Cumincad : CUMINCAD Papers : Search Results

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	ecaade2024_16
id	ecaade2024_16
authors	Yan, Zhanlin; Tu, Han; Stouffs, Rudi
year	2024
title	Implicit Inequality: Urban inequality mapping and boundary detection through big data analysis and machine learning
source	Kontovourkis, O, Phocas, MC and Wurzer, G (eds.), Data-Driven Intelligence - Proceedings of the 42nd Conference on Education and Research in Computer Aided Architectural Design in Europe (eCAADe 2024), Nicosia, 11-13 September 2024, Volume 1, pp. 595–604
doi	https://doi.org/10.52842/conf.ecaade.2024.1.595
summary	To understand and interpret the multi-dimensional nature of the implicit inequalities, we premise “inequality” as a neutral word and map the physical distribution of different elements related to everyone's daily life by utilizing the strength of big data technology and machine learning. Using geo-located street view images and GIS data of points of interest, we analyse the “inequality” condition in multiple dimensions for one specific region in Singapore. We propose a new methodology to detect and analyse “inequality boundaries” in Singapore, revealed in the form of linear elements such as edges and pathways. The methodology functions by developing a scoring system of cells in a regular grid, that belongs to a uniform fishnet covering the whole Singapore region. The cell scores relating to contrasting measures are considered as the foundation for boundary detection. This research successfully identifies boundary locations where areas of opposing measures lay side by side, and determines the specific “inequality boundary”as linear elements within the boundary locations
keywords	Urban inequality, Big data, Machine learning, Urban analysis
series	eCAADe
email
last changed	2024/11/17 22:05

_id	ijac201614206
id	ijac201614206
authors	Yanagawa, Kane
year	2016
title	ReIndustrializing Architecture
source	International Journal of Architectural Computing vol. 14 - no. 2, 158-166
summary	After decades of improving the efficiency and economy of our existing building ecology, instruments of the Third Industrial Revolution are redefining the practice of architecture, both internally and externally. This article focuses on the employment of the Constrained Design Hysteresis methodology as a mediating strategy, in which computational tools for content creation and fabrication can merge in post-industrial societies to effectively reindustrialize the fields of architectural design manufacturing and building. Such reformation of the accepted norms of architectural building practice do not represent a regression of the profession to a pre-industrial mode of building craftsmanship, but an evolution into one that directly addresses various shortcomings of global industrialization, ranging from restrictions imposed by mass production to the creation of social class disparity. In this context, the application of computational tools and processes can both empower and liberate design individuals through the restructuring of the existing industrial manufacturing ecosystems.
keywords	Digital fabrication, design automation, third industrial revolution, constrained design hysteresis, social reform
series	journal
last changed	2016/06/13 08:34

_id	cdrf2022_385
id	cdrf2022_385
authors	Yang Song, Asterios Agkathidis, and Richard Koeck
year	2022
title	Augmented Bricks an Onsite AR Immersive Design to Fabrication Framework for Masonry Structures
source	Proceedings of the 2022 DigitalFUTURES The 4st International Conference on Computational Design and Robotic Fabrication (CDRF 2022)
doi	https://doi.org/https://doi.org/10.1007/978-981-19-8637-6_33
summary	The Augmented Bricks research project aims to develop an immersive design to fabrication framework for the assembly of masonry building components by incorporating robotic fabrication and augmented reality (AR) technologies. Our method incorporates two main phases: firstly, the design phase in which users’ gestures and interactions are being identified in AR for the immersive design and simulation process; secondly, an innovative robotic assembly phase in which users can control a robotic arm for assembly by interacting with the AR user interface (UI). Our framework is validated by the design and assembly of four brick-based columns. Our findings highlight that the proposed design to fabrication framework offers a novel, intuitive design inspiration and experience beyond the traditional design methods. It returns the task of assembling parametric structures with high-tech equipment back to the designers, allowing them to master and participate in the entire design to the fabrication process. The impact of this practice-based research will allow architects and designers to modify and construct their designs more simply and intuitively through the AR environment.
series	cdrf
email
last changed	2024/05/29 14:03

_id	0c8b
authors	Yang, Chien-Tse
year	2001
title	Perspective and Visualization of Dynamic Spaces using VR techniques
source	Architectural Information Management [19th eCAADe Conference Proceedings / ISBN 0-9523687-8-1] Helsinki (Finland) 29-31 August 2001, pp. 479-484
doi	https://doi.org/10.52842/conf.ecaade.2001.479
summary	By the perspective method, it is easy to produce many geometrical spatial forms. But through current computer media, we are able to control dynamic spaces. Under these circumstances, what type of role will traditional architectural elements play in this new era? This research investigates the different perceptions in various spaces. Afterward architectural elements are introduced and we test the effects on the perceptions of different spaces. Therefore the effectiveness of these elements is verified in different types of space.
keywords	Perspective, Conventional/Computer Media, Dynamic Spaces, VR
series	eCAADe
last changed	2022/06/07 07:57

_id	caadria2020_094
id	caadria2020_094
authors	Yang, Chunxia and Gu, Zhuoxing
year	2020
title	Optimization of Public Space Design Based on Reconstruction of Digital Multi-Agent Behavior - --Taking the public space of the North Bund in Shanghai as an example
source	D. Holzer, W. Nakapan, A. Globa, I. Koh (eds.), RE: Anthropocene, Design in the Age of Humans - Proceedings of the 25th CAADRIA Conference - Volume 1, Chulalongkorn University, Bangkok, Thailand, 5-6 August 2020, pp. 335-344
doi	https://doi.org/10.52842/conf.caadria.2020.1.335
summary	This paper uses the digital software platform to build an intelligent multi-agent system. Through the classification of site elements, the Shanghai North Bund waterfront public space elements are classified into different systems such as transportation hub facilities, catering facilities, shopping facilities and leisure venues. The main population activities in this area are classified into different activities such as youth activities, elderly activities, and family activities through user behavior classification. Finally, the intelligent multi-agent particle swarm is built by the dynamic simulation component of grasshopper, and its individual behavior rules and group interaction rules are adjusted to form the crowd moving particle flow. The particle flow interacts with the classified site elements to derive a distribution pattern of population activity in different systems. Particle flow data information and particle distribution patterns after interactive simulation can be the support for urban design evaluation and optimization.
keywords	Self-organizing system; Multi-agent system; Particle property construction; Urban design elements; Waterfront public space
series	CAADRIA
email
last changed	2022/06/07 07:57

_id	caadria2019_202
id	caadria2019_202
authors	Yang, Chunxia, Gu, Zhuoxing and Yao, Ziying
year	2019
title	Adaptive Urban Design Research based on Multi-Agent System - Taking The Urban Renewal Design Of Shanghai Hongkou Port Area As An Example
source	M. Haeusler, M. A. Schnabel, T. Fukuda (eds.), Intelligent & Informed - Proceedings of the 24th CAADRIA Conference - Volume 1, Victoria University of Wellington, Wellington, New Zealand, 15-18 April 2019, pp. 225-234
doi	https://doi.org/10.52842/conf.caadria.2019.1.225
summary	Utilizing digital method to establish a multi-agent simulation platform and establish an interactive simulation between site elements and agents particles behavior. In this study, urban space could not have the absolute frozen state, it is always evolving and self-renewing. We hope to integrate such unstable relationships into urban design methods and programs. By constructing various type of agent particles and the interaction behaviors, we not only directly simulate the flow of people or traffic, but also simulate the public space relationship such as line of sight space, waterfront space accessibility, commercial supporting function layout, and historical and cultural block attraction from a more abstract level. From macro to micro, the result of spatial simulation has an intrinsic close causal relationship with the site's landform, building status, site function, and planning pattern, can be the basis for space generation.
keywords	Self-organization; Multi-agent System; Cluster City; Particle Personality; Site Elements
series	CAADRIA
email
last changed	2022/06/07 07:57

_id	caadria2021_075
id	caadria2021_075
authors	Yang, Chunxia, Lyu, Chengzhe, Yao, Ziying and Liu, Mengxuan
year	2021
title	Study on the Differences of Day and Night Behavior in Urban Waterfront Public Space Based on Multi-agent Behavior Simulation
source	A. Globa, J. van Ameijde, A. Fingrut, N. Kim, T.T.S. Lo (eds.), PROJECTIONS - Proceedings of the 26th CAADRIA Conference - Volume 2, The Chinese University of Hong Kong and Online, Hong Kong, 29 March - 1 April 2021, pp. 559-568
doi	https://doi.org/10.52842/conf.caadria.2021.2.559
summary	In the twenty-four hour city era, how to optimize public spaces based on night behavior demands to promote full-time use has become a significant issue of urban design. Taking Shanghai North Bund as an example, the study collects data through site survey and questionnaire including environment elements, users attribute and behaviors. Next, the study sets up the simulation environment and translate the interaction of space and behavior into model language. Then, by setting up agent particles, running and fitting, the study obtains an ideal model. Finally, through sub-simulation and analysis, the study quantitatively explores the interaction mechanism between the physical environment and behavior from three levels of different spaces, different groups of people and different light conditions. The study finds that the differences of day and night behavior are produced under the combined effect of changes in attractiveness of environmental elements and changes in users demands and preferences. Compared with adults, the behaviors of elderly people and children show more obvious differences between day and night, and are more susceptible to space lighting, ground conditions and operating hours of facilities. Furthermore, the same kind of environment element will further affect users behavior in the night under different light conditions.
keywords	Self-Organization Behavior; Behavior Differences; Day and Night; Multi-Agent Behavior Simulation; Waterfront Public Space
series	CAADRIA
email
last changed	2022/06/07 07:57

_id	cf2013_233
id	cf2013_233
authors	Yang, Li and Dexuan Song
year	2013
title	The Research of Relationship between Architectural Space and Wind Environment in Residential Area
source	Global Design and Local Materialization[Proceedings of the 15th International Conference on Computer Aided Architectural Design Futures / ISBN 978-3-642-38973-3] Shanghai, China, July 3-5, 2013, pp. 233-244.
summary	In residential estate planning, several types of architectural combination space such as surround type, determinant, around the wrong column type and staggered type are commonly used. In this paper, the relationship between them and wind environment are simulated by CFD (Computational Fluid Dynamics) technology. The difference between two kinds of incident angle conditions are analyzed by landscape contrast, as well as the difference between construction plane combination by vertical contrast. General rules of architectural combination space and wind environment are summarized, and it is of significance in guiding the development of ecological energy-saving living environment.
keywords	Architectural space, Wind environment, Residential area
series	CAAD Futures
email
last changed	2014/03/24 07:08

_id	caadria2019_666
id	caadria2019_666
authors	Yang, Lijing, Cheng, Bingyu, Deng, Nachuan, Zhou, Zhi and Huang, Weixin
year	2019
title	The Influence of Supermarket Spatial Layout on Shopping Behavior and Product Sales - An application of the Ultra-wideband Indoor Positioning System
source	M. Haeusler, M. A. Schnabel, T. Fukuda (eds.), Intelligent & Informed - Proceedings of the 24th CAADRIA Conference - Volume 1, Victoria University of Wellington, Wellington, New Zealand, 15-18 April 2019, pp. 301-310
doi	https://doi.org/10.52842/conf.caadria.2019.1.301
summary	Companies and researchers had explored many methods to record people's shopping behavior, in order to explore a more favorable spatial layout. However, few research has been done from the architectural perspective using fine data. This research aims to set forth a clear relationship between the layout of the shelves and shopping behavior, as well as product sales, thus achieving a balance between customers shopping experience improvement and supermarket sales promotion. To achieve the goal, we designed experiments to track the shopping trajectory of many shoppers and set up questionnaires to get their personal and shopping information. Regarding the equipment for tracking the trajectory, we adopted the Ultra-Wideband indoor positioning system, which provides high positioning accuracy and stable performance. Based on the location data, we found spaces that appealed to shoppers and spaces where shoppers stayed longer. In addition, by comparing with the products they ultimately purchased, we found that buying behavior are highly related with the shoppers' movements in the supermarket. Based on the existing analysis, we assume that the spatial layout of the supermarket will affect people's impulse purchasing behavior. The UWB approach turns out to be feasible and can be applied to other supermarket behavior studies.
keywords	Shopping behavior; Ultra-Wideband; Supermarket layout; Trajectory; Quantitative Analysis
series	CAADRIA
email
last changed	2022/06/07 07:57

_id	acadia21_182
id	acadia21_182
authors	Yang, Qi; Cruz-Garza, Jesus G.; Kalantari, Saleh
year	2021
title	MindSculpt
source	ACADIA 2021: Realignments: Toward Critical Computation [Proceedings of the 41st Annual Conference of the Association of Computer Aided Design in Architecture (ACADIA) ISBN 979-8-986-08056-7]. Online and Global. 3-6 November 2021. edited by B. Bogosian, K. Dörfler, B. Farahi, J. Garcia del Castillo y López, J. Grant, V. Noel, S. Parascho, and J. Scott. 182-193.
doi	https://doi.org/10.52842/conf.acadia.2021.182
summary	MindSculpt enables users to generate a wide range of hybrid geometries in Grasshopper in real-time simply by thinking about those geometries. This design tool combines a non-invasive brain–computer interface (BCI) with the parametric design platform Grasshopper, creating an intuitive design workflow that shortens the latency between ideation and implementation compared to traditional computer-aided design tools based on mouse-and-keyboard paradigms. The project arises from transdisciplinary research between neuroscience and architecture, with the goal of building a cyber-human collaborative tool that is capable of leveraging the complex and fluid nature of thinking in the design process. MindSculpt applies a supervised machine-learning approach, based on the support vector machine model (SVM), to identify patterns of brain-waves that occur in EEG data when participants mentally rotate four different solid geometries. The researchers tested MindSculpt with participants who had no prior experience in design, and found that the tool was enjoyable to use and could contribute to design ideation and artistic endeavors.
series	ACADIA
type	paper
email
last changed	2023/10/22 12:06

_id	cf2003_m_059
id	cf2003_m_059
authors	YANG, Qizhen and CUI, Lu
year	2003
title	Interoperable and Extensible Design Information Modelling
source	Digital Design - Research and Practice [Proceedings of the 10th International Conference on Computer Aided Architectural Design Futures / ISBN 1-4020-1210-1] Tainan (Taiwan) 13–15 October 2003, pp. 93-104
summary	Modelling of interoperable and extensible design information is one of the key issues in computer-aided architectural design. IFC technology provides standardised mechanisms for the development of such information models. By using the IFC dynamic definition extension mechanism this paper presents a method for IFC-compliant design information modelling for architectural CAD objects. The method has been implemented as an addon toolkit to the Architectural Desktop CAD package. The use scenarios of the toolkit are discussed in the paper for CAD property modelling, property database management, and interoperable design information modelling with property set extensions.
keywords	IFC, information modelling, interoperability
series	CAAD Futures
last changed	2003/09/22 12:21

_id	caadria2024_80
id	caadria2024_80
authors	Yang, Runyu, Wang, Weili and Gui, Peng
year	2024
title	Predicting Pedestrian Trajectories in Architectural Spaces: A Graph Neural Network Approach
source	Nicole Gardner, Christiane M. Herr, Likai Wang, Hirano Toshiki, Sumbul Ahmad Khan (eds.), ACCELERATED DESIGN - Proceedings of the 29th CAADRIA Conference, Singapore, 20-26 April 2024, Volume 1, pp. 251–260
doi	https://doi.org/10.52842/conf.caadria.2024.1.251
summary	This paper introduces a graph neural network-based model for predicting pedestrian trajectories in architectural spaces. Compared to traditional simulations based on physics-based models, this data-driven model has a stronger ability to learn and predict pedestrian behaviour patterns from real-world data. The model is pre-trained based on Hongqiao Railway Station Dataset, then trained and tested based on the ETH Dataset and the Stanford Drone Dataset, enabling comparisons with other AI models. By creating a more intelligent model, we can establish a digital replica of the real world that can predict pedestrian flow with higher accuracy in daily life or extreme situations such as sudden fires. Our results underscore the critical role of such models in comprehending how architectural spaces are utilized, and thus in improving architectural design and urban planning.
keywords	multi-agent simulation, trajectory prediction, graph neural network, conditional variational autoencoder, path-finding
series	CAADRIA
email
last changed	2024/11/17 22:05

_id	sigradi2023_49
id	sigradi2023_49
authors	Yang, Ruyi, Shi, Hanyu, Yang, Zeyu and Sun, Zeyi
year	2023
title	Landscapes in Social Media: A Quantitative Analysis of Color Harmony in Historical Buildings
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. 149–160
summary	Historic buildings are vital repositories of local historical memory in urban environments. Color harmony, a key aspect of urban historical landscapes, lacks comprehensive quantitative standards and detailed research, notably concerning the evaluation of color harmony in historic contexts, encompassing monochromatic, analogous, and complementary hues. Integrating quantitative color indices and assessment techniques into historic preservation strategies necessitates further exploration. This study employs semantic segmentation algorithms, image property detection, and color pattern quantification to evaluate color harmony in historical buildings. Analyzing 100 viral Instagram images, dominant colors were extracted, categorized into 12 hue-based ranges, and assessed for harmonious combinations. Analogous and complementary schemes predominate, with 1–2 color harmonies and 2–4 color ranges recommended for optimal richness without visual clutter. Our findings offer a precise method, informed by popular social media images, to guide the conservation and restoration of historic landscapes with quantified color harmony guidelines.
keywords	Cultural Landscapes and New Technologies, Historical Landscape Renovation, Color Harmony, Color Scheme, Quantitative Analysis
series	SIGraDi
email
last changed	2024/03/08 14:06

_id	ijac202322203
id	ijac202322203
authors	Yang, Stephen; Jonathan Dortheimer, Aaron Sprecher and Qian Yang
year	2024
title	When design workshops meet chatbots: Meaningful participation at scale?
source	International Journal of Architectural Computing 2024, Vol. 22 - no. 2, 1-22
summary	This paper explores the potential of chatbots, powered by large language models, as a tool for fostering community participation in architectural and urban design. By taking a hybrid approach to community participation in a real-world mixed-use building project, in which we integrated remote chatbot engagements with face-to-face workshops, we explored the potential for a hybrid approach to scaling up the reach of participation while ensuring that such participation is meaningful, genuine, and empowering. Our findings suggest that a hybrid approach amplified the strengths and mitigated the shortcomings of the two methods. The chatbot was effective in sustaining the length of participation, broadening the reach of participation, and creating a personalized environment for introspection. Meanwhile, the face-to-face workshops still played a crucial role in bolstering community ties and trust. This research contributes to understanding chatbots’ strengths and weaknesses in participatory processes, both within spatial design and beyond. In addition, it informs future explorations of participatory processes that span different spatial-temporal configurations
keywords	Artificial intelligence, chatbot, community participation, large language models, natural language processing, participatory design
series	journal
last changed	2024/07/18 13:03

_id	caadria2008_12_session2a_103
id	caadria2008_12_session2a_103
authors	Yang, Wun-Bin Ji-Hyun Lee
year	2008
title	Building a Colour Image Database to Recommend Architectural Colour Scheme using Case-Based Retrieval Mechanism
source	CAADRIA 2008 [Proceedings of the 13th International Conference on Computer Aided Architectural Design Research in Asia] Chiang Mai (Thailand) 9-12 April 2008, pp. 103-109
doi	https://doi.org/10.52842/conf.caadria.2008.103
summary	The purpose of this study is to develop a digitized Taiwanese colour image database for architectural colour scheme in Taiwan. This paper uses adjectives to present each colour’s contribution to the colour image. The system uses the “colour difference formula” from the CIEDE2000 method, which calculates the difference between the two colour perceptions represented by the two given points. Using the “Group Nearest Neighbour” algorithm, the retrieval mechanism obtains a similarity measurement. This approach can help designers to know the meanings of colours and their associated colour images, which will help them develop the building image.
keywords	Colour Scheme; Colour Image; Nearest Neighbour; Case-Based Retrieval
series	CAADRIA
email
last changed	2022/06/07 07:57

_id	caadria2021_080
id	caadria2021_080
authors	Yang, Xuyou and Xu, Weishun
year	2021
title	A Tool for Searching Active Bending Bamboo Strips in Construction via Deep Learning
source	A. Globa, J. van Ameijde, A. Fingrut, N. Kim, T.T.S. Lo (eds.), PROJECTIONS - Proceedings of the 26th CAADRIA Conference - Volume 1, The Chinese University of Hong Kong and Online, Hong Kong, 29 March - 1 April 2021, pp. 463-472
doi	https://doi.org/10.52842/conf.caadria.2021.1.463
summary	As an alternative material for construction, the structural use of bamboo in architecture is commonly associated with active bending. However, as natural material, the deformation of unprocessed bamboo strips is affected by the distribution of nodes, whose impact on deformation is difficult to precisely programme for each individual case and thus often causes discrepancies between generic digital simulation and construction. This research proposes a tool for searching active bending bamboo strips via deep leaning based on a multi-task neural network. The tool is able to predict both the number and locations of nodes suggested on bamboo strips according to a target curve as tool input. By approximating the prediction, users can find a strip that is most likely to deform into the desired geometry.
keywords	neural network; active bending; neural architecture search (NAS); bamboo; material behaviour
series	CAADRIA
email
last changed	2022/06/07 07:57

_id	caadria2022_411
id	caadria2022_411
authors	Yang, Xuyou, Bao, Ding Wen, Yan, Xin and Zhao, Yucheng
year	2022
title	OptiGAN: Topological Optimization in Design Form-Finding With Conditional GANs
source	Jeroen van Ameijde, Nicole Gardner, Kyung Hoon Hyun, Dan Luo, Urvi Sheth (eds.), POST-CARBON - Proceedings of the 27th CAADRIA Conference, Sydney, 9-15 April 2022, pp. 121-130
doi	https://doi.org/10.52842/conf.caadria.2022.1.121
summary	With the rapid development of computers and technology in the 20th century, the topological optimisation (TO) method has spread worldwide in various fields. This novel structural optimisation approach has been applied in many disciplines, including architectural form-finding. Especially Bi-directional Evolutionary Structural Optimisation (BESO), which was proposed in the 1990s, is widely used by thousands of engineers and architects worldwide to design innovative and iconic buildings. To integrate topological optimisation with artificial intelligence (AI) algorithms and to leverage its power to improve the diversity and efficiency of the BESO topological optimisation method, this research explores a non-iterative approach to accelerate the topology optimisation process of structures in architectural form-finding via conditional generative adversarial networks (GANs), which is named as OptiGAN. Trained with topological optimisation results generated through Ameba software, OptiGAN is able to predict a wide range of optimised architectural and structural designs under defined conditions.
keywords	BESO (bi-directional evolutionary structural optimisation), Artificial Intelligence, Deep Learning, Topological Optimisation, Form-Finding, GAN (Generative Adversarial Networks), SDG 12, SDG 9
series	CAADRIA
email
last changed	2022/07/22 07:34

_id	caadria2005_b_5c_d
id	caadria2005_b_5c_d
authors	Yang-Ting Shen, Tay-Sheng Teng
year	2005
title	Personal Mobile Device for Situated Interaction
source	CAADRIA 2005 [Proceedings of the 10th International Conference on Computer Aided Architectural Design Research in Asia / ISBN 89-7141-648-3] New Delhi (India) 28-30 April 2005, vol. 2, pp. 382-387
doi	https://doi.org/10.52842/conf.caadria.2005.382
summary	The objective of the paper is to explore how the personal mobile devices help the user to interact with the space and get the personal service. We embed the RFID tag in PDA for the sake of identifying by the space. The space adapts itself to fit the user’s need by reading the data of the electronic tag. And the user uses PDA to interact with the space and record the interactive experience. We establish an interactive scenario between the user and the space to experiment how the system work.
series	CAADRIA
email
last changed	2022/06/07 07:57

_id	sigradi2023_246
id	sigradi2023_246
authors	YAO, Chaowen and Fricker, Pia
year	2023
title	Building Green Decarbonization for Urban Digital Twin – Estimating Carbon Sequestration of Urban Trees by Allometric Equations using Blend Types of Point Cloud
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. 91–102
summary	The achievement of climate neutrality is a fundamental goal for cities in the next 30 years. In order to achieve this goal, this research focuses on a novel tree carbon sequestration utilizing point clouds. Using a multi-algorithm workflow, tree information is extracted to calculate carbon storage from airborne and mobile laser scanning data, using Helsinki as a test case. The study employs local maximum and seeded region growing algorithms to detect tree locations and crown extents from aerial point clouds. A Python script is generated using the DBSCAN algorithm to extract tree point clouds and trunk diameters. The established allometric equations are utilized to calculate the carbon sequestration of trees. The results are integrated into the digital platform, filling the gap in urban digital twins' carbon storage information. This innovative approach will contribute significantly to urban planning and decision-making for sustainable cities in the face of climate challenges.
keywords	Urban tree, Carbon sequestration, Point cloud applications, Density-based clustering, Urban digital twin.
series	SIGraDi
email
last changed	2024/03/08 14:06

_id	ecaade2024_424
id	ecaade2024_424
authors	Yao, Chaowen; Fricker, Pia
year	2024
title	Neural Network-Driven 3D Generation of Urban Trees: Advancing carbon mitigation simulation through detailed tree modeling from point cloud data
source	Kontovourkis, O, Phocas, MC and Wurzer, G (eds.), Data-Driven Intelligence - Proceedings of the 42nd Conference on Education and Research in Computer Aided Architectural Design in Europe (eCAADe 2024), Nicosia, 11-13 September 2024, Volume 1, pp. 605–614
doi	https://doi.org/10.52842/conf.ecaade.2024.1.605
summary	Urban digital twins are essential for climate-responsive urban planning but often fail to accurately represent trees, relying instead on oversimplified models that inadequately capture their environmental impact. Traditional methods for tree modeling, notably skeletonization, are both iterative and labor-intensive, leading to inefficiencies in environmental simulation accuracy. Addressing this gap, our study introduces a novel approach using a Block Sparse Convolutional Neural Network (BSCNN) to generate precise 3D tree models from mobile laser-scanned point clouds, significantly enhancing simulations for carbon mitigation efforts. Our method, tested in Helsinki's Jätkäsaari area, leverages pre-defined skeleton data to train the neural network, streamlining the extraction of movement direction and distance, thus bypassing traditional skeletonization's iterative nature. We further refine our model's accuracy and robustness by incorporating point clouds of varying densities and tailoring our approach to account for the morphological diversity of specific tree species. This specificity enables our models to more closely mirror real-world trees, making them invaluable for dynamic environmental modeling within urban digital twins. Moreover, our models support integration with the L-system, a prominent plant growth simulation algorithm, showcasing the potential of advanced neural networks to revolutionize computational architecture and foster precise, sustainable urban environmental simulations.
keywords	3D Point Cloud Analysis, Block Sparse Convolutional Neural Networks (BSCNN), Tree Morphology and Morphological Diversity, Urban Digital Twin and Environmental Simulation
series	eCAADe
email
last changed	2024/11/17 22:05

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