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Abstract
The overarching objective of this thesis is to develop processes that incentivize private investment in architecture and urban design such that it enhances the public good. Existing literature on this topic tends to lack quantitative measures for explaining how architectural design impacts social sustainability. Currently, many common decision-making frameworks are built upon direct economic metrics that inform architectural designs. This thesis therefore explores humancentered concepts that can be quantified and synthesized in order to transform intuitive and theoretical knowledge regarding the impact of architectural design on human health and well-being into evidence-based decision-making processes. Feeding this knowledge into the design stages of new projects would yield more informed design decisions and contribute to a mostly qualitative approaches to assess the impact of architecture on human behavior and well-being. Through extensive literature research, this thesis presents previously applied data collection methods and empirical findings from space-use relationships and concludes that technological advances in collecting human-centric data would enrich and enhance qualitative empirical findings within this field. The thesis identifies trade-offs between varying space typologies and concentrates on opposing and complimentary design elements that influence behavior and occupancy choices when compared on a building and city scale. It develops measurable indicator frameworks that synthesize traditional and modern data sources for better integration into architectural design processes, and demonstrate the technical feasibility of recognizing basic human activities with digital technology in real-world applications. Based on a newly constructed university building in the US, this thesis also contributes to the field of computer science by demonstrating how raw-data from image-based sensors can be extracted and transformed to useful information for analyzing space-use relationships. The main contribution of this thesis is however dedicated to the intersection of quantitative human data and architectural research, in which real-world scenarios are designed to investigate the use of social spaces in learning environments. In combination with literature
based empirical findings, the accumulated data can be used to inform the early stages of the architectural design processes for new spaces and buildings. This research demonstrates how structured human data can assist in communicating these findings to architects, and support them in providing a business case for incorporating human-oriented design aspects. This allows architects and urban planners to make an empirically based case, demonstrating to stakeholders how socially sustainable designs can benefit the larger community through improved user satisfaction and well being.
based empirical findings, the accumulated data can be used to inform the early stages of the architectural design processes for new spaces and buildings. This research demonstrates how structured human data can assist in communicating these findings to architects, and support them in providing a business case for incorporating human-oriented design aspects. This allows architects and urban planners to make an empirically based case, demonstrating to stakeholders how socially sustainable designs can benefit the larger community through improved user satisfaction and well being.
Original language | English |
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Publisher | Technical University of Denmark |
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Number of pages | 256 |
Publication status | Published - 2022 |
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Dive into the research topics of 'Mapping Micro-Contexts: Informing Architectural Urban Design and Developement'. Together they form a unique fingerprint.Projects
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Mapping micro-contexts: Informing architectural urban design and development
Jens, K. (PhD Student), Gregg, J. S. (Main Supervisor), Lehmann, S. (Supervisor), Strømann-Andersen, J. B. (Supervisor), Toftum, J. (Examiner), Berg, P. (Examiner), Dreiseitl, H. (Examiner), Str?mann-Andersen, J. B. (Supervisor) & Toftum, J. (Examiner)
01/03/2018 → 30/09/2021
Project: PhD