Open Daily: 10am - 10pm | Alley door pickup 10am - 7pm 3038 Hennepin Ave Minneapolis, MN
612-822-4611

  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Context-rich Urban Analysis Using Machine Learning: A Case Study in Pittsburgh, PA

Context-rich Urban Analysis Using Machine Learning: A Case Study in Pittsburgh, PA

Rhee, Jinmo

Paperback

General Architecture

ISBN10: 9975347517
ISBN13: 9789975347518
Publisher: Eliva Pr
Published: Dec 8 2020
Pages: 124
Weight: 0.53
Height: 0.32 Width: 6.00 Depth: 9.00
Language: English
This book presents the analytic and generative potential of using machine learning methods on context-rich urban datasets. Working with a dataset of Pittsburgh's urban data, this research proposes a novel method to extract information about each building in the city in ways that reflect its immediate urban context and analyze it in terms of urban homogeneity through machine learning algorithms. The method can identify clusters of urban spaces sharing similar architectural context conditions by statistically calculating features of all building footprints and urban contexts in Pittsburgh. From the clustering results, a new type of map called a 'datadriven map of urban morphological types' can be generated. The interpretations and applications of this map and method will be discussed. From these discussions I will address values, meanings, and potentials of this new method in terms of architectural design, urbanism, and computation.

Also in

General Architecture

View All