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CumInCAD is a Cumulative Index about publications in Computer Aided Architectural Design
supported by the sibling associations ACADIA, CAADRIA, eCAADe, SIGraDi, ASCAAD and CAAD futures

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_id	caadria2023_384
id	caadria2023_384
authors	Dong, Jiahua, Jiang, Qingrui, Wang, Anqi and Wang, Yuankai
year	2023
title	Urban Cultural Inheritance: Generative Adversarial Networks (GANs) Assisted Street Facade Design in Virtual Reality (VR) Environments Based on Hakka Settlements in Hong Kong
doi	https://doi.org/10.52842/conf.caadria.2023.1.473
source	Immanuel Koh, Dagmar Reinhardt, Mohammed Makki, Mona Khakhar, Nic Bao (eds.), HUMAN-CENTRIC - Proceedings of the 28th CAADRIA Conference, Ahmedabad, 18-24 March 2023, pp. 473–482
summary	In Hong Kong, the Hakka settlements are the home of indigenous people who have been involved in agriculture and fishing for over 200 years, which has a special place in Hong Kong’s history. However, these settlements are gradually being abandoned as ghost towns due to rapid urbanisation, where the city is progressively constructing high-density habitats to accommodate the exponentially increased population since the 1950s. This challenges designers to rethink means of preserving urban cultural heritage, while engaging in continuous urban regeneration processes. This study investigates workflows to detect historical building styles in one of the most densely-populated cities in the world - Hong Kong - that further deployed in human-computer interfaces in the virtual reality (VR) environment as a collaborative and suggestive design -107958641080
keywords	Urban Culture Inheritance, Hakka Settlements, Facade Generation, Human-Computer Interaction (HCI), Virtual Reality (VR)
series	CAADRIA
email
last changed	2023/06/15 23:14

_id	sigradi2023_387
id	sigradi2023_387
authors	Dong, Jiahua, Lin, Shuiyang and van Ameijde, Jeroen
year	2023
title	Predicting Network Integration Based on Satellite Imagery Around High-Density Public Housing Estates Through Machine Learning
source	García Amen, F, Goni Fitipaldo, A L and Armagno Gentile, Á (eds.), Accelerated Landscapes - Proceedings of the XXVII International Conference of the Ibero-American Society of Digital Graphics (SIGraDi 2023), Punta del Este, Maldonado, Uruguay, 29 November - 1 December 2023, pp. 795–806
summary	In studies focusing on environmental and health aspects of urban planning, the integration of road networks within the built environment emerges as an important metric for assessing the livability and healthiness of neighborhoods. The complexity and diversity of the road networks are significant for shaping vibrant streets. In Hong Kong’s ongoing construction program of large-scale public housing estates, the design prioritizes the connectivity of pedestrian circulation to foster social interaction among residents and encourage the utilization of recreational facilities. In this study, an analytical framework is developed to interpret public housing estate spatial layout based on satellite imagery. It extracts road networks using neural networks and vectorizes results to analyze network integration around estates to predict social interactions. The aim of this process is to employ a machine learning workflow to analyze options for newly planned estates, where the design configuration can be further optimized based on its potential to stimulate social engagement and community interaction. Due to the scalability and universality of the method, the research can contribute to improved road networks and sociable housing complexes in Hong Kong, or in other international cities of similar density and vibrancy.
keywords	Network Integration, Spatial Structure, Satellite Imagery, Machine Learning, Hong Kong Public Housing
series	SIGraDi
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last changed	2024/03/08 14:07

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