Identify spatial & temporal patterns
Explore bus stop frequency changes throughout the pandemic and compare them with socioeconomic variables, individually or together.
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.
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.
Geographic context, temporal change, and socioeconomic filters in one exploratory workflow.
Explore bus stop frequency changes throughout the pandemic and compare them with socioeconomic variables, individually or together.
Identify census tracts and stop rates that may warrant further analysis or additional measures to improve service.
Narrow the data to relationships such as median income by tract, or unemployment over time alongside stop frequency.
Bus stop frequency + census tract attributes + time
Leaflet provided the map interface; D3.js supported the linked data visualizations.Project demo · McClain Martensen & Jeremy McKowski. Playback begins at 0:02. If the embedded player is unavailable, use Watch on YouTube.
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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