{
  "abstract": "Google Earth Engine (GEE) and Microsoft Planetary Computer (MPC) distribute Sentinel-2 Level-2A surface reflectance, and their outputs can be combined in one time series. Over a 73 ha cattle farm in northern Colombia, we tested whether the two platforms yield the same parcel-scale vegetation and water indices and, where they differ, whether the difference originates in the product (the L2A scene), the processing chain (masking, 3 × 3 smoothing, NDVI, EVI, NDWI and monthly median) or the scene universe (which acquisitions enter a composite). For the ten pairs in which both platforms served the same product, scene classification and harmonised reflectance matched in every comparable pixel, and the same chain run locally or server-side in GEE agreed within 10⁻⁶. The catalogues, however, did not hold the same scenes. Between June 2024 and April 2025, 10 of 146 scene–tile records existed only in GEE, six of them Sentinel-2C records from around the satellite's entry into operations, and none only in MPC. In 22 of 136 common records, all from June–July 2024, the catalogues held different L2A generations; of the ten such pairs with valid pixels, one had a different cloud mask. Adding the GEE-only scenes shifted mean monthly NDVI over the farm by −0.0005 (December 2024) and −0.0087 (January 2025), and by up to −0.028 in a public 1 km² demonstration area (January 2025). For the operations tested, the platforms are computationally equivalent, but combining them requires reconciling scene inventories. The reconciliation table, composite scene lists and open-source tools are released.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": null,
  "author_total": 1,
  "authors": [
    {
      "name": "Heiber Alexander Pantevez Villamil"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/dqg5gcs9ejvpc.bib",
  "cited_by": 0,
  "doi": "10.31223/x5sc0b",
  "fulltext_url": null,
  "id": "dqg5gcs9ejvpc",
  "issns": [],
  "landing_url": "https://eartharxiv.org/repository/view/15577/",
  "language": null,
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/legalcode",
  "metadata_licence": null,
  "native_subjects": [
    [
      "bepress",
      "Earth Sciences"
    ],
    [
      "bepress",
      "Environmental Sciences"
    ],
    [
      "bepress",
      "Google Earth Engine"
    ],
    [
      "bepress",
      "Microsoft Planetary Computer"
    ],
    [
      "bepress",
      "STAC"
    ],
    [
      "bepress",
      "Sentinel-2"
    ],
    [
      "bepress",
      "interoperability"
    ],
    [
      "bepress",
      "provenance"
    ],
    [
      "bepress",
      "reproducibility"
    ],
    [
      "bepress",
      "scene inventory"
    ],
    [
      "openalex",
      "2303|Remote Sensing in Agriculture"
    ]
  ],
  "openalex": "W7222865227",
  "pdf_url": "https://eartharxiv.org/repository/object/15577/download/27044/",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-19",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/dqg5gcs9ejvpc.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:17:46Z",
      "native_id": "15577",
      "source": "eartharxiv",
      "url": "https://eartharxiv.org/repository/view/15577/"
    }
  ],
  "subjects": [
    {
      "field": "earth",
      "origin": "bepress:Environmental Sciences",
      "subfield": "environmental-science"
    }
  ],
  "title": "Same computation, different scenes: a single-site comparison of Sentinel-2 L2A composites from Google Earth Engine and Microsoft Planetary Computer",
  "title_text": "Same computation, different scenes: a single-site comparison of Sentinel-2 L2A composites from Google Earth Engine and Microsoft Planetary Computer",
  "type": "preprint",
  "updated_at": "2026-10-30T12:17:46Z",
  "url": "https://research.draconitic.com/paper/dqg5gcs9ejvpc",
  "venue": "EarthArXiv",
  "versions": []
}