OvertureMaps / OvertureMaps/data

[Buildings] Consumption or conflation issue in San Diego County

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Dominant language
Python
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Description

I recently noticed that many of the buildings in San Diego County are being sourced from Microsoft ML buildings instead of from this higher-quality Esri dataset that covers pretty much all of San Diego County. I suspect that either this dataset isn't being consumed, or that there's an issue with the data conflation, leading to Microsoft's buildings being given a higher priority.

For context, I'm an OpenStreetMap mapper who primarily adds buildings from the aforementioned dataset. Rapid recently started sourcing the Esri Community Maps building footprints from OvertureMaps instead of from the many separate sources in ArcGIS, which is how I came across this issue.

Contributor guide

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First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

Start by tracing how the Esri Community Maps building footprints and Microsoft ML buildings are ingested and conflated for San Diego County. Compare the resulting buildings with the linked Esri dataset; done means the Esri coverage is consumed and receives the intended priority without harmful conflation.

Written by the indexing model from the issue text.

Assessment

Tech stack
python
Domain
data-engineering
Issue type
Bug
Difficulty
4/5
Estimated time
3-5 days
Activity status
Quiet
Clarity
Mostly clear
Newbie friendliness
45/100

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