Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/139101
Title: ENHANCING THE URBAN DESIGN PROCESS FROM A DATA FAMILIARITY PERSPECTIVE
Authors: LIU YUEZHONG
ORCID iD:   orcid.org/0000-0001-9717-8953
Keywords: Energy Performance, Micro-Scale Weather Data, TMY, UHI, S3VM, Familiar and Unfamiliar
Issue Date: 18-Jan-2017
Citation: LIU YUEZHONG (2017-01-18). ENHANCING THE URBAN DESIGN PROCESS FROM A DATA FAMILIARITY PERSPECTIVE. ScholarBank@NUS Repository.
Abstract: With technological advances leading to new urban practices and contemporary problems, urban designers face significantly increasing pressure to process cross-disciplinary and transdisciplinary data for decision-making during the urban design process. From the design perspective, the data could be segmented into two groups: familiar and unfamiliar. Currently how to explore/exploit the unfamiliar data remains a big challenge for designers during the design process. Hence, this research identifies major research questions that may be possible to investigate with the unfamiliar data and identifies three themes for the use of data familiarity perspective in improving/optimizing the urban design process: a) accuracy, b) prediction and c) guidance. The results of three case studies prove the proposed data method could inform and guide the designer pursuing energy performance during the urban design process. The data familiarity perspective method will play a vital role for decision-making for urban design in the future.
URI: http://scholarbank.nus.edu.sg/handle/10635/139101
Appears in Collections:Ph.D Theses (Open)

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