Menu

EAS 523: Interactive Visualisation of the Built Environment

 

Course Title

Interactive Visualisation of the Built Environment

Course Code

EAS 523

Course Type

Elective

Level

PhD

Instructor’s Name

Asst. Prof. George Artopoulos (Lead Instructor), Prof. Salvatore Carlucci

ECTS

5

Lectures / week

1 (1 hour)

Laboratories / week

1 (2 hour)

Course Purpose and Objectives

Purpose: The course will introduce students to thevisualization of complex phenomena, such as the impact of natural and artificial agents to the built environment, in order to understand how the performance of the latter is the result of its integration in an emergent system of parameters. The purpose of the course is to provide students insights to computer interactive visualisation and simulation of complex systems as a means to better understanding built environment’s past and present conditions, as well as to speculate about possible transformations for sustainable futures by means of data and information collected in the real world. Students will thus be able to better contextualize built environment as part of a larger, more complex (eco)system of interacting parameters. Data visualization is an
essential component of planning a smart city, and researchers currently seek new methods for conducting real-time simulations. The impact analysis of “what-if scenarios” becomes ever more useful and relevant for the management of the built environment but it requires a significant amount of time and resources, and virtual reality (VR) can be used as a tool for addressing these challenges. Advanced methodologies will be illustrated by the research and innovation thrusts currently pursued within the EEWRC (Energy, Environment and Water Research Centre, Built Environment) and The Cyprus Institute Virtual Environments Lab. They will cover: (i) visualising complex phenomena in the built environment, (ii) experimental tools for modelling and interacting with built environment data, (iii) constructing Virtual
Reality simulations of built environment data, (iv) analysing spatial data, (v) Advanced concepts of immersion in data for interpreting the complex performance of built environment.

Objectives:
The course will include introductions into techniques of independentObjectives: The course will include introductions into techniques of independentscientific investigations from the planning to the publication and disseminationstage. It will also provide opportunities for the students to get actively engagedthrough presentations and reviews of literature provided throughout the course.Specifically, the objectives of the course include:•to provide a framework for the integration and classification of state of the arton interactive data visualisation for the study of the built environment;•to reveal areas of research in the field of sustainable built environment;•to summarize issues and challenges related to interactive data visualisation forthe study of the built environment, and suggest how these can be pursued;•to forecast future research and development thrusts in this area.

Learning Outcomes

Students will familiarize themselves with simulation and analysis tools, dataStudents will familiarize themselves with simulation and analysis tools, datavisualization methods, literature and computational resources in order to engage ininterdisciplinary activities, including interactive visualizations for the analysis andinterpretation of the complex data of the performance of built environment withinits natural environment. The multi-disciplinary dimension of the course will enrichthe scientific background of the students while offering them a betterunderstanding of research and innovation thrusts of key vertical and horizontalpriorities of the Cyprus Smart Specialization Strategy (i.e. Environment, Energy, BuiltEnvironment). Specifically, students will be able to:

- Comprehend the main components of an interactive data visualization.
- Represent the built environment that will stage the simulation.
- Identify conflicting parameters and shortcomings in the visualization process.
- Understand complex systems in built environment and their interactionmechanisms.
- Develop a computational visualization model (or a simplified prototype of it)and deal with the relevant technological interfaces and tools,
- Be familiar and critical with the theoretical background, relevant practices,tools and methodologies of complexity theory and emergence in the context of the built environment research

Prerequisites

EAS 500, EAS 518

Background Requirements

None

Course Content

1: Introduction to modeling and visualization
1.1. Why to model a complex phenomenon in the built environment?
1.2. Modeling for interactive data visualization
1.3. Visualizing human-environment interaction
1.4. Virtual reality-based modeling and visualization
 
2: Spatial Computing Interfaces
2.1. Fundamentals of spatial computing
2.2. Desktop screen-based computing
2.3. Mobile computing
2.4. Pervasive computing
 
3: Interactive data visualization in Planning and Design
3.1. Exploring built environment problems through interactive visualization
3.2. Geographical environment and the parameter space
3.3. Advances of interactive data visualization in planning and design
3.4. Limitations of interactive data visualization
 
4: Physical modeling of the built environment (Part 1)
4.1. Problem statement
4.2. Building-environment interaction phenomena
4.3. Governing equations and assumptions
4.4. Modeling approaches and tools
 
5: Physical modeling of the built environment (Part 2)
5.1. Physical characterization of urban surfaces
5.2. Anthropogenic heat and urban heat island
5.3. Outdoor thermal comfort and human health
5.4. Energy use and mobility
 
6: Spatial modelling
6.1. Introduction to Complexity
6.2. Modelling built environment and Settlement dynamics
6.3. Sets of parameters to be represented in spatial modelling
6.4. Setting up dynamic interactions in spatial modelling
 
7: Presence: Immersion and virtual environments
7.1. Theory of immersion, basics of cognitive processes
7.2. Setting up immersive simulations for data exploration
7.3. Data interpretation through immersive visualization
7.4. Applications
 
8: Machine Learning for Data Analysis and visualization
8.1. Introduction to supervised learning
8.2. Introduction to unsupervised learning
8.3. Implementation and applications in predictive modelling
8.4. Implementation and applications in representation learning and clustering
 
9: Theoretical considerations
9.1. Complexity theory
9.2. Cities as open ended systems
9.3. Computational practices in studying human-built environment interactions
9.4. Applications
 
10: Virtual Reality: Visualization of simulated data I
10.1. Information design and interaction design
10.2. 2D mapping
10.3. 3D representation
10.4. Integrating agent-, intelligence- and knowledge-based problems of the built environment
 
11: Virtual Reality: Visualization of simulated data II
11.1. Use of VR for immersion in the simulated environment
11.2. VR implementation (including hardware display, input, computing and trackers, and software)
11.3. VR tools
11.4. Limitations of technological interfaces
 
12: Virtual Reality: Visualization of simulated data III
12.1. Simulating materiality and environmental conditions
12.2. A VR workflow
12.3. VR Applications (single user VR vs. collaborative systems)
12.4. Shortcomings and good practices

Teaching Methodology

Lectures, seminars, tutorials.

Bibliography

1. Batty, M. 2007. Cities and complexity: understanding cities with cellular automata, agent- based models, and fractals. MIT Press.

2. Batty, M., Axhausen, K.W., Giannotti, F., Pozdnoukhov, A., Bazzani, A., Wachowicz, M., Portugali, Y. Smart cities of the future. Eur. Phys. J. Spec. Top. 2012, 214, 481–518.

3. Bibri, S.E., Krogstie, J. Smart sustainable cities of the future: An extensive interdisciplinary literature review. Sustain. Cities Soc. 2017, 31, 183–212.
 
4. Braem, B., Latre, S., Leroux, P., Demeester, P., Coenen, T., Ballon, P. Designing a smart city playground: Real-time air quality measurements and visualization in the City of Things testbed. In Proceedings of the IEEE International Smart Cities Conference (ISC2), Trento, Italy, 12–15 September 2016; pp. 1–2.
 
5. De Laat, R., & Van Berlo, L. Integration of BIM and GIS: The development of the CityGML GeoBIM extension. Kolbe, T. H.; König, G.; Nagel, C. (Eds.) 2011: Advances in 3D Geo-Information Sciences, ISBN 978-3-642-12669-7
 
6. Haq, S. Investigating the syntax line: Configurational properties and cognitive correlates. Environ. Plan. B Plan. Des. 2003, 30, 841–863.
 
7. Horne, M. and E.M. Thompson. The Role of Virtual Reality in Built Environment Education. Journal for Education in the Built Environment, 3:1,
5-24, DOI: 10.11120/jebe.2008.03010005
 
8. Kramers, A., Höjer, M., Lövehagen, N., Wangel, J. Smart sustainable cities–Exploring ICT solutions for reduced energy use in cities. Environ. Model. Softw. 2014, 56, 52–62.
 
9.  Kim, Y.O., Penn, A. Linking the spatial syntax of cognitive maps to the spatial syntax of the environment. Environ. ehav. 2004, 36, 483–504.
 
10. Niu S Y.Pan W and Zhao Y S. A virtual reality integrated design approach to improving occupancy information integrity for closing the building energy performance gap. Sustainable Cities and Society, 27: 275-286, 2016.
 
11.  Smith, A., M. Dodge, and S. Doyle, Visual Communication in Urban Planning and Urban Design; Centre for Advanced Spatial Analysis (CASA): London, UK, 1998.
 
12. Sun, Q., Wan, W., Yu, X. The simulation of building escape system based on Unity3D. In Proceedings of the IEEE International Conference on Audio, Language and Image Processing (ICALIP), Shanghai, China, 11–12 July 2016; pp. 156–160.
 
13. Van de Voorde, T., Jacquet, W., Canters, F. Mapping form and function in urban areas: An approach based on urban metrics and continuous impervious surface data. Landsc. Urban Plan. 2011, 102, 143–155.
 
14. Villanueva, F.J., Aguirre, C., Villa, D., Santofimia, M.J., López, J.C. Smart City data stream visualization using Glyphs. In Proceedings of the IEEE Eighth International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing (IMIS), Birmingham, UK, 2–4 July 2014; pp. 399–403.
 
15. Unity. Unity game Engine, from https://unity3d.com/
 
16. Zudilova-Seinstra, E, Adriaansen, T, & van Liere, R. (2009). Trends in Interactive Visualization: State-of-the-Art Survey (Advanced Information and Knowledge Processing). London: Springer-Verlag.
 
17. Santamouris M. Minimizing Energy Consumption, Energy Poverty and Global and Local Climate Change in the Built Environment: Innovatingto Zero- Causalities and Impacts in a Zero Concept World. Elsevier, 2019.

Assessment

Coursework, essays, presentations.

Language

English