Sentinel 2A: datastrip in item.id does not match datastrip in item.properties.s2:datastrip_id

I was just debugging why I had duplicate tiles in a certain pipeline. I found out that this was related to the datastrip_id property, which depends on to the downlink station - see S2 specification. The data seems to be the same for both item's, although I only checked this for 1 band. Why do you keep duplicate data when multiple downlink stations are used?

Anyways... I then noticed that the datastrip id that is included in the item.id does not match the one that is provided in item.properties.s2:datastrip_id. Not sure if this is important, but I thought it would be worth mentioning. Please see example below.

from copy import deepcopy

import pandas as pd
import planetary_computer
import pystac_client

def items_to_dataframe(items):
    _items = []
    for i in items:
        _i = deepcopy(i)
        _items.append(_i)
    df = pd.DataFrame(pd.json_normalize(_items))
    for field in ["properties.datetime"]:
        if field in df:
            df[field] = pd.to_datetime(df[field])
    df = df.sort_values("properties.datetime")
    return df


catalog = pystac_client.Client.open(
    "https://planetarycomputer.microsoft.com/api/stac/v1",
    modifier=planetary_computer.sign_inplace,
)

roi = {
    "type": "Polygon",
    "coordinates": [
        [
            [146.0678527, -15.3746464],
            [147.0909455, -15.3765786],
            [147.0913918, -16.369226],
            [146.0632786, -16.3671625],
            [146.0678527, -15.3746464],
        ]
    ],
}


search = catalog.search(
    collections=["sentinel-2-l2a"],
    intersects=roi,
    datetime="2022-01-01/2022-11-01",
)

items = search.item_collection()

items_ = [i.to_dict() for i in items]
df = items_to_dataframe(items_)


def split_id(x):
    return pd.Series(x.id.split("_"))


df[
    [
        "mission_id",
        "product_level",
        "datetake_start_time",
        "relative_orbit_number",
        "tilenumber",
        "id_datastrip",
    ]
] = df.apply(split_id, axis=1)

# two examples for which I found data which same data, but different datastrips
SAME_DATA_DIFFERENT_DATASTRIP = [
    "S2A_MSIL2A_20220128T002711_R016_T55LDC_20220227T190716",
    "S2A_MSIL2A_20220128T002711_R016_T55LDC_20220212T221526",
]

df_ = df.loc[df["id"].isin(SAME_DATA_DIFFERENT_DATASTRIP)].copy()

# makes it a bit easier to see the difference
def split_s2_datstrip(x):
    return x["properties.s2:datastrip_id"].split("_")[6]


df_["s2_datastrip"] = df_.apply(split_s2_datstrip, axis=1)
df_[["id_datastrip", "s2_datastrip"]]

Im Bericht werden keine Repository-Dateien oder Tests genannt. Beginne damit, die beiden Sentinel-2-Beispiele anhand des Katalogs zu reproduzieren, und vergleiche dann das Datastrip-Segment in item.id mit properties.s2:datastrip_id. Verfolge anschließend, wie diese Felder generiert oder importiert werden. Als erledigt gilt die Aufgabe, wenn das Verhalten mit den doppelten Daten und die Nichtübereinstimmung der Bezeichner erklärt sind und, falls sich dies als Katalogfehler bestätigt, durch korrigierte Daten oder eine Regression-Prüfung abgedeckt werden.