Issue retreiving building footprints west of amsterdam around Schipol

I tried to run the following with a Microsoft planetary computer to get building footprints, but apparently the buildings West of Amsterdam are not showing up?

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

asset = collection.assets["delta"]

storage_options = {
    "account_name": asset.extra_fields["table:storage_options"]["account_name"],
    "sas_token": asset.extra_fields["table:storage_options"]["credential"],
}
table = deltalake.DeltaTable(asset.href, storage_options=storage_options)

quadkeys = [
    int(mercantile.quadkey(tile))
    for tile in mercantile.tiles(*buffer[0].bounds, zooms=9)
]
quadkeys

uris = table.file_uris([("quadkey", "in", quadkeys)])
uris

df = dgd.read_parquet(uris, storage_options=storage_options)

where buffer is a circle around (52.372778, 4.893611)
# Get bounds
minx, miny, maxx, maxy = area_of_interest.total_bounds
min_dist = min([abs(minx-latlng[0]), abs(miny-latlng[1]), abs(maxx-latlng[0]), abs(maxy-latlng[1])])

# Create a GeoDataFrame with the specified point
gdf = gpd.GeoDataFrame(geometry=[Point(latlng[1], latlng[0])], crs=crs)

# The UTM zone number can be calculated from the lnggitude
utm_zone = int((latlng[1] + 180) / 6) + 1
# Determine the hemisphere and assign the appropriate UTM CRS
if latlng[0] >= 0:  # Northern Hemisphere
    local_utm_crs = f'EPSG:326{utm_zone:02d}'
else:  # Southern Hemisphere
    local_utm_crs = f'EPSG:327{utm_zone:02d}'

# Reproject to a local UTM CRS
gdf_utm = gdf.to_crs(local_utm_crs)

# Create a 50 km buffer around the point
buffer_circle = gdf_utm.buffer((radius) * 1000)  # Convert km to meters

buffer = buffer_circle

Start by rerunning the provided Python query for the 50 km buffer around (52.372778, 4.893611), checking the generated UTM bounds, quadkeys, and returned URIs. Compare the queried area with the ms-buildings Delta table coverage and determine whether the missing footprints come from the spatial query or the dataset; document the confirmed cause and reproducible result.