spatial, temporal and functional scales. This raises a question regarding methods and tools available to planners and architects for tackling these complex issues. To address this problem we are developing an interdisciplinary approach, computational framework and related workflows for multi-domain and trans-scalar modelling that integrate planning and design scales. For this article two lines of research were selected. The first focuses on understanding environments for the purpose of discovering, recovering and adapting land knowledge to different conditions and contexts. This entails an analytical data-integrated computational workflow. The second line of research focuses on designing environments and developing an approach and computational workflow for data-integrated planning and design. These two lines converge in a combined analytical and generative data-integrated computational workflow. This combined approach aims for an intense integration of architectures and environments that we call embedded architectures. In this article we discuss the two lines of research, their convergence, and further research questions.
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spelling doaj.art-e22fa45ebb4b44aa83bb156fcde220932022-12-22T04:30:28ZengStichting OpenAccessSpool2215-08972215-09002022-05-019110.47982/spool.2022.1.02Data-driven design for Architecture and Environment IntegrationDefne Sunguroğlu Hensel0Jakub Tyc1Michael Hensel2Technical University of MunichTU Wien TU Wien Rapid urbanization and related land cover and land use changes are primary causes of climate change, and of environmental and ecosystem degradation. Sustainability problems are becoming increasingly complex due to these developments. At the same time vast amounts of data on urbanization, construction and resulting environmental conditions are being generated. Yet it is hardly possible to gain insights for sustainable plan-ning and design at the same rate as data is generated. Moreover, the complexity of compound sustainability problems requires interdisciplinary approaches that address multiple knowledge fields, multiple dynamics and multiple spatial, temporal and functional scales. This raises a question regarding methods and tools available to planners and architects for tackling these complex issues. To address this problem we are developing an interdisciplinary approach, computational framework and related workflows for multi-domain and trans-scalar modelling that integrate planning and design scales. For this article two lines of research were selected. The first focuses on understanding environments for the purpose of discovering, recovering and adapting land knowledge to different conditions and contexts. This entails an analytical data-integrated computational workflow. The second line of research focuses on designing environments and developing an approach and computational workflow for data-integrated planning and design. These two lines converge in a combined analytical and generative data-integrated computational workflow. This combined approach aims for an intense integration of architectures and environments that we call embedded architectures. In this article we discuss the two lines of research, their convergence, and further research questions. https://spool.ac/index.php/spool/article/view/195Data-driven DesignData-integrated WorkflowsArchitecture and Environment IntegrationUnderstanding EnvironmentsDesigning Environments
spellingShingle Defne Sunguroğlu Hensel
Jakub Tyc
Michael Hensel
Data-driven design for Architecture and Environment Integration
Spool
Data-driven Design
Data-integrated Workflows
Architecture and Environment Integration
Understanding Environments
Designing Environments
title Data-driven design for Architecture and Environment Integration
title_full Data-driven design for Architecture and Environment Integration
title_fullStr Data-driven design for Architecture and Environment Integration
title_full_unstemmed Data-driven design for Architecture and Environment Integration
title_short Data-driven design for Architecture and Environment Integration
title_sort data driven design for architecture and environment integration
topic Data-driven Design
Data-integrated Workflows
Architecture and Environment Integration
Understanding Environments
Designing Environments
url https://spool.ac/index.php/spool/article/view/195
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