publications

2024

1. Journal

   ArchIndex: 基于多源数据的城市街区检索引擎

   Mo, Yichen, Ludger, HOVESTADT, Li, Biao, and Tang, Peng

   新建筑, 2024(1):15-21

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   城市街区检索引擎是一种城市认知智能，通过整合和呈现多源城市数据，建立城市空间检索模型，从而简化城市设计前期的认知和调研。文章通过动态网页提供城市街区检索引擎ArchIndex，在可定期更新的空间关系数据库的基础上，采集街区实例数据，建立形态、功能、活力三个方面的向量化指标，用于城市街区的检索与可视化。最终方案实现了分布式运行部署，可对任意城市建立索引，用云端计算与网页应用，为城市形态学研究提供了易用的工具和新的方法。

   @article{MoArchIndex2024,
     abbr = {Journal},
     selected = {true},
     bibtex_show = {true},
     title = {ArchIndex: 基于多源数据的城市街区检索引擎},
     author = {Mo, Yichen and Ludger, HOVESTADT and Li, Biao and Tang, Peng},
     year = {2024},
     journal = {新建筑},
     volume = {1},
     number = {15-21},
     pdf = {archindex-na.pdf}
   }

2023

1. Journal

   Case-Based Reasoning Strategy for Urban Morphological Generative Design: A Case Study of Block Scale

   Zhang, Baizhou,  Mo, Yichen, and Li, Biao

   South Architecture, 2023(01):09-18

   Bib PDF

   @article{zhangMorphological2023,
     abbr = {Journal},
     selected = {true},
     bibtex_show = {true},
     author = {Zhang, Baizhou and Mo, Yichen and Li, Biao},
     journal = {South Architecture},
     number = {09-18},
     title = {Case-Based Reasoning Strategy for Urban Morphological Generative Design: A Case Study of Block Scale},
     volume = {01},
     year = {2023},
     pdf = {morphological.pdf}
   }

2022

1. CDAC 2022

   Research on Light Weight JSON based Exchange Format for Architectural Design

   Mo, Yichen, and Li, Biao

   In Proceedings of 2022 Computational Design Symposium and the Annual Conference of Computational Design Academic Committee of Architectural Society of China, 2022

   Abs Website

   ArchiJSON is a light weight web data exchange format for architectural design. It mainly work with ArchiWeb, which is an open source web-based 3D editor for exhibiting computational design.

2. Journal

   Automatic Generation of High-rise Residential Facades from the Perspective of Building Industrialisation

   Wu, Jiaqian, Li, Biao, and Mo, Yichen

   South Architecture, 2022(04):25-31

   Bib PDF

   @article{wuResidentialFacades2022,
     abbr = {Journal},
     selected = {true},
     bibtex_show = {true},
     author = {Wu, Jiaqian and Li, Biao and Mo, Yichen},
     journal = {South Architecture},
     number = {25-31},
     title = {Automatic Generation of High-rise Residential Facades from the Perspective of Building Industrialisation},
     volume = {04},
     year = {2022},
     pdf = {residential-facades.pdf}
   }

3. CAADRIA 2021

   A Web-Based Interactive Tool for Urban Fabric Generation

   In POST-CARBON - Proceedings of the 27th CAADRIA Conference - Volume 1, Sydney, Australia, 9-15 April, pages 625–634, , 2022

   PDF

2021

1. CDAC 2021

   A B/S Framework for Generative Design System —— Case Study of Art and Media

   Mo, Yichen, Li, Biao, and Gu, Daqing

   In Proceedings of 2021 Computational Design Symposium and the Annual Conference of Computational Design Academic Committee of Architectural Society of China, 2021

   Abs Website

   参数形式生成是东南大学建筑学院二年级“艺术与媒介”中的四周课程，课程周期短，参与人数多。要保证线上教学质量，课程需要即开即用的网页应用，由简单到复杂、循序渐进地为学生提供空间练习。为此开发基于 B/S 架构的生成设计系统，用于引导学生形成基本空间认知，探索空间结构形成的客观规律。 该系统以点、线、面为基本空间操作要素，以空间剖分为基础，将空间组织的方法、形式生成的规则转译为函数接口，把影响空间关系的参数、类型等设计为用户交互界面。 操作使用 用户可操作参数对抽象构成进行一定程度仿写，通过这样的练习理解数值和策略对空间效果的意义；也可以对不同构成生成式地产生连续、有节奏的变化序列，借助参数化的解析与再创作实现对设计构成深层次的认知。 系统原型　基于空间类型学这一描述性的设计理论，本研究开发的生成设计系统是自动化设计系统的原型，其分布式的交互架构亦呈现了参数化建筑设计应用的一种可能性。这种智能设计系统可依据用户输入信息推导设计结果，通过参数调整设计细节，并能最终转化为更详细的设计实体。 应用架构　整个生成设计系统采用B/S架构，网页端使用声明式的定义方式，设置灵活的调整参数和可选形状要素等，实时渲染参数调整的结果；服务端对输入参数应用空间组织策略，建立了计算机的思维；连接两者的是一种互操作性的几何描述协议，相当于程序之间交流的语言。 这里介绍的框架将原来无法言说的设计经验，转变为了可量化、可描述、可操作的生成设计系统，并投入于实际教学使用。通过参数调整进行空间形式训练，学生能直观、高效地掌握空间操作与生成的方法，为进阶的建筑学习打下基础。

2. CUPUM 2021

   ArchIndex : A Web-based and Data-driven Retrieval System for City Blocks

   Mo, Yichen, Zhang, Baizhou, and Li, Biao

   In Proceedings of the 17th International Conference on Computational Urban Planning and Urban Management (CUPUM),, 2021

   PDF Website
3. CAADRIA 2021

   Archibase: A City-Scale Spatial Database for Architectural Research

   Mo, Yichen, Li, Biao, Wu, Jiaqian, and Tang, Peng

   In PROJECTIONS - Proceedings of the 26th CAADRIA Conference - Volume 2, Hong Kong, 29 March - 1 April 2021, pages 519–528, 2021(2)

   Abs Bib PDF Video

   The explosion of geolocation data and data-based algorithms has the potential to analyze sophisticated urban areas and foster a more robust urban model. To better collect and organize the city data, this paper introduces a city-scale spatial database called ArchiBase, built upon Java and web APIs of open source databases. With hierarchical, layered, and regularly-updated spatial data defined by relation table, ArchiBase allows indexing and geometric searching of the entire city and supports applications and extensions for different cities. This research is from a graduate urban design course aiming to renew Prato, an industrial city in Italy. ArchiBase first creates the base version of Prato from multiple data sources, then illustrates the usability and expandability through three simple applications. The use of ArchiBase can better interpret future cities and demonstrate the unparalleled opportunities of collaboration and remote work for urban researchers and designers.

   @inproceedings{moArchiBase2021,
     abbr = {CAADRIA 2021},
     selected = {true},
     bibtex_show = {true},
     title = {Archibase: {{A City-Scale Spatial Database}} for {{Architectural Research}}},
     author = {Mo, Yichen and Li, Biao and Wu, Jiaqian and Tang, Peng},
     booktitle = {PROJECTIONS - Proceedings of the 26th <strong>CAADRIA</strong> Conference - Volume 2, Hong Kong, 29 March - 1 April 2021, pages 519–528},
     volume = {2},
     pages = {519-528},
     year = {2021},
     pdf = {archibase.pdf},
     video = {https://caadria2021.org/session-2C#135}
   }

2020

1. CDAC 2020

   Data-driven Analysis Approach on Urban Subjective Map: Taking Street View Perception Analysis as an Example

   Wu, Jiaqian, Li, Biao, and Mo, Yichen

   In Proceedings of 2020 International Academic Forum on Computational Design and Annual Conference of Computational Design Academic Committee of Architectural Society of China, pages 256-267,, 2020
2. DADA 2020

   Implementing Urban Spatial Database——Case Study of Prato,Italy.

   Mo, Yichen, and Li, Biao

   In Proceedings of 2020 National Conference on Architecture’s Digital Technologies in Education Research, pages 183-189,, 2020

   Abs PDF

   The application of big data requires an abstract representation of the city, which is the most fundamental part of the digital approach. Urban design applications of digital technologies often use map data as a data source, which is lack of disciplinary relevance. Based on collaboration, design process requires the development of appropriate design tools to use varieties of urban data. In this paper, we propose a spatial database based on multiple data sources, with the whole city as the research subject, providing a data base and digital tools for design analysis. Our method integrates PostGIS applications which fully support the OGC standard, aggregates and organizes data from multiple sources, which is meaningful to architecture. This digital tool is automated regularly synchronize with online data source, adapting to the dynamic and updated nature of the city. Deployed on a server, it also resolves the conflicts in urban design when multiple users operate the same data. Finally, this paper establishes the Prato Urban Spatial Database, using digital technology for pre-analysis. The results show that the database can be used for Urban numerical models provide a rational abstract representation while establishing a scientifically sound analytical paradigm for data-driven design methods.

3. Research on Evaluation and Renewal Strategy of Urban Public Space in the Context of Crowdsourcing Data——A Case Study of Prato,Italy

   Zhao, Wenrui, Li, Biao, Wu, Jiaqian, and Mo, Yichen

   In Proceedings of 2020 National Conference on Architecture’s Digital Technologies in Education Research, pages 177-182,, 2020

   PDF