Homework 1, Section B
Team:
Chengqi Tian (ct2766)
Simon Li (ll3228)
Xuantong Zhang (xz2744)
Zhengzhe Jia (zj2244)
Conference:
The Society for Modeling & Simulation International: Symposium on Simulation for Architecture and Urban Design (SimAUD) conference
Paper Submission Requirements:
Areas of Interest:
SimAUD Topics but not Limited to:
- Simulation-based Generative Design
- Simulation-Based Collaborative Design
- Simulation-Based Design Tools and Methods
- Multidisciplinary Design Optimization
- Simulation Performance and Scalability
- Building Comfort & Energy Performance
- Simulation of Occupant Behavior
- Simulation of Building Controls
- Physics-Based Simulation in Design
- Whole Building Energy Simulation
- Thermal Comfort & Occupant Satisfaction
- Lighting and Daylighting
- Airflow In & Around Buildings
- Acoustics Modeling, Simulation & Design
- Visualization of Simulation Data
- Urban-Scale Modeling
- Uncertainty, Validation and Risk Management
- Augmented and Virtual Reality
- Design Agency & Multi-Agent Systems
- Intelligent Buildings & Building Lifecycle Management
- Sensor Networks & Building Performance Monitoring
- Interactive Environments
- Responsive Facades
- Robotic Fabrication in Design
Submission Types:
- Full Papers
Full papers (max. 8 pages) present significant contributions to research and practice in the SimAUD areas. Accepted full papers will be archived at the ACM Digital Library. Links to SimAUD papers in the Digital Library are posted at www.simaud.org/papers.php.Short papers are non-archived publications (max. 4 pages) that present brief and focused research contributions that are noteworthy but may not merit a full paper. Typically short papers provide an overview of research-in-progress and/or thought-provoking work relevant to the SimAUD community. They have not reached completion level necessary for jury review and acceptance as complete papers; however, authors will benefit from in-person feedback from symposium attendees.
2. Short Papers
Short papers should include:
- A focused description, and if appropriate, analysis of the work
- Potential impact of the work to the SimAUD community
- Recommendations for future research and application in practice
Please adhere to the 4-page limit. Paper templates will be uploaded shortly.
Please adhere to the 8-page limit. Paper templates will be uploaded shortly.
3. Invited Papers
In order to help bring together diverse disciplines we aim to establish a common language of perspectives, case studies, techniques or technologies. One way to start this process is through invited works. The Committee may internally evaluate and invite certain papers, projects, or videos to include in the symposium outside the formal peer-review process. To nominate research that you believe would be beneficial to building this new community, please email any of the chairs with suggestions.
4. Project & Videos
Many architecture and urban design projects communicate visions of a proposed future. Projects and videos are among the best ways to communicate these visions. We invite project and video submissions of high-quality scientific visualizations of architecture or urban design projects, interactive design decision support systems, compelling animations of construction simulation, and more. We strongly encourage authors of full and short paper submissions to also provide a high-quality video for peer-review and exhibition at the SimAUD symposium.
A project submission is a poster that summarizes a professional or student design project that utilizes simulation as a means for informing design decisions, in an effort to demonstrate innovation and excellence in architecture and urban design. All projects should be submitted on boards that adhere to an A1 page size, portrait or landscape orientation, with no other specific limitations and not necessarily tied to a paper submission.
All papers that were accepted as posters should be submitted following the same format as the project posters.
Accepted projects and videos will be featured in a poster session during the conference, and will be featured on SimAUD’s website. If you plan to provide a video or project, please notify the General Chair by email prior to the submission deadline.
Paper Outline:
Introduction
In this project, we are finding a neighbourhood in NYC, and, based on this neighbourhood, building a simulator that can be used to predict real property prices based on the availability of public amenities such as parks, hospitals, schools, and public transportation infrastructures. The program will allow users to build new infrastructures, eliminate or alter the function of existing ones. And the program will predict the change in property value as a result of the alteration.
Overall, the program will allow urban planners, developers, real estate investors, and policymakers to make better decisions and answer the questions: Will the different changes in land uses increase or decrease the overall housing price in one neighbourhood? What characteristics of a neighbourhood or a city make it better to invest?
Mythodology
In order to build the program, we have to determine how the value of properties in this community fluctuate as a function of a variety of factors such as availability of certain amenities, and transportation facilities. To accomplish this, several of our group members will be responsible for researching and establishing a mathematical model. After establishing the model, we will focus on creating the environment and agents by visualizing the neighbourhood, the buildings, and the amenities with graphics and pictures. Next, we will be focusing on the behaviours and parameters by adding interactive features to our program. The inputs and outputs of our program will be dictated by the mathematical model we found above.
Research
- Constructing the mathematical model
We selected 20 house price data from the last month of the crown heights as a sample, searching for real estate price data of crown heights on Streeteasy. Because the sample size was relatively small, in order to ensure the accuracy of the model, we artificially removed some values that differed greatly from the average housing price. After the sample was obtained, we processed the sample. First, we calculated the average value of the sample. The average value was 970. By observation, we selected each $50 as an interval and assigned the sample. After processing the completed housing price sample, we selected the parks, hospitals, and transportation facilities within the community as variables for this study. Through calculations, the distance between parks, hospitals, and transportation facilities to each real estate project was obtained. Re-assign every 0.4 miles as an interval. The distance scores of each real estate in parks, hospitals, and transportation facilities were obtained.
Next step, we imported the processed data into SPSS. With the simulation, we found that the multiple linear regression model has the greatest significance. So the model was obtained by multiple linear regression. The R square of the model passes the test, so the model is valid.
Model
Y=-0.83X1+0.375X2+0.105X3–6.359
Y= housing price
X1= distance from the hospital
X2= distance from transit
X3= distance from park
Analysis
As we come up with different scenarios and situations, we can find the scenarios in which the property values can be maximized. We could also add more factors as we take crime rate, median household income into consideration.
Learnings and Conclusion
The model can be used to develop the optimized plan for maximizing property values in an area or neighborhood. In our example, the Crown Heights’ property value are maximized when we build 2 more hospitals and 4 more subway stations. The resulting increase in property value is 164 million dollars. (more conclusions can be drawn after we conduct our research).
Future Implications
The simulation can help to answer the questions we proposed. Specifically, we are trying to find out how changes in land use affect the overall housing price in a neighborhood. The simulation will benefit different parties including urban planners, policy makers, investors, and developers.
1. For urban planners and policymakers
First of all, the simulation can help urban planners analyze a variety of issues and social implications involved in the construction of amenities and transportation facilities, such as the displacement of lower income tenants and landlords, fluctuation in crime rate, and segregation in terms of income and race. With this simulation in place, urban planners can gain a deeper understanding of these changes when they are making decisions regarding whether and where to build new amenities.
Secondly, the change in property values also implies the change in property taxes collected. This will be important for policy makers and planners. As they are making decisions regarding the construction of a new metro station or a new public amenity, they can consider whether the future increase in property tax revenue can compensate for the construction costs of the new station or the park. If so, how many years does it take to compensate for the costs. Although the benefits of urban amenities are much more than just the increase in tax revenue, the policy makers can at least get some sense of the financial implications and validity of constructing new urban amenities and transportation facilities.
2. For investors and developers
A growing body of research indicates that people tend to pay more to to have access to urban amenities. Amenities such as parks, hospitals, and transit are amenities that make for a rich urban experience. And a package of urban amenities can increase desirability and competition for real estate in an area, and this will in turn increase the rent that property owners can achieve. Higher achievable rents can allow developers to consider larger scale, higher quality real estate projects. The increased investment activities will result in an upward cycle of even more desirability and investment. Therefore, it is important for real estate developers to consider how public and private investment can change the desirability of an area and the best location and number of amenities to add to a neighbourhood to maximize its property values.
