Data cluster

Thailand Motorcycle Taxi Data.

Bangkok motorcycle-taxi win counts, driver counts, stand mapping, app-certification context, and last-mile data strategy.

2 sources Updated 2026-05-11 Download JSON

Best use for travel intelligence

For travel decisions, motorcycle-taxi data is strongest for short soys, BTS/MRT last-mile access, and neighborhoods where a car taxi adds more friction than value.

What this changes for travelers

  • DLT stand/driver counts: How many wins and licensed drivers exist in Bangkok.
  • OSM and POI layers: Where a win or stand is likely mapped and how reliable its location is.
  • App/legal guidance: Which services are regulated and when a motorcycle taxi is a realistic last-mile move.
  • Local movement logic: Useful for short soys, BTS/MRT access, and neighborhoods where a car taxi is slower than expected.

Best sources to start with

  • Best count dataset: DLT Bangkok motorcycle-taxi stands and drivers dataset for win and driver counts.
  • Best mapping layer: OpenStreetMap/Overpass for amenity=taxi and related local tagging where wins or stands are mapped.
  • Best licensed enrichment: Google Places, Longdo, and NOSTRA for Thai-local search and nearby place context when a win has a stable mapped presence.
  • Best developer starting point: Keep win counts, driver counts, and stand coordinates separate because many datasets provide only counts without precise geometry.
Official / agency sources

1 of 2 sources look official or agency-backed.

API/feed candidates

1 sources expose API, feed, CKAN/DataStore, JSON, XML, or similar machine-readable access.

Near-real-time signals

0 sources have live, hourly, event-driven, warning, or frequent update language.

Developer note

Separate win counts, driver counts, stand mapping, and app-certification context; many wins need manual coordinate validation.

Last checked and source confidence

Last checked: 2026-05-11.

Source confidence: This cluster is strongest when several sources describe the same traveler problem from different angles: official context, machine-readable feeds, and slower fallback documentation.