Time: 4-20-2021

Course: SI659-Developing AR/VR Experiences, EAS750-Urban Design

Mentor: Michael Nebeling, Liwei Wu, Mark Lindquist

Device/Software/Code: iOS/Unity/C#

When it comes to decision support tool (DST) in terms of public engagement during the urban planning and design process, it is alway difficult to effectively visualize environmental experience and collect public environmental and social concerns. Therefore, the purpose of the this AR project is to provide a user-friendly DST interface for the better design engagement of residents

Time: 12-5-2021

Course: SI559-Intro to VR/AR

Mentor: Michael Nebeling

Device/Software/Code: iOS/Unity/C#

Trees live long, but not forever because there are many factors that can influence the forest ecosystem in a dynamic process. In terms of environmental education, AR can make the learning process more interesting and immersive. This project tries to prototype a marker-based AR card game based on the mobile device for young students to learn some ecological knowledge in terms of forest.

Time: 10-20-2021

Course: SI559-Intro to VR/AR

Mentor: Michael Nebeling

Device/Software/Code: iOS/Unity/C#

In urban and working environments, people usually get stressful, anxious, mentally exhausted due to frequent exposure to pressure, heavy workload, and traffic noise. These psychological issues can affect not only working efficacy but also long-term mental health. The therapeutic effects of natural experience have been being studied in many experiments for decades and many researchers indicate that multisensory experience in the natural environment has restorative potential to reduce pressure or attenuate negative emotions.

Time: 2-27-2020

Course: EAS501-Geovisualization 1

Mentor: Derek van Berkel

This study tried to find out the visiting hotspots in the Central Park and to figure out visitors' behavior over seasons and time. The study analyzed the visitor density patterns of time and seasons based on the distribution of the position where the photos were taken.

Time: 4-20-2020

Course: EAS501-Geovisualization 2

Mentor: Derek van Berkel

COVID-19 had become an international disaster that influences people's work and life. Many Twitter users shared thier feelings and thoughts about COVID-19 in tweets, which provides a different perspective to understand how this outbreak goes in people's mind and to visualize a map of people's subjective consciousness. This study focuses on analyzing how many times countries or regions in the world were mentioned by Twitter users in thier tweets about COVID-19 and analyzing the sentiment of these tweets. The name of country and region was used as statistical keyword. The sentiments dataset is a general-purpose lexicon bing from Bing Liu and collaborators.

Time: 12-13-2021

Course: Arch703-Virtual Engagement

Mentor: Glenn Wilcox

The inspiration is from the image/pixel-based stairs generated by neural networks, which was trained based on a dataset of over 2,000 stairs pictures. This project has tried to emulate the style and randomness of the generated stairs by coding to create a spatial reconstruction.

Time: 5-8-2019

Award: 2019 ASLA Student Awards | Honor Award of Analysis and Planning Category

Mentor: Chongxian Chen, Yu Xia

The study area is in Guangzhou, the Pearl River Delta, China, a region with a complex landscape system featuring agricultural production and wetland. The coastal disasters such as storm surge and seawater intrusion have always been a risk for most of the agricultural land, which is lower than the local mean sea level. Therefore, an adaptive agriculture model is needed to deal with the greater risk caused by sea level rise. Based on traditional reclamation agricultural model, our proposal is to integrate agriculture production with wetland transformation under sea level rise to create a successional salty agriculture landscape adapting to coastal environmental change and benefit agriculture, ecology and social culture for the next 100 years.

Time: 3-30-2019

Award: 2019 IFLA Asia-Pac Professional Award of Excellence

Team: Chongxian Chen, Xiaohao Yang, Yu Xia

Based on the PSR (Pressure-State-Response) model, this research project assessed the vulnerability of built Environment and natural Environment system of inundated areas in Guangzhou by depth status simulation and depth-damage functions. The research combines undamaged ratio under 2100 SLR and 200-year Storm surge scenario and adaptivity to identify environmental resilience weakness and classify evolution strategies priority for urban systems.

Time: 12-7-2022

Mentor: Lisa DuRussel

This project proposed a phasing strategy using the vacant land and urban agriculture to provide a solution to these problems and make a more sustainable and resilient development for future Detroit. The phasing strategy in this project is used to overlap more eco-functions, agricultural value, economic value, and public recreation in urban vacancy over time. The city landscape will be more resilient to higher temperatures and more frequent heavy precipitation event. The residents will have more access to healthy public space and more employment opportunities. Overlapped tree farm on vacancy as a preparation for urban revitalization, takes the advantage of the value of vacancy that was used to be wasted.