LocalSpace: Predicting Heliport's Impact
Urban Data Visualization Tool UX & UI Design
Yuheng Zhu, Adam Schreiber (ORIE), Idan Bar-Dov (MBA), Saloni Gandlhi (CS), Chutian Tai (CS)
When at Cornell AAP NYC, Yuheng joined an interdisciplinary design team at the Cornell Tech Product Studio as an urban designer. The team worked with an advisor from Uber Elevate, who challenged the team with a line of inquiry: How might we better integrate the transit facilities for Urban Air Mobility vehicles into local communities? After intensive research, user interviews, and programming, the team designed the LocalSpace, a solution prototype. This product won the team an opportunity to showcase it at the Cornell Tech Open Studio 2019.
LocalSpace is a comprehensive tool that models and visualizes the impact prospective construction of heliports will have on local communities. It estimates the externalities of developing the project and generates a heat map that presents local impact in terms of noise, mobility, and retail activity.
User Research & Industry Research
The project started with user and industry research, in order to picture the complex system and stakeholders. This rich picture was derived from interviews with industry specialists and targeted neighborhood residents. Then, the team decided on the design objective through Value Creation Analysis.
Problem & Solution
Miscommunication between local communities and real-estate developers intercepts the advancement of projects and communities.
Therefore, we proposed LocalSpace, a platform that (1) models and visualizes the various impacts of potential heliports in an intuitive way and (2) facilitates an informed dialogue between developers and external stakeholders.
Uber Elevate Advisor
To determine the relevant factors, we communicate with the industry advisor of the team and together strive to design the prototype as a real-world solution.
Prototype UI Design
Black box of heliport’s impact
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Insight #1: Not All Noise is Created Equal
Noise is of the utmost concern to local communities.
However, the bothersome quality of each added decibel to a system is inversely proportional to the existing noise level.
LocalSpace targets regions with high existing ambient noise levels that have sufficient leeway for additional noise load.
Visualization of analysis result
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Insight #2: Humans are Complicated
Initial idea was to develop a formula that represents the “net“ impact of a proposed project using importance weightings for each impact factor.
Through our experimentation, it becomes clear that a mathematical relationship of weighted factors cannot accurately represent human sentiment in this case.
LocalSpace, therefore, models impact data for each factor individually.