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Adding comprehensive global nighttime light pollution dataset.

Dataset: https://archive.org/details/radiance-geojson-data-2025
Repository: https://codeberg.org/imigueldiaz/radiance-geojson

  • 176 countries with radiance, MPSAS, and Bortle scale values
  • 0.5 km sampling resolution
  • ~2.8 GB total (compressed JSON format)
  • Permanently hosted on Internet Archive
  • License: CC-BY 4.0 (VIIRS data) + MIT (code)

Use cases: astronomy, dark sky research, urban planning, environmental studies

@ppival
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ppival commented Nov 25, 2025

Thanks, @imigueldiaz but the new file (core/EarthScience/Radiance-GeoJSON-Light-Pollution.yml) in this PR has 38-Cloud metadata, which already exists elsewhere in the repository. To correctly add the Radiance GeoJSON light pollution dataset as described in your PR, please replace the contents of that file with the following metadata:


title: Radiance GeoJSON — Global Light Pollution
homepage: https://archive.org/details/radiance-geojson-data-2025
category: EarthScience
description: Global nighttime light pollution dataset provided as GeoJSON. Contains VIIRS-derived radiance values plus derived MPSAS and Bortle-scale estimates for ~176 countries, sampled at ~0.5 km resolution. Permanently hosted on Internet Archive; suitable for astronomy, dark-sky research, urban planning, and environmental studies.
version: 1.0
keywords: night-time lights, light pollution, radiance, VIIRS, MPSAS, Bortle, GeoJSON, global, sampling 0.5km
image:
temporal: 2025
spatial: Global; ~0.5 km sampling resolution
access_level: public
copyrights:
accrual_periodicity:
specification: GeoJSON (compressed JSON distribution; feature collections / newline-delimited GeoJSON)
data_quality: true
data_dictionary: Included with the dataset and repository (see references)
language: en
license:


…N dataset

Apologies for the error. The file previously contained 38-Cloud metadata instead of the Radiance GeoJSON light pollution dataset information. This commit corrects the metadata with:
- Proper dataset description (VIIRS-derived global light pollution data)
- Complete technical details (173 countries, 139M+ points, 0.5km resolution)
- Both GeoJSON and PostGIS database formats (3.2GB compressed, ~27GB restored)
- Correct licensing (CC BY 4.0 for data, MIT for code)
- Proper references to Internet Archive and project repository
@imigueldiaz
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@ppival Thanks for catching that error! I've corrected the file with the proper Radiance GeoJSON metadata. Apologies for the confusion with the 38-Cloud data.

Note: While testing locally, I noticed that core/Climate+Weather/Washington Post Climate Change.yml fails validation with the current tests/validate.py script due to an encoding issue. The file contains UTF-8 characters (smart quotes: ' U+2019 and U+2014) but the validation script opens files without specifying encoding='utf-8', causing a UnicodeDecodeError on Windows systems.

Error details:

  • File: core/Climate+Weather/Washington Post Climate Change.yml
  • Issue: Contains UTF-8 characters at positions 287-289 (') and 615-617 (—)
  • Error: 'charmap' codec can't decode byte 0x9d in position 1591: character maps to <undefined>
  • Fix needed: Line 31 in tests/validate.py should use open(entry, encoding='utf-8') instead of open(entry)

The file validates correctly when opened with UTF-8 encoding. Just wanted to bring this to your attention in case you'd like to address it.

@ppival ppival merged commit d8059b7 into awesomedata:master Nov 26, 2025
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ppival commented Nov 26, 2025

Thanks @imigueldiaz and for the note on the validation issue - I'm going to post that under Issues and tag @caesar0301

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