‘Mushy Edges’ Spatial Selection Interface

Environments Data Capture

In the class Sensing Environments (51-377) taught by Mitch Sipus, we became familiar with and identified shortcomings in “Environment Mapping” software — both professional tools like QGIS and Fulcrum and consumer offerings like Google My Maps. Following this research period, we entered a short design sprint where we had to zone in on a particular shortcoming and design a solution.

Table of Contents

        1. Research
        2. Context
        3. Design
        4. Algorithmic Underpinnings


First, Most existing solutions connect data capture to specific points 📍 instead of ‘Spatial Regions.’
Fulcrum: Mobile environment data collection applicationFulcrum
Mobile environment data collection application

Second, when they do allow for denoting Spaces  🗺  –  doing so is frequently rigid, difficult, and unnatural.
Google 'My Maps' point-based spatial selection UI shown
point-based spatial selection UI shown
Photoshop Masking and feathering as a strategy for denoting a 'blurry' edge
Masking and feathering as a strategy for denoting a 'blurry' edge


My Research Question: Night-Time Illumination on Carnegie Mellon’s Campus: What spaces are illuminated? How brightly? Warm or cool light?

Capturing the edges is essential to defining the space and qualities of any environment


Algorithmic Underpinnings

“Metaballs are, in computer graphics, organic-looking n-dimensional objects” —Quote from Wikipedia

October 2018