What You See Is What You Get: Data-Informed Workflow in Design for Architecture and Urbanism
Javier Argota Sanchez-Vaquerizo
10.1184/R1/7063361.v1
https://kilthub.cmu.edu/articles/thesis/What_You_See_Is_What_You_Get_Data-Informed_Workflow_in_Design_for_Architecture_and_Urbanism/7063361
<p>This research leverages computer vision with statistical,
computational, and urban design techniques to reveal insightful and helpful
relations between spatial features and patterns of spatial use. Three case
studies are developed in two locations, in Madrid and Pittsburgh, with
distinct spatial and
utilization characteristics for covering
diverse conditions through
two types of experiments. The
first one develops a bivariate analysis between parameters from data that
describe the layout
and use of
each location for identifying correlations between spatial features
and utilization patterns.
The second experiment uses machine-learning techniques for spatial
clustering supported by matching temporal signatures of the detected
occupations by the developed computer vision algorithms. </p><p><br></p>
<p>The proposed design
framework yields new
types of data
about people’s interactions
with their urban
built environment for
generating new knowledge
to inform design
and policy decisions
more effectively and
expanding the capabilities
of practitioners for
focusing on exploring new scenarios. This thesis
advocates for expanding design through data.</p>
2018-05-10 00:00:00
urban space
data science
computer vision
sensor fusion
machine learning
urban behavior
computational design