# Copyright 2025, SERTIT-ICube - France, https://sertit.unistra.fr/
# This file is part of eoreader project
# https://github.com/sertit/eoreader
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""Sentinel-2 products"""
import contextlib
import difflib
import json
import logging
import os
import re
import tempfile
import zipfile
from collections import defaultdict, namedtuple
from datetime import datetime
from enum import unique
from typing import Union
import geopandas as gpd
import numpy as np
import pandas as pd
import rasterio
import xarray as xr
from affine import Affine
from lxml import etree
from rasterio import errors, features, transform
from rasterio.crs import CRS
from rasterio.enums import Resampling
from sertit import AnyPath, files, geometry, path, rasters, types, vectors
from sertit.misc import ListEnum
from sertit.types import AnyPathStrType, AnyPathType
from shapely.geometry import box
from eoreader import DATETIME_FMT, EOREADER_NAME, cache, utils
from eoreader.bands import (
ALL_CLOUDS,
AOT,
BLUE,
CA,
CIRRUS,
CLOUDS,
EOREADER_STAC_MAP,
GREEN,
NARROW_NIR,
NIR,
RAW_CLOUDS,
RED,
SCL,
SHADOWS,
SWIR_1,
SWIR_2,
SWIR_CIRRUS,
VRE_1,
VRE_2,
VRE_3,
WV,
WVP,
BandNames,
S2MaskBandNames,
SpectralBand,
is_mask,
is_s2_l2a_specific_band,
to_band,
to_str,
)
from eoreader.exceptions import InvalidProductError, InvalidTypeError
from eoreader.keywords import ASSOCIATED_BANDS
from eoreader.products import OpticalProduct, StacProduct
from eoreader.products.optical.optical_product import RawUnits
from eoreader.products.product import OrbitDirection
from eoreader.stac import CENTER_WV, FWHM, GSD, ID, NAME
from eoreader.utils import simplify
LOGGER = logging.getLogger(EOREADER_NAME)
[docs]
@unique
class S2ProductType(ListEnum):
"""Sentinel-2 products types (L1C or L2A)"""
L1C = "MSIL1C"
"""Level-1C: https://sentinel.esa.int/web/sentinel/user-guides/sentinel-2-msi/product-types/level-1c"""
L2A = "MSIL2A"
"""Level-2A: https://sentinel.esa.int/web/sentinel/user-guides/sentinel-2-msi/product-types/level-2a"""
[docs]
@unique
class S2GmlMasks(ListEnum):
"""Sentinel-2 GML masks (processing baseline < 4.0)"""
FOOTPRINT = "DETFOO"
CLOUDS = "CLOUDS"
DEFECT = "DEFECT"
NODATA = "NODATA"
SATURATION = "SATURA"
QUALITY = "TECQUA"
# L2A (jp2)
CLDPRB = "CLDPRB"
SNWPRB = "SNWPRB"
[docs]
@unique
class S2Jp2Masks(ListEnum):
"""Sentinel-2 jp2 masks (processing baseline > 4.0)"""
# Both L1C and L2A
DETFOO = "DETFOO"
CLASSI = "CLASSI" # Regroups CLOUDS and SNOWICE
QUALIT = "QUALIT" # Regroups CLOLOW, TECQUA, DEFECT, SATURA, NODATA
# L2A
CLDPRB = "CLDPRB"
SNWPRB = "SNWPRB"
BAND_DIR_NAMES = {
S2ProductType.L1C: ".",
S2ProductType.L2A: {
"01": ["R60m"],
"02": ["R10m", "R20m", "R60m"],
"03": ["R10m", "R20m", "R60m"],
"04": ["R10m", "R20m", "R60m"],
"05": ["R20m", "R60m"],
"06": ["R20m", "R60m"],
"07": ["R20m", "R60m"],
"08": ["R10m"],
"8A": ["R20m", "R60m"],
"09": ["R60m"],
"11": ["R20m", "R60m"],
"12": ["R20m", "R60m"],
"SCL": ["R20m", "R60m"],
"AOT": ["R10m", "R20m", "R60m"],
"WVP": ["R10m", "R20m", "R60m"],
},
}
S2_MSK = namedtuple("S2_MSK", ["mask_fname", "band_number"])
MASK_MAPPING_PB_0400 = {
S2MaskBandNames.DETFOO: S2_MSK(mask_fname=S2Jp2Masks.DETFOO, band_number=1),
S2MaskBandNames.ANC_LOST: S2_MSK(mask_fname=S2Jp2Masks.QUALIT, band_number=1),
S2MaskBandNames.ANC_DEG: S2_MSK(mask_fname=S2Jp2Masks.QUALIT, band_number=2),
S2MaskBandNames.MSI_LOST: S2_MSK(mask_fname=S2Jp2Masks.QUALIT, band_number=3),
S2MaskBandNames.MSI_DEG: S2_MSK(mask_fname=S2Jp2Masks.QUALIT, band_number=4),
S2MaskBandNames.QT_DEFECTIVE_PIXELS: S2_MSK(
mask_fname=S2Jp2Masks.QUALIT, band_number=5
),
S2MaskBandNames.QT_NODATA_PIXELS: S2_MSK(
mask_fname=S2Jp2Masks.QUALIT, band_number=6
),
S2MaskBandNames.QT_PARTIALLY_CORRECTED_PIXELS: S2_MSK(
mask_fname=S2Jp2Masks.QUALIT, band_number=7
),
S2MaskBandNames.QT_SATURATED_PIXELS: S2_MSK(
mask_fname=S2Jp2Masks.QUALIT, band_number=8
),
# S2MaskBandNames.CLOUD_INV: S2_MSK(mask_fname=S2Jp2Masks.QUALIT, band_number=9), # Non existing for L1C
S2MaskBandNames.OPAQUE: S2_MSK(mask_fname=S2Jp2Masks.CLASSI, band_number=1),
S2MaskBandNames.CIRRUS: S2_MSK(mask_fname=S2Jp2Masks.CLASSI, band_number=2),
S2MaskBandNames.SNOW_ICE: S2_MSK(mask_fname=S2Jp2Masks.CLASSI, band_number=3),
}
[docs]
class S2Product(OpticalProduct):
"""
Class of Sentinel-2 Products
You can use directly the .zip file
"""
[docs]
def __init__(
self,
product_path: AnyPathStrType,
archive_path: AnyPathStrType = None,
output_path: AnyPathStrType = None,
remove_tmp: bool = False,
**kwargs,
) -> None:
# Processing baseline < 02.07: images not georeferenced (L2Ap and after)
# Is this product comes from a processing baseline less than 4.0
# The processing baseline 4.0 introduces format changes:
# - masks are given as GeoTIFFs instead of GML files
# - an offset is added to keep the zero as no-data value
# See here for more information
# https://sentinels.copernicus.eu/web/sentinel/-/copernicus-sentinel-2-major-products-upgrade-upcoming
self._processing_baseline = None
self.raw_no_data = 0
self.no_data_val = {}
# L2Ap
self._is_l2ap = False
# S2 Sinergise
self._is_sinergise = kwargs.pop("is_sinergise", False)
# Initialization from the super class
super().__init__(product_path, archive_path, output_path, remove_tmp, **kwargs)
try:
self.read_mtd()
except InvalidProductError:
LOGGER.warning(
f"Corrupted metadata for {self.path}. "
f"Trying to process this product in degraded mode. "
f"Every process needing something from the metadata won't be able to be computed (i.e. HILLSHADE)"
)
def _pre_init(self, **kwargs) -> None:
"""
Function used to pre_init the products
(setting needs_extraction and so on)
"""
self._has_cloud_cover = True
self.needs_extraction = False
# Use filename for SAFE names, not for others
# S2A_MSIL1C_20191215T110441_N0208_R094_T30TXP_20191215T114155.SAFE has 65 characters
self._use_filename = len(self.filename) > 50
self._raw_units = RawUnits.REFL
# We need to set the constellation asap for this product (to manage correctly the name of broken products)
self.constellation = self._get_constellation()
# Pre init done by the super class
super()._pre_init(**kwargs)
def _post_init(self, **kwargs) -> None:
"""
Function used to post_init the products
(setting sensor type, band names and so on)
"""
self.tile_name = self._get_tile_name()
# Get processing baseline: N0213 -> 02.13
pr_baseline = float(self.split_name[3][1:]) / 100
self._processing_baseline = pr_baseline
# Post init done by the super class
super()._post_init(**kwargs)
def _set_pixel_size(self) -> None:
"""
Set product default pixel size (in meters)
"""
# S2: use 10 m resolution, even if we got 60 m and 20 m resolution
# In the future, maybe use one resolution per band?
self.pixel_size = 10.0
def _get_tile_name(self) -> str:
"""
Retrieve tile name
Returns:
str: Tile name
"""
return self.split_name[-2]
def _set_product_type(self) -> None:
"""Set products type"""
self.product_type = S2ProductType.from_value(self.split_name[1])
def _set_instrument(self) -> None:
"""
Set instrument
Sentinel-2: https://sentinels.copernicus.eu/web/sentinel/missions/sentinel-2/instrument-payload/
"""
self.instrument = "MSI"
def _map_bands(self) -> None:
"""
Map bands
"""
l2a_bands = {
CA: SpectralBand(
eoreader_name=CA,
**{NAME: "B01", ID: "01", GSD: 60, CENTER_WV: 442, FWHM: 21},
),
BLUE: SpectralBand(
eoreader_name=BLUE,
**{NAME: "B02", ID: "02", GSD: 10, CENTER_WV: 492, FWHM: 66},
),
GREEN: SpectralBand(
eoreader_name=GREEN,
**{NAME: "B03", ID: "03", GSD: 10, CENTER_WV: 560, FWHM: 36},
),
RED: SpectralBand(
eoreader_name=RED,
**{NAME: "B04", ID: "04", GSD: 10, CENTER_WV: 665, FWHM: 31},
),
VRE_1: SpectralBand(
eoreader_name=VRE_1,
**{NAME: "B05", ID: "05", GSD: 20, CENTER_WV: 704, FWHM: 15},
),
VRE_2: SpectralBand(
eoreader_name=VRE_2,
**{NAME: "B06", ID: "06", GSD: 20, CENTER_WV: 740, FWHM: 15},
),
VRE_3: SpectralBand(
eoreader_name=VRE_3,
**{NAME: "B07", ID: "07", GSD: 20, CENTER_WV: 781, FWHM: 20},
),
NIR: SpectralBand(
eoreader_name=NIR,
**{NAME: "B08", ID: "08", GSD: 10, CENTER_WV: 833, FWHM: 106},
),
NARROW_NIR: SpectralBand(
eoreader_name=NARROW_NIR,
**{NAME: "B8A", ID: "8A", GSD: 20, CENTER_WV: 864, FWHM: 21},
),
WV: SpectralBand(
eoreader_name=WV,
**{NAME: "B09", ID: "09", GSD: 60, CENTER_WV: 944, FWHM: 20},
),
SWIR_1: SpectralBand(
eoreader_name=SWIR_1,
**{NAME: "B11", ID: "11", GSD: 20, CENTER_WV: 1612, FWHM: 92},
),
SWIR_2: SpectralBand(
eoreader_name=SWIR_2,
**{NAME: "B12", ID: "12", GSD: 20, CENTER_WV: 2190, FWHM: 180},
),
}
if self.product_type == S2ProductType.L2A:
self.bands.map_bands(l2a_bands)
elif self.product_type == S2ProductType.L1C:
self.bands.map_bands(
{
**l2a_bands,
SWIR_CIRRUS: SpectralBand(
eoreader_name=SWIR_CIRRUS,
**{NAME: "B10", ID: "10", GSD: 60, CENTER_WV: 1380, FWHM: 30},
),
}
)
else:
raise InvalidProductError(f"Invalid Sentinel-2 name: {self.filename}")
[docs]
@cache
def crs(self) -> CRS:
"""
Get UTM projection of the tile
.. code-block:: python
>>> from eoreader.reader import Reader
>>> path = r"S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE.zip"
>>> prod = Reader().open(path)
>>> prod.crs()
CRS.from_epsg(32630)
Returns:
rasterio.crs.CRS: CRS object
"""
if self._processing_baseline < 2.07:
try:
root, ns = self.read_mtd()
crs = CRS.from_string(root.findtext(".//HORIZONTAL_CS_CODE"))
except InvalidProductError:
# Manage broken XML
utm_nb = self.tile_name[1:3]
utm_letter = self.tile_name[3]
utm_hemisphere = 6 if utm_letter > "N" else 7
crs = CRS.from_string(f"epsg:32{utm_hemisphere}{utm_nb}")
else:
crs = super().crs()
return crs
[docs]
@cache
def extent(self) -> gpd.GeoDataFrame:
"""
Get UTM extent of the tile
.. code-block:: python
>>> from eoreader.reader import Reader
>>> path = r"S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE.zip"
>>> prod = Reader().open(path)
>>> prod.extent()
geometry
0 POLYGON ((309780.000 4390200.000, 309780.000 4...
Returns:
gpd.GeoDataFrame: Extent in UTM
"""
if self._processing_baseline < 2.07:
tf, width, height, crs = self.default_transform()
bounds = transform.array_bounds(height, width, tf)
return gpd.GeoDataFrame(geometry=[box(*bounds)], crs=crs)
else:
return super().extent()
[docs]
def get_datetime(self, as_datetime: bool = False) -> Union[str, datetime]:
"""
Get the product's acquisition datetime, with format :code:`YYYYMMDDTHHMMSS` <-> :code:`%Y%m%dT%H%M%S`
.. WARNING::
Sentinel-2 datetime is the datatake sensing time, not the granule sensing time!
(the one displayed in the product's name)
.. code-block:: python
>>> from eoreader.reader import Reader
>>> path = r"S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE.zip"
>>> prod = Reader().open(path)
>>> prod.get_datetime(as_datetime=True)
datetime.datetime(2020, 8, 24, 11, 6, 31)
>>> prod.get_datetime(as_datetime=False)
'20200824T110631'
Args:
as_datetime (bool): Return the date as a datetime.datetime. If false, returns a string.
Returns:
Union[str, datetime.datetime]: Its acquisition datetime
"""
if self.datetime is None:
# Sentinel-2 datetime (in the filename) is the datatake sensing time, not the granule sensing time!
sensing_time = self.split_name[2]
# Convert to datetime
date = datetime.strptime(sensing_time, "%Y%m%dT%H%M%S")
else:
date = self.datetime
if not as_datetime:
date = date.strftime(DATETIME_FMT)
return date
def _get_name_constellation_specific(self) -> str:
"""
Set product real name from metadata
Returns:
str: True name of the product (from metadata)
"""
try:
# Get MTD XML file
root, _ = self.read_datatake_mtd()
# Open identifier
name = root.findtext(".//PRODUCT_URI")
if not name:
# Manage L2Ap products
name = root.findtext(".//PRODUCT_URI_2A")
if not name:
raise InvalidProductError("PRODUCT_URI not found in metadata!")
name = path.get_filename(name)
except InvalidProductError:
try:
tile_info = files.read_json(
next(self.path.glob("**/tileInfo.json")), print_file=False
)
name = tile_info["productName"]
except (json.JSONDecodeError, StopIteration) as exc:
raise InvalidProductError(
f"Corrupted metadata and bad filename for {self.path}! "
f"Impossible to process this product."
) from exc
return name
def _get_qi_folder(self):
""""""
if self._is_sinergise:
mask_folder = "qi"
elif self.is_archived:
mask_folder = ".*GRANULE.*QI_DATA"
else:
mask_folder = "**/*GRANULE/*/QI_DATA"
return mask_folder
def _get_image_folder(self):
""""""
if self._is_sinergise:
img_folder = "."
elif self.is_archived:
img_folder = ".*GRANULE.*IMG_DATA"
else:
img_folder = "**/*GRANULE/*/IMG_DATA"
return img_folder
def _get_res_band_folder(self, band_list: list, pixel_size: float = None) -> dict:
"""
Return the folder containing the bands of a proper S2 products.
(IMG_DATA for L1C, IMG_DATA/Rx0m for L2A)
Args:
band_list (list): Wanted bands (listed as 01, 02...)
pixel_size (float): Band resolution for Sentinel-2 products {R10m, R20m, R60m}.
The wanted bands will be chosen in this proper folder.
Returns:
dict: Dictionary containing the folder path for each queried band
"""
if pixel_size is not None and types.is_iterable(pixel_size):
pixel_size = pixel_size[0]
# Open the band directory names
s2_bands_folder = {}
# Manage L2A
band_dir = BAND_DIR_NAMES[self.product_type]
for band in band_list:
if is_s2_l2a_specific_band(band):
band_id = band.name
else:
band_id = self.bands[band].id
if band_id is None:
raise InvalidProductError(
f"Non existing band ({band.name}) for S2-{self.product_type.name} products"
)
# If L2A products, we care about the resolution
if self.product_type == S2ProductType.L2A:
# If we got a true S2 resolution, open the corresponding band
if pixel_size and f"R{int(pixel_size)}m" in band_dir[band_id]:
dir_name = f"R{int(pixel_size)}m"
# Else open the first one, it will be resampled when the band will be read
else:
dir_name = band_dir[band_id][0]
# If L1C, we do not
else:
dir_name = band_dir
if self.is_archived:
# Get the band folder (use dirname is the first of the list is a band)
band_path = os.path.dirname(
self._get_archived_rio_path(
f"{self._get_image_folder()}.*{dir_name}"
)
)
# Workaround for a bug involving some bad archives
if band_path.startswith("/"):
band_path = band_path[1:]
# Workaround for PEPS Sentinel-2 archives with incomplete manifest (without any directory)
if band_path.endswith(".jp2"):
band_path = os.path.dirname(band_path)
else:
band_path = os.path.basename(band_path)
s2_bands_folder[band] = band_path
else:
# Search for the name of the folder into the S2 products
try:
s2_bands_folder[band] = next(
self.path.glob(f"{self._get_image_folder()}/{dir_name}")
)
except (IndexError, StopIteration):
s2_bands_folder[band] = self.path
for band in band_list:
if band not in s2_bands_folder:
raise InvalidProductError(
f"Band folder for band {band.value} not found in {self.path}"
)
return s2_bands_folder
[docs]
def get_band_paths(
self, band_list: list, pixel_size: float = None, **kwargs
) -> dict:
"""
Return the paths of required bands.
.. code-block:: python
>>> from eoreader.reader import Reader
>>> from eoreader.bands import *
>>> path = r"S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE.zip"
>>> prod = Reader().open(path)
>>> prod.get_band_paths([GREEN, RED])
{
<SpectralBandNames.GREEN: 'GREEN'>: 'zip+file://S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE.zip!/S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE/GRANULE/L1C_T30TTK_A027018_20200824T111345/IMG_DATA/T30TTK_20200824T110631_B03.jp2',
<SpectralBandNames.RED: 'RED'>: 'zip+file://S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE.zip!/S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE/GRANULE/L1C_T30TTK_A027018_20200824T111345/IMG_DATA/T30TTK_20200824T110631_B04.jp2'
}
Args:
band_list (list): List of the wanted bands
pixel_size (float): Band pixel size
kwargs: Other arguments used to load bands
Returns:
dict: Dictionary containing the path of each queried band
"""
band_folders = self._get_res_band_folder(band_list, pixel_size)
band_paths = {}
for band in band_list:
# Get clean band path
clean_band = self.get_band_path(band, pixel_size=pixel_size, **kwargs)
if clean_band.is_file():
band_paths[band] = clean_band
else:
if is_s2_l2a_specific_band(band):
band_id = band.name
else:
band_id = f"B{self.bands[band].id}"
try:
if self.is_archived:
band_paths[band] = self._get_archived_rio_path(
f".*{band_folders[band]}.*{band_id}.*.jp2",
)
else:
band_paths[band] = path.get_file_in_dir(
band_folders[band],
f"{band_id}",
extension="jp2",
)
except (FileNotFoundError, IndexError) as ex:
raise InvalidProductError(
f"Non existing {band} ({band_id}) band for {self.path}"
) from ex
return band_paths
def _read_band(
self,
band_path: AnyPathStrType,
band: BandNames = None,
pixel_size: Union[tuple, list, float] = None,
size: Union[list, tuple] = None,
**kwargs,
) -> xr.DataArray:
"""
Read band from disk.
.. WARNING::
Invalid pixels are not managed here
Args:
band_path (AnyPathType): Band path
band (BandNames): Band to read
pixel_size (Union[tuple, list, float]): Size of the pixels of the wanted band, in dataset unit (X, Y)
size (Union[tuple, list]): Size of the array (width, height). Not used if pixel_size is provided.
kwargs: Other arguments used to load bands
Returns:
xr.DataArray: Band xarray
"""
geocoded_path = band_path
# For L2Ap
try:
if self._processing_baseline < 2.07 and str(band_path).endswith(".jp2"):
# Get and write geocode data if not already existing
geocoded_path = self._geocode_band(band_path)
except errors.RasterioIOError as ex:
if (
str(band_path).endswith("jp2") or str(band_path).endswith("tif")
) and band_path.exists():
raise InvalidProductError(f"Corrupted file: {band_path}") from ex
else:
raise ex
# Read band
return utils.read(
geocoded_path,
pixel_size=pixel_size,
size=size,
resampling=kwargs.pop("resampling", self.band_resampling),
**kwargs,
)
def _to_reflectance(
self,
band_arr: xr.DataArray,
band_path: AnyPathType,
band: BandNames,
**kwargs,
) -> xr.DataArray:
"""
Converts band to reflectance
Args:
band_arr (xr.DataArray): Band array to convert
band_path (AnyPathType): Band path
band (BandNames): Band to read
**kwargs: Other keywords
Returns:
xr.DataArray: Band in reflectance
"""
# Only on raw files
if str(band_path).endswith(".jp2") or (
self._processing_baseline < 2.07
and path.get_filename(band_path).startswith("T")
):
try:
# Get MTD XML file
root, _ = self.read_datatake_mtd()
# Get quantification value
quantif_prefix = (
"BOA_" if self.product_type == S2ProductType.L2A else ""
)
try:
quantif_value = float(
root.findtext(f".//{quantif_prefix}QUANTIFICATION_VALUE")
)
except TypeError as exc:
raise InvalidProductError(
f"{quantif_prefix}QUANTIFICATION_VALUE not found in datatake metadata!"
) from exc
# Get offset
offset_prefix = (
"BOA_" if self.product_type == S2ProductType.L2A else "RADIO_"
)
if self._processing_baseline < 4.0:
offset = 0.0
else:
try:
band_id = 8 if band == NARROW_NIR else int(self.bands[band].id)
offset = float(
root.findtext(
f".//{offset_prefix}ADD_OFFSET[@band_id = '{band_id}']"
)
)
except TypeError as exc:
raise InvalidProductError(
f"{offset_prefix}ADD_OFFSET not found in datatake metadata!"
) from exc
except InvalidProductError:
# If not datatake file
offset = 0.0 if self._processing_baseline < 4.0 else -1000.0
quantif_value = 10000.0
# Compute the correct radiometry of the band
band_arr = (band_arr + offset) / quantif_value
self.no_data_val[band] = (self.raw_no_data + offset) / quantif_value
return band_arr.astype(np.float32)
def _reorder_loaded_bands_like_input(
self, bands: list, bands_dict: dict, **kwargs
) -> dict:
"""
Get the band key, either with the band alone or with the band and its associated band
Args:
bands (list): Bands that needed to be loaded
bands_dict (dict): Dict with loaded bands
**kwargs: Other args
Returns:
dict: Loaded bands in the right order
"""
reordered_dict = {}
associated_bands = self._sanitized_associated_bands(
bands, kwargs.get(ASSOCIATED_BANDS)
)
for band in bands:
if associated_bands and band in associated_bands:
for associated_band in associated_bands[band]:
key = self._get_band_key(band, associated_band, **kwargs)
reordered_dict[key] = bands_dict[key]
else:
key = self._get_band_key(band, associated_band=None, **kwargs)
reordered_dict[key] = bands_dict[key]
return reordered_dict
def _has_mask(self, mask: BandNames) -> bool:
"""
Can the specified mask be loaded from this product?
.. code-block:: python
>>> from eoreader.reader import Reader
>>> from eoreader.bands import *
>>> path = r"S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE.zip"
>>> prod = Reader().open(path)
>>> prod.has_index(DETFOO)
True
Args:
mask (BandNames): Mask
Returns:
bool: True if the specified mask is provided by the current product
"""
s2_masks = [S2MaskBandNames.DETFOO]
if self._processing_baseline < 4.0:
s2_masks += [
S2MaskBandNames.TECQUA,
S2MaskBandNames.SATURA,
S2MaskBandNames.NODATA,
S2MaskBandNames.DEFECT,
]
else:
s2_masks += [
S2MaskBandNames.ANC_LOST,
S2MaskBandNames.ANC_DEG,
S2MaskBandNames.MSI_LOST,
S2MaskBandNames.MSI_DEG,
S2MaskBandNames.QT_DEFECTIVE_PIXELS,
S2MaskBandNames.QT_NODATA_PIXELS,
S2MaskBandNames.QT_PARTIALLY_CORRECTED_PIXELS,
S2MaskBandNames.QT_SATURATED_PIXELS,
S2MaskBandNames.OPAQUE,
S2MaskBandNames.CIRRUS,
S2MaskBandNames.SNOW_ICE,
]
if self.product_type == S2ProductType.L2A:
s2_masks += [S2MaskBandNames.CLDPRB, S2MaskBandNames.SNWPRB]
return mask in s2_masks
def _sanitized_associated_bands(self, bands: list, associated_bands: dict) -> dict:
"""
Sanitizes the associated bands
-> convert all inputs to BandNames
Args:
bands (list): Band wanted
associated_bands (dict): Associated bands
Returns:
dict: Sanitized associated bands
"""
sanitized_associated_bands = {}
if associated_bands:
for key, val in associated_bands.items():
if val != [None]:
# Allow giving a JP2 mask as an associated band for simplicity
is_jp2_mask = False
if self._processing_baseline >= 4.0:
with contextlib.suppress(ValueError, AttributeError):
jp2_mask = S2Jp2Masks(key)
is_jp2_mask = True
for band, mapping in MASK_MAPPING_PB_0400.items():
if mapping.mask_fname == jp2_mask:
sanitized_associated_bands[band] = to_band(val)
if not is_jp2_mask:
sanitized_associated_bands[to_band(key, as_list=False)] = (
to_band(val)
)
for band in bands:
if is_mask(band) and band not in sanitized_associated_bands:
# B00
if band in [
S2MaskBandNames.CLDPRB,
S2MaskBandNames.SNWPRB,
S2MaskBandNames.OPAQUE,
S2MaskBandNames.CIRRUS,
S2MaskBandNames.SNOW_ICE,
]:
sanitized_associated_bands[band] = [None]
else:
raise ValueError(
f"You must specify an associated spectral band to the {band.name} mask, as it is band-specific."
)
return sanitized_associated_bands
def _load_masks(
self,
bands: list,
pixel_size: float = None,
size: Union[list, tuple] = None,
**kwargs,
) -> dict:
"""
Load cloud files as xarrays. Overload to manage associated bands.
Args:
bands (list): List of the wanted bands
pixel_size (int): Band pixel size in meters
size (Union[tuple, list]): Size of the array (width, height). Not used if pixel_size is provided.
kwargs: Additional arguments
Returns:
dict: Dictionary {band_name, band_xarray}
"""
band_dict = {}
if bands:
# First, try to open the cloud band written on disk
bands_to_load = []
associated_bands_to_load = defaultdict(list)
# Sanitize associated bands
associated_bands = self._sanitized_associated_bands(
bands, kwargs.get(ASSOCIATED_BANDS)
)
# Update kwargs with sanitized associated bands
if associated_bands:
kwargs[ASSOCIATED_BANDS] = associated_bands_to_load
for band in bands:
for associated_band in associated_bands[band]:
key = self._get_band_key(band, associated_band, **kwargs)
mask_path = self.get_band_path(
key,
pixel_size,
size,
writable=False,
**kwargs,
)
if mask_path.is_file():
band_dict[key] = utils.read(mask_path)
else:
bands_to_load.append(band)
associated_bands_to_load[band].append(associated_band)
# Then load other bands that haven't been loaded before
loaded_bands = self._open_masks(
bands_to_load,
pixel_size,
size,
**kwargs,
)
# Write them on disk
for band_id, band_arr in loaded_bands.items():
mask_path = self.get_band_path(
band_id, pixel_size, size, writable=True, **kwargs
)
band_arr = utils.write_path_in_attrs(band_arr, mask_path)
utils.write(
band_arr,
mask_path,
dtype=band_arr.encoding["dtype"], # This field is mandatory
nodata=band_arr.encoding.get("_FillValue"),
)
# Merge the dict
band_dict.update(loaded_bands)
return band_dict
def _open_masks(
self,
bands: list,
pixel_size: float = None,
size: Union[list, tuple] = None,
**kwargs,
) -> dict:
"""
Open a list of mask files as xarrays.
Args:
band_arr (xr.DataArray): Band array
band (BandNames): Band name as an SpectralBandNames
kwargs: Other arguments used to load bands
Returns:
xr.DataArray: Cleaned band array
"""
# Already sanitized
associated_bands = self._sanitized_associated_bands(
bands, kwargs.get(ASSOCIATED_BANDS)
)
band_dict = {}
for band in bands:
for associated_band in associated_bands[band]:
# Create the key for the output dict
key = self._get_band_key(band, associated_band, **kwargs)
# Open mask
LOGGER.debug(f"Loading {to_str(key, as_list=False)} mask")
band_arr = self._open_mask(
band, associated_band, pixel_size, size, **kwargs
)
# Save band in output dict
band_dict[key] = band_arr
return band_dict
def _open_mask(
self,
band: BandNames,
associated_band: BandNames = None,
pixel_size: float = None,
size: Union[list, tuple] = None,
**kwargs,
) -> xr.DataArray:
"""
Open one mask files as xarrays.
Args:
bands (BandNames): Wanted mask band
associated_band (BandNames): Associated spectral band to the wanted mask,v to determine the bit ID of some masks. Using the GREEN band if not given.
pixel_size (int): Band pixel size in meters
size (Union[tuple, list]): Size of the array (width, height). Not used if pixel_size is provided.
kwargs: Additional arguments
Returns:
xr.DataArray: Mask
"""
if band in [S2MaskBandNames.CLDPRB, S2MaskBandNames.SNWPRB]:
try:
if self.is_archived:
mask_path = self._get_archived_rio_path(
f"{self._get_qi_folder()}.*MSK_{band.name}_20m.jp2"
)
else:
mask_path = path.get_file_in_dir(
self.path,
f"{self._get_qi_folder()}/MSK_{band.name}_20m.jp2",
exact_name=True,
)
except FileNotFoundError:
# For some old processing baselines
# (2.04? But not for all products... i.e. S2A_MSIL2A_20170406T105021_N0204_R051_T30SWD_20170406T105317.SAFE)
if self.is_archived:
mask_path = self._get_archived_rio_path(
f"{self._get_qi_folder()}.*_{band.name.replace('PRB', '')}_20m.jp2"
)
else:
mask_path = path.get_file_in_dir(
self.path,
f"{self._get_qi_folder()}/*_{band.name.replace('PRB', '')}_20m.jp2",
exact_name=True,
)
# Old mask proba files are not geocoded
if self._processing_baseline < 2.07:
mask_path = self._geocode_band(mask_path)
# Read mask
band_arr = utils.read(
mask_path,
pixel_size=pixel_size,
size=size,
resampling=Resampling.nearest,
as_type=np.uint8,
masked=False,
**kwargs,
)
else:
if self._processing_baseline < 4.0:
vec = self._open_mask_lt_4_0(band.name, associated_band, **kwargs)
# Rasterize vector
def_band = self._read_band(
self.get_default_band_path(),
self.get_default_band(),
pixel_size=pixel_size,
size=size,
**kwargs,
)
# Rasterize to the default band size
band_arr = self._rasterize(def_band, vec)
else:
mapping = MASK_MAPPING_PB_0400[band]
band_arr = self._open_mask_gt_4_0(
mapping.mask_fname,
associated_band,
pixel_size=pixel_size,
size=size,
indexes=mapping.band_number,
**kwargs,
)
band_name = self._get_band_key(band, associated_band, as_str=True, **kwargs)
band_arr.attrs["long_name"] = band_name
return band_arr.rename(band_name)
def _open_mask_lt_4_0(
self,
mask_id: Union[str, S2GmlMasks],
band: Union[BandNames, str] = None,
**kwargs,
) -> gpd.GeoDataFrame:
"""
Open S2 mask (GML files stored in QI_DATA/qi) as :code:`gpd.GeoDataFrame`.
Masks than can be called that way are:
- :code:`TECQUA`: Technical quality mask
- :code:`SATURA`: Saturated Pixels
- :code:`NODATA`: Pixel nodata (inside the detectors)
- :code:`DETFOO`: Detectors footprint -> used to process nodata outside the detectors
- :code:`DEFECT`: Defective pixels
- :code:`CLOUDS`, **only with :code:`00` as a band!**
.. code-block:: python
>>> from eoreader.reader import Reader
>>> from eoreader.bands import *
>>> path = r"S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE.zip"
>>> prod = Reader.open(r"S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE.zip")
>>> prod.open_mask("NODATA", GREEN)
Empty GeoDataFrame
Columns: [geometry]
Index: []
>>> prod.open_mask("SATURA", GREEN)
Empty GeoDataFrame
Columns: [geometry]
Index: []
>>> prod.open_mask("DETFOO", GREEN)
gml_id ... geometry
0 detector_footprint-B03-02-0 ... POLYGON Z ((199980.000 4500000.000 0.000, 1999...
1 detector_footprint-B03-03-1 ... POLYGON Z ((222570.000 4500000.000 0.000, 2225...
2 detector_footprint-B03-05-2 ... POLYGON Z ((273050.000 4500000.000 0.000, 2730...
3 detector_footprint-B03-07-3 ... POLYGON Z ((309770.000 4453710.000 0.000, 3097...
4 detector_footprint-B03-04-4 ... POLYGON Z ((248080.000 4500000.000 0.000, 2480...
5 detector_footprint-B03-06-5 ... POLYGON Z ((297980.000 4500000.000 0.000, 2979...
[6 rows x 3 columns]
Args:
mask_id (Union[str, S2GmlMasks]): Mask name, such as DEFECT, NODATA, SATURA...
band (Union[BandNames, str]): Band number as an SpectralBandNames or str (for clouds: 00)
Returns:
gpd.GeoDataFrame: Mask as a vector
"""
# Check inputs
mask_id = S2GmlMasks.from_value(mask_id)
if mask_id == S2GmlMasks.CLOUDS:
band = "00"
# Get QI_DATA path
band_name = self.bands[band].id if isinstance(band, BandNames) else band
tmp_dir = tempfile.TemporaryDirectory()
try:
if self.is_archived:
# Open the zip file
# WE DON'T KNOW WHY BUT DO NOT USE path.read_archived_vector HERE !!!
with zipfile.ZipFile(self.path, "r") as zip_ds:
filenames = [f.filename for f in zip_ds.filelist]
regex = re.compile(
f"{self._get_qi_folder()}.*{mask_id.value}_B{band_name}.gml"
)
mask_path = zip_ds.extract(
list(filter(regex.match, filenames))[0], tmp_dir.name
)
else:
# Get mask path
mask_path = path.get_file_in_dir(
self.path,
f"{self._get_qi_folder()}/*{mask_id.value}_B{band_name}.gml",
exact_name=True,
)
# Read vector
try:
mask = vectors.read(
mask_path,
crs=self.crs(),
**utils._prune_keywords(**kwargs),
)
except vectors.DataSourceError:
LOGGER.warning(f"Corrupted mask: {mask_path}. Returning an empty one.")
mask = gpd.GeoDataFrame(geometry=[], crs=self.crs())
except Exception as ex:
raise InvalidProductError(ex) from ex
finally:
tmp_dir.cleanup()
return mask
def _open_mask_gt_4_0(
self,
mask_id: Union[str, S2Jp2Masks],
band: Union[BandNames, str] = None,
pixel_size: float = None,
size: Union[list, tuple] = None,
**kwargs,
) -> xr.DataArray:
"""
Open S2 mask (jp2 files stored in QI_DATA) as raster.
Masks than can be called that way are:
- :code:`DETFOO`: Detectors footprint -> used to process nodata outside the detectors
- :code:`QUALIT`: TECQUA, DEFECT, NODATA, SATURA, CLOLOW merged
- :code:`CLASSI`: CLOUDS and SNOICE **only with :code:`00` as a band!**
Args:
mask_id (Union[str, S2GmlMasks]): Mask ID
band (Union[BandNames, str]): Band number as an SpectralBandNames or str (for clouds: 00)
pixel_size (int): Band pixel size in meters
size (Union[tuple, list]): Size of the array (width, height). Not used if pixel_size is provided.
Returns:
gpd.GeoDataFrame: Mask as a DataArray
"""
# Check inputs
mask_id = S2Jp2Masks.from_value(mask_id)
if mask_id == S2Jp2Masks.CLASSI:
band = "00"
# Get QI_DATA path
band_id = self.bands[band].id if isinstance(band, BandNames) else band
if self.is_archived:
mask_path = self._get_archived_rio_path(
f"{self._get_qi_folder()}.*{mask_id.value}_B{band_id}.jp2"
)
else:
# Get mask path
mask_path = path.get_file_in_dir(
self.path,
f"{self._get_qi_folder()}/*{mask_id.value}_B{band_id}.jp2",
exact_name=True,
)
# Read mask
mask = utils.read(
mask_path,
pixel_size=pixel_size,
size=size,
resampling=Resampling.nearest,
as_type=np.uint8,
masked=False,
**kwargs,
)
return mask
def _manage_invalid_pixels(
self,
band_arr: xr.DataArray,
band: BandNames,
pixel_size: float = None,
**kwargs,
) -> xr.DataArray:
"""
Manage invalid pixels (Nodata, saturated, defective...)
See there: https://sentinel.esa.int/documents/247904/349490/S2_MSI_Product_Specification.pdf
Args:
band_arr (xr.DataArray): Band array
band (BandNames): Band name as an SpectralBandNames
kwargs: Other arguments used to load bands
Returns:
xr.DataArray: Cleaned band array
"""
if self._processing_baseline < 4.0:
return self._manage_invalid_pixels_lt_4_0(band_arr, band, **kwargs)
else:
# return band_arr
return self._manage_invalid_pixels_gt_4_0(band_arr, band, **kwargs)
def _manage_nodata(
self,
band_arr: xr.DataArray,
band: BandNames,
pixel_size: float = None,
**kwargs,
) -> xr.DataArray:
"""
Manage only nodata pixels
Args:
band_arr (xr.DataArray): Band array
band (BandNames): Band name as an SpectralBandNames
kwargs: Other arguments used to load bands
Returns:
xr.DataArray: Cleaned band array
"""
if self._processing_baseline < 4.0:
return self._manage_nodata_lt_4_0(band_arr, band, pixel_size, **kwargs)
else:
return self._manage_nodata_gt_4_0(band_arr, band, pixel_size, **kwargs)
def _manage_invalid_pixels_lt_4_0(
self,
band_arr: xr.DataArray,
band: BandNames,
pixel_size: float = None,
**kwargs,
) -> xr.DataArray:
"""
Manage invalid pixels (Nodata, saturated, defective...)
See there: https://sentinel.esa.int/documents/247904/349490/S2_MSI_Product_Specification.pdf
Args:
band_arr (xr.DataArray): Band array
band (BandNames): Band name as an SpectralBandNames
kwargs: Other arguments used to load bands
Returns:
xr.DataArray: Cleaned band array
"""
# Get detector footprint to deduce the outside nodata
nodata_det = self._open_mask_lt_4_0(
S2GmlMasks.FOOTPRINT, band
) # Detector nodata -> pixels that are outside the detectors
if len(nodata_det) > 0:
# Rasterize nodata
mask = self._rasterize(
band_arr,
nodata_det,
value_inside=self._mask_false,
value_outside=self._mask_true,
)
else:
# Manage empty geometry: nodata is 0
LOGGER.warning(
"Empty detector footprint (DETFOO) vector. Nodata will be set where the pixels are null."
)
s2_nodata = 0
mask = np.where(band_arr == s2_nodata, 1, 0).astype(np.uint8)
# Load masks and merge them into the nodata
nodata_pix = self._open_mask_lt_4_0(
S2GmlMasks.NODATA, band
) # Pixel nodata, not pixels that are outside the detectors !!!
if len(nodata_pix) > 0:
# Discard pixels corrected during crosstalk
nodata_pix = nodata_pix[nodata_pix.gml_id == "QT_NODATA_PIXELS"]
nodata_pix = pd.concat(
[nodata_pix, self._open_mask_lt_4_0(S2GmlMasks.DEFECT, band)]
)
nodata_pix = pd.concat(
[nodata_pix, self._open_mask_lt_4_0(S2GmlMasks.SATURATION, band)]
)
# Technical quality mask
tecqua = self._open_mask_lt_4_0(S2GmlMasks.QUALITY, band)
if len(tecqua) > 0:
# Do not take into account ancillary data
tecqua = tecqua[tecqua.gml_id.isin(["MSI_LOST", "MSI_DEG"])]
nodata_pix = pd.concat([nodata_pix, tecqua])
if len(nodata_pix) > 0:
# Rasterize mask
mask_pix = self._rasterize(band_arr, nodata_pix)
mask = mask | mask_pix
return self._set_nodata_mask(band_arr, mask)
def _manage_invalid_pixels_gt_4_0(
self,
band_arr: xr.DataArray,
band: BandNames,
pixel_size: float = None,
**kwargs,
) -> xr.DataArray:
"""
Manage invalid pixels (Nodata, saturated, defective...)
See there:
https://sentinels.copernicus.eu/documents/247904/685211/Sentinel-2-Products-Specification-Document-14_8.pdf
Args:
band_arr (xr.DataArray): Band array
band (BandNames): Band name as an SpectralBandNames
kwargs: Other arguments used to load bands
Returns:
xr.DataArray: Cleaned band array
"""
# Get detector footprint to deduce the outside nodata
nodata = self._open_mask_gt_4_0(
S2Jp2Masks.DETFOO,
band,
pixel_size=pixel_size,
size=(band_arr.rio.width, band_arr.rio.height),
**kwargs,
).data
nodata = np.where(nodata == 0, 1, 0).astype(np.uint8)
# Manage quality mask
# TODO: Optimize it -> very slow (why?)
# Technical quality mask: Only keep MSI_LOST (band 3) and MSI_DEG (band 4)
# Defective pixels (band 5)
# Nodata pixels (band 6)
# Saturated pixels (band 8)
quality = self._open_mask_gt_4_0(
S2Jp2Masks.QUALIT,
band,
pixel_size=pixel_size,
size=(band_arr.rio.width, band_arr.rio.height),
indexes=[3, 4, 5, 6, 8],
**kwargs,
).data
# Compute mask
mask = (nodata + np.sum(quality, axis=0)) > 0
return self._set_nodata_mask(band_arr, mask)
def _manage_nodata_lt_4_0(
self,
band_arr: xr.DataArray,
band: BandNames,
pixel_size: float = None,
**kwargs,
) -> xr.DataArray:
"""
Manage only nodata
See there: https://sentinel.esa.int/documents/247904/349490/S2_MSI_Product_Specification.pdf
Args:
band_arr (xr.DataArray): Band array
band (BandNames): Band name as an SpectralBandNames
kwargs: Other arguments used to load bands
Returns:
xr.DataArray: Cleaned band array
"""
# Get detector footprint to deduce the outside nodata
nodata_det = self._open_mask_lt_4_0(
S2GmlMasks.FOOTPRINT, band
) # Detector nodata, -> pixels that are outside the detectors
if len(nodata_det) > 0:
# Rasterize nodata
mask = self._rasterize(
band_arr,
nodata_det,
value_inside=self._mask_false,
value_outside=self._mask_true,
)
else:
# Manage empty geometry: nodata is 0
LOGGER.warning(
"Empty detector footprint (DETFOO) vector. Nodata will be set where the pixels are null."
)
s2_nodata = 0
mask = xr.where(band_arr == s2_nodata, 1, 0).astype(np.uint8)
return self._set_nodata_mask(band_arr, mask)
def _manage_nodata_gt_4_0(
self,
band_arr: xr.DataArray,
band: BandNames,
pixel_size: float = None,
**kwargs,
) -> xr.DataArray:
"""
Manage only nodata
See there: https://sentinel.esa.int/documents/247904/349490/S2_MSI_Product_Specification.pdf
Args:
band_arr (xr.DataArray): Band array
band (BandNames): Band name as an SpectralBandNames
kwargs: Other arguments used to load bands
Returns:
xr.DataArray: Cleaned band array
"""
# Get detector footprint to deduce the outside nodata
nodata = self._open_mask_gt_4_0(
S2Jp2Masks.DETFOO,
band,
pixel_size=pixel_size,
size=(band_arr.rio.width, band_arr.rio.height),
**kwargs,
).data
nodata = np.where(nodata == 0, 1, 0).astype(np.uint8)
return self._set_nodata_mask(band_arr, nodata)
def _load_bands(
self,
bands: list,
pixel_size: float = None,
size: Union[list, tuple] = None,
**kwargs,
) -> dict:
"""
Load bands as numpy arrays with the same pixel size (and same metadata).
Args:
bands (list): List of the wanted bands
pixel_size (float): Band pixel size in meters
size (Union[tuple, list]): Size of the array (width, height). Not used if pixel_size is provided.
kwargs: Other arguments used to load bands
Returns:
dict: Dictionary {band_name, band_xarray}
"""
# Return empty if no band is specified
if not bands:
return {}
band_paths = self.get_band_paths(bands, pixel_size=pixel_size, **kwargs)
# Open bands and get array (resampled if needed)
band_arrays = self._open_bands(
band_paths, pixel_size=pixel_size, size=size, **kwargs
)
return band_arrays
def _has_s2_l2a_bands(self, band: BandNames) -> bool:
"""
Can the specified mask be loaded from this product?
.. code-block:: python
>>> from eoreader.reader import Reader
>>> from eoreader.bands import *
>>> path = r"S2A_MSIL2A_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE.zip"
>>> prod = Reader().open(path)
>>> prod.has_index(SCL)
True
Args:
mask (BandNames): Mask
Returns:
bool: True if the specified mask is provided by the current product
"""
return self.product_type == S2ProductType.L2A
def _load_s2_l2a_bands(
self,
bands: list,
pixel_size: float = None,
size: Union[list, tuple] = None,
**kwargs,
) -> dict:
"""
Load Sentinel-2 L2A band files as xarrays.
Args:
bands (list): List of the wanted bands
pixel_size (int): Band pixel size in meters
size (Union[tuple, list]): Size of the array (width, height). Not used if pixel_size is provided.
kwargs: Additional arguments
Returns:
dict: Dictionary {band_name, band_xarray}
"""
band_dict = {}
if bands:
# First, try to open the cloud band written on disk
bands_to_load = []
for band in bands:
s2_l2a_path = self.get_band_path(
band, pixel_size, size, writable=False, **kwargs
)
if s2_l2a_path.is_file():
band_dict[band] = utils.read(s2_l2a_path)
else:
bands_to_load.append(band)
# Then load other bands that haven't been loaded before
loaded_bands = {}
for band, band_path in self.get_band_paths(bands_to_load).items():
# SCL is a uint8 classified band
if band == SCL:
band_arr = utils.read(
band_path,
pixel_size=pixel_size,
size=size,
resampling=Resampling.nearest,
as_type=np.uint8,
masked=False,
**kwargs,
)
# WVP and AOT are classif float32 bands
elif band in [WVP, AOT]:
band_arr = self._read_band(
band_path, band, pixel_size=pixel_size, size=size, **kwargs
)
if str(band_path).endswith(".jp2"):
try:
# Get MTD XML file
root, _ = self.read_datatake_mtd()
# Get quantification value
quantif_prefix = band.name
try:
quantif_value = float(
root.findtext(
f".//{quantif_prefix}QUANTIFICATION_VALUE"
)
)
except TypeError as exc:
raise InvalidProductError(
f"{quantif_prefix}QUANTIFICATION_VALUE not found in datatake metadata!"
) from exc
except InvalidProductError:
quantif_value = 1000.0
# Compute the correct radiometry of the band
band_arr = (band_arr / quantif_value).astype(np.float32)
else:
raise NotImplementedError
loaded_bands[band] = band_arr
# Write them on disk
for band_id, band_arr in loaded_bands.items():
s2_l2a_path = self.get_band_path(
band_id, pixel_size, size, writable=True, **kwargs
)
band_arr = utils.write_path_in_attrs(band_arr, s2_l2a_path)
utils.write(band_arr, s2_l2a_path)
# Merge the dict
band_dict.update(loaded_bands)
return band_dict
def _get_condensed_name(self) -> str:
"""
Get S2 products condensed name ({date}_S2_{tile}_{product_type}_{generation_time}).
Returns:
str: Condensed name
"""
# Used to make the difference between 2 products acquired on the same tile at the same date but cut differently
# Sentinel-2 generation time: "%Y%m%dT%H%M%S" -> save only %H%M%S
gen_time = self.split_name[-1].split("T")[-1]
# Force S2 as constellation name for S2_SIN to work
return f"{self.get_datetime()}_S2_{self.tile_name}_{self.product_type.name}_{gen_time}"
[docs]
@cache
def get_mean_sun_angles(self) -> (float, float):
"""
Get Mean Sun angles (Azimuth and Zenith angles)
.. code-block:: python
>>> from eoreader.reader import Reader
>>> path = r"S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE.zip"
>>> prod = Reader().open(path)
>>> prod.get_mean_sun_angles()
(149.148155074489, 32.6627897525474)
Returns:
(float, float): Mean Azimuth and Zenith angle
"""
try:
# Read metadata
root, _ = self.read_mtd()
try:
mean_sun_angles = root.find(".//Mean_Sun_Angle")
zenith_angle = float(mean_sun_angles.findtext("ZENITH_ANGLE"))
azimuth_angle = float(mean_sun_angles.findtext("AZIMUTH_ANGLE"))
except TypeError as exc:
raise InvalidProductError(
"Azimuth or Zenith angles not found in metadata!"
) from exc
except InvalidProductError as exc:
LOGGER.warning(f"{exc}: setting sun angles to (0, 0).")
azimuth_angle = 0.0
zenith_angle = 0.0
return azimuth_angle, zenith_angle
@cache
def _read_mtd(self) -> (etree._Element, dict):
"""
Read metadata and outputs the metadata XML root and its namespaces as a dict
.. code-block:: python
>>> from eoreader.reader import Reader
>>> path = r"S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE.zip"
>>> prod = Reader().open(path)
>>> prod.read_mtd()
(<Element {https://psd-14.sentinel2.eo.esa.int/PSD/S2_PDI_Level-2A_Tile_Metadata.xsd}Level-2A_Tile_ID at ...>,
{'nl': '{https://psd-14.sentinel2.eo.esa.int/PSD/S2_PDI_Level-2A_Tile_Metadata.xsd}'})
Returns:
(etree._Element, dict): Metadata XML root and its namespaces
"""
if self._is_sinergise:
mtd_from_path = "metadata.xml"
mtd_archived = r"metadata\.xml"
else:
mtd_from_path = "GRANULE/*/MTD*.xml"
mtd_archived = r"GRANULE.*MTD.*\.xml"
return self._read_mtd_xml(mtd_from_path, mtd_archived)
[docs]
@cache
def read_datatake_mtd(self) -> (etree._Element, dict):
"""
Read datatake metadata and outputs the metadata XML root and its namespaces as a dict
(datatake metadata is the file in the root directory named :code:`MTD_MSI(L1C/L2A).xml`)
.. code-block:: python
>>> from eoreader.reader import Reader
>>> path = r"S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE.zip"
>>> prod = Reader().open(path)
>>> prod.read_mtd()
(<Element {https://psd-14.sentinel2.eo.esa.int/PSD/S2_PDI_Level-2A_Tile_Metadata.xsd}Level-2A_Tile_ID at ...>,
{'nl': '{https://psd-14.sentinel2.eo.esa.int/PSD/S2_PDI_Level-2A_Tile_Metadata.xsd}'})
Returns:
(etree._Element, dict): Metadata XML root and its namespaces
"""
mtd_from_path = "MTD_MSI*.xml"
mtd_archived = r"MTD_MSI.*\.xml"
return self._read_mtd_xml(mtd_from_path, mtd_archived)
def _has_cloud_band(self, band: BandNames) -> bool:
"""
Does this product has the specified cloud band?
https://sentinels.copernicus.eu/web/sentinel/technical-guides/sentinel-2-msi/level-1c/cloud-masks
"""
return band != SHADOWS
def _open_clouds_lt_4_0(
self,
bands: list,
pixel_size: float = None,
size: Union[list, tuple] = None,
**kwargs,
) -> dict:
"""
Load cloud files as xarrays.
Read S2 cloud mask .GML files (both valid for L2A and L1C products).
https://sentinels.copernicus.eu/web/sentinel/technical-guides/sentinel-2-msi/level-1c/cloud-masks
Args:
bands (list): List of the wanted bands
pixel_size (int): Band pixel size in meters
size (Union[tuple, list]): Size of the array (width, height). Not used if pixel_size is provided.
kwargs: Additional arguments
Returns:
dict: Dictionary {band_name, band_xarray}
"""
band_dict = {}
if bands:
cloud_vec = self._open_mask_lt_4_0(S2GmlMasks.CLOUDS)
# Open a bands to mask it
def_band = self._read_band(
self.get_default_band_path(),
self.get_default_band(),
pixel_size=pixel_size,
size=size,
**kwargs,
)
nodata = np.where(np.isnan(def_band), 1, 0)
for band in bands:
if band == ALL_CLOUDS:
cloud = self._rasterize(def_band, cloud_vec, nodata)
elif band == CIRRUS:
try:
cirrus = cloud_vec[cloud_vec.maskType == "CIRRUS"]
except AttributeError:
# No masktype -> empty
cirrus = gpd.GeoDataFrame(geometry=[], crs=cloud_vec.crs)
cloud = self._rasterize(def_band, cirrus, nodata)
elif band == CLOUDS:
try:
clouds = cloud_vec[cloud_vec.maskType == "OPAQUE"]
except AttributeError:
# No masktype -> empty
clouds = gpd.GeoDataFrame(geometry=[], crs=cloud_vec.crs)
cloud = self._rasterize(def_band, clouds, nodata)
elif band == RAW_CLOUDS:
cloud = self._rasterize(def_band, cloud_vec, nodata)
else:
raise InvalidTypeError(
f"Non existing cloud band for Sentinel-2: {band}"
)
# Rename
band_name = to_str(band)[0]
# Multi bands -> do not change long name
if band != RAW_CLOUDS:
cloud.attrs["long_name"] = band_name
band_dict[band] = cloud.rename(band_name).astype(np.float32)
return band_dict
def _open_clouds_gt_4_0(
self,
bands: list,
pixel_size: float = None,
size: Union[list, tuple] = None,
**kwargs,
) -> dict:
"""
Load cloud files as xarrays.
Read S2 cloud mask .JP2 files (both valid for L2A and L1C products).
https://sentinels.copernicus.eu/documents/247904/685211/Sentinel-2-Products-Specification-Document-14_8.pdf
Args:
bands (list): List of the wanted bands
pixel_size (int): Band pixel size in meters
size (Union[tuple, list]): Size of the array (width, height). Not used if pixel_size is provided.
kwargs: Additional arguments
Returns:
dict: Dictionary {band_name, band_xarray}
"""
band_dict = {}
if bands:
cloud_arr = self._open_mask_gt_4_0(
S2Jp2Masks.CLASSI,
"00",
pixel_size=pixel_size,
size=size,
**kwargs,
)
for band in bands:
if band == ALL_CLOUDS:
cloud = cloud_arr[0, :, :] | cloud_arr[1, :, :]
elif band == CIRRUS:
cloud = cloud_arr[1, :, :] # CIRRUS = band 2
elif band == CLOUDS:
cloud = cloud_arr[0, :, :] # OPAQUE = band 1
elif band == RAW_CLOUDS:
cloud = cloud_arr
else:
raise InvalidTypeError(
f"Non existing cloud band for Sentinel-2: {band}"
)
if len(cloud.shape) == 2:
cloud = cloud.expand_dims(dim="band", axis=0)
# Rename
band_name = to_str(band)[0]
# Multi bands -> do not change long name
if band != RAW_CLOUDS:
cloud.attrs["long_name"] = band_name
band_dict[band] = cloud.rename(band_name).astype(np.float32)
return band_dict
def _open_clouds_l2a(
self,
bands: list,
pixel_size: float = None,
size: Union[list, tuple] = None,
**kwargs,
):
"""
Load cloud files as xarrays.
Read S2 MSK_CLDPRB_20m .JP2 file, only for L2A products.
CLOUDS and ALL_CLOUDS corresponds to a threshold at 66% of this mask, when CIRRUS is loaded with the above functions.
Args:
bands (list): List of the wanted bands
pixel_size (int): Band pixel size in meters
size (Union[tuple, list]): Size of the array (width, height). Not used if pixel_size is provided.
kwargs: Additional arguments
Returns:
dict: Dictionary {band_name, band_xarray}
"""
band_dict = {}
if bands:
# Read mask
cloud_arr = self._load_masks(
[S2MaskBandNames.CLDPRB],
pixel_size=pixel_size,
size=size,
**kwargs,
)[S2MaskBandNames.CLDPRB]
# Threshold the probability array -> Cloud > 66%
# Do the same classification as Landsat
# https://www.usgs.gov/landsat-missions/landsat-collection-1-level-1-quality-assessment-band
# 01 = “Low” = Algorithm has low to no confidence that this condition exists (0-33 percent confidence)
# 10 = “Medium” = Algorithm has medium confidence that this condition exists (34-66 percent confidence)
# 11 = “High” = Algorithm has high confidence that this condition exists (67-100 percent confidence
cloud_arr_thresh = xr.where(
cloud_arr > 66, self._mask_true, self._mask_false
)
# Set nodata
cloud_arr_thresh = self._manage_nodata(
cloud_arr_thresh, self.get_default_band()
)
for band in bands:
if band in [ALL_CLOUDS, CLOUDS]:
cloud = cloud_arr_thresh
elif band == CIRRUS:
# Cannot extract CIRRUS from this mask (keep the old way)
if self._processing_baseline < 4.0:
cloud = self._open_clouds_lt_4_0(
[CIRRUS], pixel_size, size, **kwargs
)[CIRRUS]
else:
cloud = self._open_clouds_gt_4_0(
[CIRRUS], pixel_size, size, **kwargs
)[CIRRUS]
elif band == RAW_CLOUDS:
cloud = cloud_arr
else:
raise InvalidTypeError(
f"Non existing cloud band for Sentinel-2: {band}"
)
if len(cloud.shape) == 2:
cloud = cloud.expand_dims(dim="band", axis=0)
# Rename
band_name = to_str(band)[0]
# Multi bands -> do not change long name
if band != RAW_CLOUDS:
cloud.attrs["long_name"] = band_name
band_dict[band] = cloud.rename(band_name).astype(np.float32)
return band_dict
def _open_clouds(
self,
bands: list,
pixel_size: float = None,
size: Union[list, tuple] = None,
**kwargs,
) -> dict:
"""
Load cloud files as xarrays.
L2A data (except for CIRRUS):
Read S2 MSK_CLDPRB_20m .JP2 file
L1C data with baseline > 4.0
Read S2 cloud mask .JP2 files (both valid for L2A and L1C products).
L1C data with baseline < 4.0
Read S2 cloud mask .GML files (both valid for L2A and L1C products).
https://sentinels.copernicus.eu/web/sentinel/technical-guides/sentinel-2-msi/level-1c/cloud-masks
Args:
bands (list): List of the wanted bands
pixel_size (int): Band pixel size in meters
size (Union[tuple, list]): Size of the array (width, height). Not used if pixel_size is provided.
kwargs: Additional arguments
Returns:
dict: Dictionary {band_name, band_xarray}
"""
if self.product_type == S2ProductType.L2A:
clouds = self._open_clouds_l2a(bands, pixel_size, size, **kwargs)
else:
if self._processing_baseline < 4.0:
clouds = self._open_clouds_lt_4_0(bands, pixel_size, size, **kwargs)
else:
clouds = self._open_clouds_gt_4_0(bands, pixel_size, size, **kwargs)
return clouds
def _rasterize(
self,
xds: xr.DataArray,
geometry: gpd.GeoDataFrame,
nodata: np.ndarray = None,
value_outside: float = None,
value_inside: float = None,
) -> xr.DataArray:
"""
Rasterize a vector on a memory dataset
Args:
xds (xr.DataArray): Array
geometry (gpd.GeoDataFrame): Geometry to rasterize
nodata (np.ndarray): Nodata mask
Returns:
xr.DataArray: Rasterized vector
"""
if value_outside is None:
value_outside = self._mask_false
if value_inside is None:
value_inside = self._mask_true
if not geometry.empty:
# Just in case
if geometry.crs != xds.rio.crs:
geometry = geometry.to_crs(xds.rio.crs)
# Rasterize mask
cond = features.rasterize(
geometry.geometry,
out_shape=(xds.rio.height, xds.rio.width),
fill=value_outside, # Pixels outside mask
default_value=value_inside, # Pixels inside mask
transform=transform.from_bounds(
*xds.rio.bounds(), xds.rio.width, xds.rio.height
),
dtype=np.uint8,
)
cond = np.expand_dims(cond, axis=0)
else:
# If empty geometry, just
cond = np.full(
shape=(xds.rio.count, xds.rio.height, xds.rio.width),
fill_value=value_outside,
dtype=np.uint8,
)
return self._create_mask(xds, cond, nodata)
def _geocode_band(self, band_path: AnyPathType) -> AnyPathType:
"""
Geocode a band, used for old L2Ap products (bands or old cloud probability masks).
Args:
band_path (AnyPathType): Band path to be geocoded
Returns:
AnyPathType: Geocoded band
"""
geocoded_path = band_path
with rasterio.open(str(band_path), "r") as ds:
if not ds.crs:
# Download path just in case
on_disk_path = self._get_band_folder(writable=True) / band_path.name
if not on_disk_path.is_file():
if path.is_cloud_path(band_path):
geocoded_path = band_path.download_to(
self._get_band_folder(writable=True)
)
else:
geocoded_path = files.copy(
band_path, self._get_band_folder(writable=True)
)
else:
geocoded_path = on_disk_path
# Get and write geocode data if not already existing
try:
with rasterio.open(str(geocoded_path), "r+") as out_ds:
tf, _, _, crs = self._get_geocoding_info(band_path)
out_ds.crs = crs
out_ds.transform = tf
except SystemError:
# Workaround for jp2 file that for a reason or another fails to be updated
# Maybe linked to https://github.com/rasterio/rasterio/issues/2528?
jp2_geocoded_path = geocoded_path
geocoded_path = jp2_geocoded_path.with_suffix(".tif")
with rasterio.open(str(jp2_geocoded_path), "r") as jp2_ds:
tif_meta = jp2_ds.meta
tif_meta["driver"] = "GTiff"
with rasterio.open(
str(geocoded_path), "w", **tif_meta
) as out_ds:
out_ds.write(jp2_ds.read())
tf, _, _, crs = self._get_geocoding_info(band_path)
out_ds.crs = crs
out_ds.transform = tf
return geocoded_path
def _get_geocoding_info(
self, band_path: AnyPathType = None
) -> (Affine, int, int, CRS):
"""
Get geocoding information, used for:
- old L2Ap products (bands or old cloud probability masks)
- rasterizing masks for PB < 04.00
Args:
band_path (AnyPathType): Band path to be geocoded
Returns:
(Affine, int, int, CRS): Transform, width, height and CRS of the band
"""
try:
if band_path is None:
resolution = int(self.pixel_size)
else:
if isinstance(band_path, str):
band_path = AnyPath(band_path)
# Read metadata
root, ns = self.read_mtd()
# Determine wanted resolution
if "10m" in band_path.name:
resolution = 10
elif "20m" in band_path.name:
resolution = 20
else:
resolution = 60
# Open size
width = int(root.findtext(f".//Size[@resolution='{resolution}']/NCOLS"))
height = int(root.findtext(f".//Size[@resolution='{resolution}']/NROWS"))
# Open upper-left corner
ulx = float(
root.findtext(f".//Geoposition[@resolution='{resolution}']/ULX")
)
uly = float(
root.findtext(f".//Geoposition[@resolution='{resolution}']/ULY")
)
# Create transform
tf = transform.from_origin(ulx, uly, resolution, resolution)
except InvalidProductError as exc:
raise InvalidProductError("Cannot geocode any band!") from exc
return tf, width, height, self.crs()
[docs]
@cache
def get_cloud_cover(self) -> float:
"""
Get cloud cover as given in the metadata
.. code-block:: python
>>> from eoreader.reader import Reader
>>> path = r"S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE.zip"
>>> prod = Reader().open(path)
>>> prod.get_cloud_cover()
55.5
Returns:
float: Cloud cover as given in the metadata
"""
# Get the cloud cover
try:
# Get MTD XML file
root, nsmap = self.read_mtd()
cc = float(root.findtext(".//CLOUDY_PIXEL_PERCENTAGE"))
except (InvalidProductError, TypeError):
LOGGER.warning(
"'CLOUDY_PIXEL_PERCENTAGE' not found in metadata! Cloud coverage set to 0."
)
cc = 0
return cc
[docs]
def get_quicklook_path(self) -> str:
"""
Get quicklook path if existing (some providers are providing one quicklook, such as creodias)
Returns:
str: Quicklook path
"""
quicklook_path = None
try:
if self.is_archived:
quicklook_path = self.path / self._get_archived_path(regex=r".*ql\.jpg")
else:
quicklook_path = next(self.path.glob("**/*ql.jpg"))
except (StopIteration, FileNotFoundError):
try:
if self.is_archived:
quicklook_path = self.path / self._get_archived_path(
regex=r".*preview\.jpg"
)
else:
quicklook_path = next(self.path.glob("**/preview.jpg"))
except (StopIteration, FileNotFoundError):
# Use the PVI
try:
if self.is_archived:
quicklook_path = self._get_archived_rio_path(
regex=r".*PVI\.jp2"
)
else:
quicklook_path = next(self.path.glob("**/*PVI.jp2"))
except (StopIteration, FileNotFoundError):
LOGGER.warning(f"No quicklook found in {self.condensed_name}")
if quicklook_path is not None:
quicklook_path = str(quicklook_path)
return quicklook_path
[docs]
@cache
def get_orbit_direction(self) -> OrbitDirection:
"""
Get cloud cover as given in the metadata
.. code-block:: python
>>> from eoreader.reader import Reader
>>> path = r"S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE.zip"
>>> prod = Reader().open(path)
>>> prod.get_orbit_direction().value
"DESCENDING"
Returns:
OrbitDirection: Orbit direction (ASCENDING/DESCENDING)
"""
try:
# Get MTD XML file
root, _ = self.read_datatake_mtd()
# Get the orbit direction
try:
od = OrbitDirection.from_value(
root.findtext(".//SENSING_ORBIT_DIRECTION")
)
except TypeError as exc:
raise InvalidProductError(
"SENSING_ORBIT_DIRECTION not found in metadata!"
) from exc
except InvalidProductError:
od = OrbitDirection.DESCENDING
return od
[docs]
class S2StacProduct(StacProduct, S2Product):
[docs]
def __init__(
self,
product_path: AnyPathStrType = None,
archive_path: AnyPathStrType = None,
output_path: AnyPathStrType = None,
remove_tmp: bool = False,
**kwargs,
) -> None:
self.kwargs = kwargs
"""Custom kwargs"""
# Copy the kwargs
super_kwargs = kwargs.copy()
# Get STAC Item
self.item = self._set_item(product_path, **super_kwargs)
""" STAC Item of the product """
if not self._is_mpc():
self.default_clients = [
self.get_e84_client(),
self.get_sinergise_client(),
# Not yet handled
# HttpClient(ClientSession(base_url="https://landsatlook.usgs.gov", auth=BasicAuth(login="", password="")))
]
self.clients = super_kwargs.pop("client", self.default_clients)
if product_path is None:
# Canonical link is always the second one
# TODO: check if ok
product_path = AnyPath(self.item.links[1].target).parent
# Initialization from the super class
super().__init__(product_path, archive_path, output_path, remove_tmp, **kwargs)
def _pre_init(self, **kwargs) -> None:
"""
Function used to pre_init the products
(setting needs_extraction and so on)
"""
self._raw_units = RawUnits.REFL
self._has_cloud_cover = True
self._use_filename = False
self.needs_extraction = False
# Pre init done by the super class
super(S2Product, self)._pre_init(**kwargs)
def _get_path(self, file_id: str, ext="tif") -> str:
"""
Get either the archived path of the normal path of a tif file
Args:
band_id (str): Band ID
Returns:
AnyPathType: band path
"""
if file_id.lower() in self.item.assets:
asset_name = file_id.lower()
elif file_id in [band.id for band in self.bands.values() if band is not None]:
band_name = [
band_name
for band_name, band in self.bands.items()
if band is not None and f"{band.id}" == file_id
][0]
asset_name = EOREADER_STAC_MAP[band_name].value
else:
try:
asset_name = difflib.get_close_matches(
file_id, self.item.assets.keys(), cutoff=0.5, n=1
)[0]
except Exception as exc:
raise FileNotFoundError(
f"Impossible to find an asset in {list(self.item.assets.keys())} close enough to '{file_id}'"
) from exc
return self.sign_url(self.item.assets[asset_name].href)
[docs]
def get_band_paths(
self, band_list: list, pixel_size: float = None, **kwargs
) -> dict:
"""
Return the paths of required bands.
.. code-block:: python
>>> from eoreader.reader import Reader
>>> from eoreader.bands import *
>>> path = r"S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE.zip"
>>> prod = Reader().open(path)
>>> prod.get_band_paths([GREEN, RED])
{
<SpectralBandNames.GREEN: 'GREEN'>: 'zip+file://S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE.zip!/S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE/GRANULE/L1C_T30TTK_A027018_20200824T111345/IMG_DATA/T30TTK_20200824T110631_B03.jp2',
<SpectralBandNames.RED: 'RED'>: 'zip+file://S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE.zip!/S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE/GRANULE/L1C_T30TTK_A027018_20200824T111345/IMG_DATA/T30TTK_20200824T110631_B04.jp2'
}
Args:
band_list (list): List of the wanted bands
pixel_size (float): Band pixel size
kwargs: Other arguments used to load bands
Returns:
dict: Dictionary containing the path of each queried band
"""
band_paths = {}
for band in band_list:
# Get clean band path
clean_band = self.get_band_path(band, pixel_size=pixel_size, **kwargs)
if clean_band.is_file():
band_paths[band] = clean_band
else:
if is_s2_l2a_specific_band(band):
band_id = band.name
else:
band_id = self.bands[band].id
try:
band_paths[band] = self._get_path(band_id)
except (FileNotFoundError, IndexError) as ex:
raise InvalidProductError(
f"Non existing {band} ({band_id}) band for {self.path}"
) from ex
return band_paths
[docs]
@cache
def read_datatake_mtd(self) -> (etree._Element, dict):
"""
Read datatake metadata and outputs the metadata XML root and its namespaces as a dict
(datatake metadata is the file in the root directory named :code:`MTD_MSI(L1C/L2A).xml`)
.. code-block:: python
>>> from eoreader.reader import Reader
>>> path = r"S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE.zip"
>>> prod = Reader().open(path)
>>> prod.read_mtd()
(<Element {https://psd-14.sentinel2.eo.esa.int/PSD/S2_PDI_Level-2A_Tile_Metadata.xsd}Level-2A_Tile_ID at ...>,
{'nl': '{https://psd-14.sentinel2.eo.esa.int/PSD/S2_PDI_Level-2A_Tile_Metadata.xsd}'})
Returns:
(etree._Element, dict): Metadata XML root and its namespaces
"""
return self._read_mtd_xml_stac(self._get_path("product-metadata"))
@cache
def _read_mtd(self) -> (etree._Element, dict):
"""
Read Landsat metadata as:
- :code:`pandas.DataFrame` whatever its collection is (by default for collection 1)
- XML root + its namespace if the product is retrieved from the 2nd collection (by default for collection 2)
Args:
force_pd (bool): If collection 2, return a pandas.DataFrame instead of an XML root + namespace
Returns:
Tuple[Union[pd.DataFrame, etree._Element], dict]:
Metadata as a Pandas.DataFrame or as (etree._Element, dict): Metadata XML root and its namespaces
"""
return self._read_mtd_xml_stac(self._get_path("granule-metadata"))
[docs]
def get_quicklook_path(self) -> str:
"""
Get quicklook path if existing.
Returns:
str: Quicklook path
"""
return self._get_path("preview")
