Published July 27, 2026 | Version 1.0.0

Vehicle speed dataset for the major European road network derived from Sentinel-2 imagery, 2022–2026

  • 1. Heidelberg Institute for Geoinformation Technology (HeiGIT)
  • 2. ROR icon University of Łódź
  • 3. GIScience Research Group, Institute of Geography, University of Heidelberg

Description

The dataset provides individual vehicle speed observations on European E-roads: motorways, trunk roads, primary and secondary roads, as tagged in OpenStreetMap as e-roads, for the years 2022-2026

Speeds are derived from Copernicus Sentinel-2 Level-2A satellite optical imagery using a processing pipeline that exploits the short, well-characterized acquisition delays between the blue (B02_10m), green (B03_10m), and red bands (B04_10m) of the Sentinel-2 push-broom instrument.

A moving vehicle appears at slightly displaced positions in the three bands, forming a moving echo.
The detected displaced intensity peaks are linked into per-vehicle trajectories through a prediction-and-matching procedure.
The resulting displacements are converted into ground speeds using publicly accessible inter-band time delays.

Each record contains the trajectory geometry, per-channel displacements and headings, internal quality indicators, the estimated speed, the acquisition timestamp, and the source Sentinel-2 product identifier.

The dataset is distributed as GeoPackage files, with one record per detected vehicle, and can support studies of traffic patterns, speed behavior, transport modeling, and the calibration of road network attributes at a continental scale.

Files

Files (7.2 GB)

Name Size
md5:f5d34128d3b20e9deac5024763958439
1.1 kB Download
md5:ca509a03b6d85142cf3a7b0bcd1b0153
5.9 kB Download
md5:43d383bbe9544cde347ff204e74bee73
5.9 kB Download
md5:d3b616c622dfadee1f57e9a754cf21e5
5.9 kB Download
md5:e5d1723c3d9deae33f2511386c590261
5.9 kB Download
md5:1a9a6614827ad31658b5f0d34faa4576
5.9 kB Download
md5:fb382631d0d3932a9a7222094adc68b0
11.2 MB Download
md5:b07d83ff75c67758d3e4723248c6e6d5
937.4 MB Download
md5:8a2bbdd9594f0882af976f3727c59b80
1.3 GB Download
md5:ab5d032cf643d3c4340fa16747f7f939
1.5 GB Download
md5:8680f7c097cdb529a2be171b7c0fe549
2.2 GB Download
md5:1aad8ddf937e2c0efb71f325774028c5
1.2 GB Download
md5:842c5fdfa545a155adc28d987e967f80
59.8 MB Download

Additional details

Dates

Created
2026-07-27

Software

Repository URL
https://gitlab.heigit.org/traffic-flow-estimator/nibblergb
Programming language
Python
Development Status
Active