microsoft / microsoft/GlobalMLBuildingFootprints
How to access latest data and understand versions
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- Dominant language
- Python
- Stars
- 2k
- Forks
- 277
- PR merge metrics
- No merged PRs in 30d
Description
First, thanks and much appreciation for making this both open and accessible, both via the dataset-links.csv linked from this repository and on the planetary computer data catalog!
I can happily access either source, but I'm not clear which data releases are available in each location, or how best to pull updates.
-
https://minedbuildings.blob.core.windows.net/global-buildings/dataset-links.csv lists all URLs with
2023-12-26in the path. Is2023-12-26the release date for all these files? -
the README.md here lists an update for
2024-01-03, particularly for buildings in Brazil and Italy. Is this update included in files linked fromdataset-links.csv? -
the planetary computer example notebook shows how to access the data as a Delta Table, which lists URIs under
2023-04-25/ml-buildings.parquet, andtable.history()gives a single WRITE operation at timestamp 1682774982678, around2023-04-29. Are any of the more recent updates listed in this repository present in that parquet dataset, or are there plans to push updates there?
Should I be aware of tools to help with bulk access or reading metadata for either location?
-
I can request a signed URL with an SAS token for the delta table blob storage container from https://planetarycomputer.microsoft.com/api/sas/v1/sign?href=https://bingmlbuildings.blob.core.windows.net/footprints/delta and give that to
azcopy list, though I don't discover any other versions or updates there. -
I'm not sure how to directly access or list all files under
https://minedbuildings.blob.core.windows.net/global-buildings, only directly accessing those listed in the CSV, or linked from the README in history here (e.g. Abyei. Are all versions (or all latest versions, with release/update metadata) intended to be accessible?
Contributor guide
No contributing guide indexed for this repository
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start with README.md, dataset-links.csv, and the Planetary Computer example notebook named in the issue. Verify how release dates, Delta Table history, bulk listing, and metadata access relate, then document the supported versions and update workflow.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- azure, python
- Domain
- cloud, data-engineering, documentation
- Issue type
- Documentation
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 30/100