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Academic project / 03 · Denver, Colorado

RTD bus routes.
A pandemic perspective.

Socioeconomic Effects of COVID-19 on RTD Bus Routes

An interactive geovisualization exploring how changing bus service intersected with the socioeconomic geography of Denver during COVID-19.

LeafletD3.jsSpatiotemporal visualizationSocioeconomic analysis
My contribution
Collaborative GIS & web visualization
Project collaborator
Jeremy McKowski
Study area
Denver · RTD bus routes
Context
College project during COVID-19
The project

How did service change,
and for whom?

Jeremy McKowski and I developed this project in college during the pandemic. We used Leaflet and D3.js to connect a geographic view of Denver’s bus service with socioeconomic information at the census tract level.

By linking daily bus stop frequency and census tract information, the geovisualization lets users explore changes across both space and time. It was designed to help users and planners identify patterns and select areas for more detailed investigation.

Map objectives

Link the data.
Explore the relationships.

Geographic context, temporal change, and socioeconomic filters in one exploratory workflow.

01

Identify spatial & temporal patterns

Explore bus stop frequency changes throughout the pandemic and compare them with socioeconomic variables, individually or together.

02

Find areas for a closer look

Identify census tracts and stop rates that may warrant further analysis or additional measures to improve service.

03

Filter by the question

Narrow the data to relationships such as median income by tract, or unemployment over time alongside stop frequency.

The spatial connection

Bus stop frequency + census tract attributes + time

Leaflet provided the map interface; D3.js supported the linked data visualizations.
Project demonstration

See the geovisualization
in action.

Watch on YouTube ↗

Project demo · McClain Martensen & Jeremy McKowski. Playback begins at 0:02. If the embedded player is unavailable, use Watch on YouTube.

The value of the work

A starting point
for better questions.

Bringing service frequency and socioeconomic context together makes it easier to spot patterns that a single map layer might miss. The project’s goal was to support a first look at where additional analysis could help guide more responsive transit service.

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