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FAQ: Geolocation Limitations in M-Lab Data

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Why M-Lab measurements often share identical coordinates and how to work around coarse geolocation for spatial analysis.

intermediate GeolocationData AccessPrivacyBigQuery & SQL

Q: Why do many M-Lab measurements show identical latitude/longitude coordinates? Can I get more precise location data for fine-grained spatial analysis?

A: M-Lab’s geolocation data has intentional limitations due to privacy considerations and the inherent constraints of IP-based geolocation:

Geolocation Source and Privacy

  • M-Lab uses MaxMind’s GeoLite2 database for IP geolocation
  • Geographic precision is intentionally kept coarse (typically city-level) for privacy protection
  • All M-Lab data is publicly accessible, so fine-grained location data could compromise user privacy

Common Limitations

  • Multiple measurements may share identical coordinates within a city
  • Geolocation accuracy varies significantly by region and ISP
  • Rural or less-populated areas often have very broad location estimates
  • The client.Geo.AccuracyRadiusKm field indicates the estimated accuracy radius

Improving Spatial Precision

  1. Filter by accuracy: Use client.Geo.AccuracyRadiusKm <= 5 to focus on more precise estimates
  2. Alternative geolocation services: Consider using paid services like MaxMind GeoIP2, IPinfo, or similar to re-annotate M-Lab data with your own geolocation
  3. Grid-based analysis: Aggregate data into geographic grids rather than relying on exact coordinates
  4. Use newer datasets: The ndt7_union table includes measurements from more servers and may provide better geographic coverage

For Fine-Grained Analysis

M-Lab’s built-in geolocation may not be suitable for block-level or infrastructure-specific analysis. Consider combining M-Lab data with external geolocation services or using statistical methods to estimate coverage areas based on network topology and known infrastructure locations.