NextBillion.AI-OSM-PedestrianMapping

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Introduction

To collaborate with the OpenStreetMap community and create a quality pedestrian network in the US using RapID and JOSM, validated by trained mappers and local OSM communities.


Data Projects

We reviewed existing pedestrian data and improved the network in Charlestown, Cambridge, Somerville, and Watertown.

Improved pedestrian route coverage and enhanced walking directions to provide the best possible navigation by validating the below attributes:

  • Sidewalks
  • Footways
  • Crossings
  • Steps
  • Cycleway (only when shared with Footways)
  • Relations between the road network and their respective footways


Contributors

The map editing team consists of Mappers and Validators, their accounts are - VLD238, VLD239,VLD240, VLD241,VLD242, VLD243,VLD244

Guidelines

We follow OSM guidelines as per the wiki and also consider local inputs as appropriate.


Tools

The team would use RapID and JOSM tools to edit map data and fix validation errors as flagged by the tool.


Resources Used

Below resources would be used to enhance the pedestrian network:

  • Publicly available satellite Imagery in JOSM, to identify and add attributes like footways, crossings, steps etc visible from aerial view
  • Street imageries like OSC, Mapillary, etc., to identify and add attributes like footways, crossings, steps etc which are covered under vegetation and not visible from aerial view
  • Strava
  • Other publicly available GPS traces


Pre-review analysis

A Pre-review analysis would be performed in multiple areas across the selected city to check the correctness of the existing data and estimate value addition. Also, we would identify the best suitable imagery and document challenges if any. Based on the initial observations, the information would be passed to the local mappers/community through GitHub/Wiki and ask for further suggestions if any.


Step-by-step Procedure

Screenshot 2020-10-21 at 11.34.07 AM.png


Changeset Comments

The team would provide appropriate changeset comments that comply with the OSM changeset guidelines


Error Detection

We would use various QA tools, JOSM validation warnings, and OSM inspectors to validate the edits performed. To analyze the detailed history of the segments, we will use the below tools:

  • OSM cha
  • OSM Analytics
  • OSM achavi


For more details, please write to osm@nextbillion.ai