Humans and Machines Mapping Together

Sunday 12:00, S.1.5 no recording This event will not be recorded.

Sajjad Anwar 60 minutes

Development Seed

Machine Learning (ML) can be used to supercharge human mapping efforts by prioritizing which areas to look in. Instead of generating geometries, ML models can estimate the likelihood that a feature appears in a certain area. Then human mappers can use this guidance to decide where they map - focusing on quality, and improving efficiency.

We'll walk through building a machine learning pipeline and present a workflow for human mappers to create OpenStreetMap features over large areas. The workshop will cover:

  • Using OpenStreetMap as training data for a ML model (using the open source tool Label Maker (
  • Training a sophisticated ML model, to identify whether certain features appear in a tile
  • Using the output of the model to help guide mappers to priority areas
  • Integrating this workflow into existing OpenStreeMap tools (Tasking Manager and To-Fix)

We've used this method to map electricity infrastructure in Pakistan, Nigeria, and Zambia. We look forward to sharing it with more mappers and increasing the impact of everyone's efforts.