Urban Data Visualization
LocalSpace: Predicting Heliport's Impact / Fall 2019
Type/
Collaborative Data Visualization Tool Design
Members/
Yuheng Zhu, Adam Schreiber (ORIE), Idan Bar-Dov (MBA), Saloni Gandlhi (CS), Chutian Tai (CS)
Personal contribution includes user research, communication with company advisor, Value Creation Analysis, front-end prototype design, presentation at the Cornell Tech Open Studio as the main designer.
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.

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 this solution prototype. This product won the team an opportunity to showcase it at the Cornell Tech Open Studio, Fall 2019.
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
Problem
Miscommunication between local communities and real-estate developers intercepts the advancement of projects and communities.

Developer
Black box of heliport’s impact
Community
Solution
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.

Data
Insight
Communication
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 UX Design




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Expanded view



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Visualization of analysis result
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Insight #1: Not All Noise is Created Equal
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Noise is of the utmost concern to local communities.
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However, the bothersome quality of each added decibel to a system is inversely proportional to the existing noise level.
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LocalSpace targets regions with high existing ambient noise levels that have sufficient leeway for additional noise load.
Insight #2: Humans are Complicated
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Initial idea was to develop a formula that represents the “net“ impact of a proposed project using importance weightings for each impact factor.
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Through our experimentation, it becomes clear that a mathematical relationship of weighted factors cannot accurately represent human sentiment in this case.
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LocalSpace, therefore, models impact data for each factor individually.