Working with GeoJSON Route Data

What is GeoJSON?

GeoJSON is an open standard format for encoding geographic features — points, lines, and polygons — as JSON. It's supported by virtually every mapping and GIS tool available today, from browser-based visualizers to enterprise platforms like ArcGIS. When you click Export GeoJSON on a TIPS report, you get a .geojson file containing every route a Traveler drew, represented as LineString features with their raw waypoint coordinates.

What's in the export?

Each exported file is a GeoJSON FeatureCollection. Every Traveler-drawn route is one Feature with:

• geometry — a LineString with the waypoint coordinates (longitude, latitude pairs) exactly as the Traveler placed them on the map.
• properties.responseId — the survey response this route belongs to, so you can correlate routes with other answers in the CSV export.
• properties.name — the name the Traveler gave the route (if any).
• properties.position — the order in which the Traveler drew the route (1st, 2nd, etc.).

Quick visualization — no install needed

If you just need to see the routes on a map, these free browser tools work instantly:

Density and corridor analysis

When dozens or hundreds of Travelers draw routes, the most valuable insight is where routes overlap — the corridors with the strongest demand signal. TIPS includes a built-in heat map on the report page, but for deeper analysis:

Professional GIS analysis

Government agencies and transportation consultancies typically use desktop GIS software for formal analysis. GeoJSON imports natively into both major platforms:

Programmatic analysis

For data scientists and developers, GeoJSON is just JSON — it loads natively in Python, R, and JavaScript:

import geopandas as gpd

routes = gpd.read_file("survey-routes-2026-05-27.geojson")
print(f"{len(routes)} routes from {routes['responseId'].nunique()} respondents")

# Buffer each route by 200 meters and find overlapping corridors
buffered = routes.to_crs(epsg=3857).buffer(200)
# ... spatial analysis continues

Typical use cases

• Demand corridor identification — overlay all Traveler routes to find the corridors with the most overlap, signaling where new or improved service would serve the most people.
• Proposed route validation — compare Traveler-drawn routes against a proposed transit line to quantify how many respondents' travel patterns it would serve.
• Public input documentation — attach the GeoJSON export to a planning report or federal grant application as evidence of community-sourced demand.
• Before/after comparison — run the same survey before and after a service change to measure how Travelers' preferred routes shift.

Common questions about TIPS route data

What is GeoJSON?

GeoJSON is an open standard format for encoding geographic features — points, lines, and polygons — as JSON. It is supported by virtually every mapping and GIS tool available today, from browser-based visualizers to enterprise platforms like ArcGIS.

What is in a TIPS GeoJSON route export?

A FeatureCollection where each Traveler-drawn route is one Feature with a LineString geometry containing the waypoint coordinates, plus properties for responseId (to correlate with the CSV export), name (Traveler-supplied label, if any), and position (the order in which they drew the route).

What is the easiest way to view a TIPS GeoJSON file?

Drag the file onto geojson.io in your browser. All routes appear on a map instantly with no install or account required. For collaborative review, Felt (felt.com) lets you upload, annotate, and share a public link.

Which GIS tool should I use for serious analysis?

QGIS if you want a free, open-source desktop GIS — the most widely used by government planners. ArcGIS if your agency already has Esri licenses; GeoJSON imports natively. Both let you overlay Traveler routes on census tracts, existing transit networks, or zoning maps for corridor and demand analysis.

How do I do heat map or density analysis on TIPS routes?

Upload the GeoJSON to kepler.gl (Uber's open-source browser tool) and apply the heatmap layer. For deeper buffer-based corridor analysis, load the file in Python with geopandas (gpd.read_file), reproject to a meter-based CRS, buffer each route by your corridor width, and union the overlapping buffers.

Can I use TIPS route data for federal grant applications?

Yes. The GeoJSON export is admissible evidence of public demand and is commonly attached to RAISE, Title VI, and other federal applications as documentation of community-sourced input. The same file can be styled in Mapbox Studio for inclusion in planning reports.

Can I analyze TIPS route data in Python?

Yes. Use geopandas: routes = gpd.read_file("survey-routes.geojson"). The dataframe includes the geometry column plus all properties (responseId, name, position). From there you can run spatial joins, density analysis, route clustering, or generate reports in matplotlib.