Urban Morphology Meets Deep Learning

Moosavi, Vahid

doi:10.1002/9781119815075.ch29

Cited by 7 publications

(4 citation statements)

References 22 publications

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“…Chen et al, 2024;Y. Chen et al, 2022;Milojevic-Dupont et al, 2020;Moosavi, 2022;Wagner et al, 2022). These studies focused on solving certain types of urban problems related to factors such as ecology, transportation, energy, and public health to achieve sustainable urban development.…”

Section: Machine Learning Interventions In Urban Morphology Analysismentioning

confidence: 99%

The Correlation Between Asian Port Cities and Traditional Portuguese Urban Forms Based on Map and Machine Learning Analyses

Chen,

Zheng,

Zheng

2024

Island Studies Journal

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In the 16th and 17th centuries, under the influence of the Portuguese Empire’s overseas expansion and cultural integration, the island city of Macau became an important international trading port in the Eastern Sea, with close ties to the Asian port cities governed by Portugal. This study introduces a new method for comparing urban morphological layouts using machine learning and investigates the potential benefits of combining urban morphological analysis with machine learning techniques. In addition, a combination of urban morphology theory and machine learning is used to excise samples of urban morphology from Portuguese urban geographical information maps. The morphological characteristics of port city areas are further extracted, and training labels for typical Portuguese urban textures are established. Using the YOLOv4 object detection algorithm, the results are compared with the urban textures of typical island and port cities of the Asian Silk Road—Goa in India, Malacca in Malaysia, Macau in China, and Dili in Timor-Leste—revealing the similarities and differences among the port cities in Asia influenced by traditional Portuguese urban practices. The results reveal the relationship between maritime trade and urban form.

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Section: Machine Learning Interventions In Urban Morphology Analysismentioning

confidence: 99%

The Correlation Between Asian Port Cities and Traditional Portuguese Urban Forms Based on Map and Machine Learning Analyses

Chen,

Zheng,

Zheng

2024

Island Studies Journal

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“…The images containing village buildings combined with roads or other environments are represented in binary to explore the integrated influence of these elements. The neural network is implemented to quantify the morphological features into feature vectors (Moosavi, 2017). After dimension reduction, cluster analysis is conducted by calculating the distance between the feature vectors (Cai et al, 2021).…”

Section: Traditional Chinese Village Morphological Feature Extraction...mentioning

confidence: 99%

Traditional Chinese Village Morphological Feature Extraction and Cluster Analysis Based on Multi-source Data and Machine Learning

Wang¹,

Tang²,

Cai³

2023

CAADRIA Proceedings

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This study of traditional village morphology provides a possible entry point for understanding the growth patterns of settlements for sustainable development. This study proposes a hybrid data-driven approach to support quantitative morphological descriptions and to further morphology-related studies using opensource map data and deep learning approaches. We construct a dataset of 6819 traditional villages on the Chinese official list with geometrical, geographic and related no-material information. The images containing village buildings combined with roads or other environments are represented in binary to explore the integrated influence of these elements. The neural network is implemented to quantify the morphological features into feature vectors. After dimension reduction, cluster analysis is conducted by calculating the distance between the feature vectors to reveal five main types of Chinese traditional village patterns. The proposed method considers their overall spatial form and other factors such as size, transportation, graphical structure, and density. At the same time, it explores a framework using machine learning in the conservation and renewal work. And it also shows the possibility of data-driven methods for design and decision making.

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“…For each street, the suitability for superblock design is assessed on the basis of urban characteristics and the street network topology. The developed geospatial and network analysis for the identification of superblocks and miniblocks relies on a graph-based representation of the street network, which is downloaded and processed from OpenStreetMap, a commonly used volunteered geographic information data source 33 .…”

Section: Geospatial Modelling and Network Analysismentioning

confidence: 99%

The potential of implementing superblocks for multifunctional street use in cities

Eggimann

2022

Nat Sustain

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Urban Morphology Meets Deep Learning

Cited by 7 publications

References 22 publications

The Correlation Between Asian Port Cities and Traditional Portuguese Urban Forms Based on Map and Machine Learning Analyses

The Correlation Between Asian Port Cities and Traditional Portuguese Urban Forms Based on Map and Machine Learning Analyses

Traditional Chinese Village Morphological Feature Extraction and Cluster Analysis Based on Multi-source Data and Machine Learning

The potential of implementing superblocks for multifunctional street use in cities

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