# -*- coding: utf-8 -*-
# Copyright 2024, 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 difflib
import json
import logging
import os
import re
import tempfile
import zipfile
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 fiona.errors import DriverError
from lxml import etree
from pystac import Item
from rasterio import errors, features, transform
from rasterio.crs import CRS
from rasterio.enums import Resampling
from sertit import AnyPath, files, geometry, path, rasters, 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,
BLUE,
CA,
CIRRUS,
CLOUDS,
EOREADER_STAC_MAP,
GREEN,
NARROW_NIR,
NIR,
RAW_CLOUDS,
RED,
SHADOWS,
SWIR_1,
SWIR_2,
SWIR_CIRRUS,
VRE_1,
VRE_2,
VRE_3,
WV,
BandNames,
SpectralBand,
to_str,
)
from eoreader.exceptions import InvalidProductError, InvalidTypeError
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
FOOTPRINT = "DETFOO"
CLOUDS = "CLASSI"
QUALITY = "QUALIT" # Regroups TECQUA, DEFECT, NODATA, SATURA
# 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"],
},
}
[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 10m resolution, even if we have 60m and 20m 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:
raise InvalidProductError(
f"Corrupted metadata and bad filename for {self.path}! "
f"Impossible to process this product."
)
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:
if isinstance(pixel_size, (list, tuple)):
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:
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:
# Open the zip file
with zipfile.ZipFile(self.path, "r") as zip_ds:
# Get the band folder (use dirname is the first of the list is a band)
band_path = [
os.path.dirname(f.filename)
for f in zip_ds.filelist
if dir_name in f.filename
][0]
# Workaround for a bug involving some bad archives
if band_path.startswith("/"):
band_path = band_path[1:]
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:
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_clean_band_path(
band, pixel_size=pixel_size, **kwargs
)
if clean_band.is_file():
band_paths[band] = clean_band
else:
band_id = self.bands[band].id
try:
if self.is_archived:
band_paths[band] = path.get_archived_rio_path(
self.path,
f".*{band_folders[band]}.*B{band_id}.*.jp2",
)
else:
band_paths[band] = path.get_file_in_dir(
band_folders[band],
f"B{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
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._l2ap_geocode_data(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._l2ap_geocode_data(band_path)
out_ds.crs = crs
out_ds.transform = tf
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=Resampling.bilinear,
**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:
raise InvalidProductError(
f"{quantif_prefix}QUANTIFICATION_VALUE not found in datatake metadata!"
)
# Get offset
offset_prefix = (
"BOA_" if self.product_type == S2ProductType.L2A else "RADIO_"
)
if self._processing_baseline < 4.0:
offset = 0.0
else:
try:
if band == NARROW_NIR:
band_id = 8
else:
band_id = int(self.bands[band].id)
offset = float(
root.findtext(
f".//{offset_prefix}ADD_OFFSET[@band_id = '{band_id}']"
)
)
except TypeError:
raise InvalidProductError(
f"{offset_prefix}ADD_OFFSET not found in datatake metadata!"
)
except InvalidProductError:
# If not datatake file
if self._processing_baseline < 4.0:
offset = 0.0
else:
offset = -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 _open_mask_lt_4_0(
self, mask_id: Union[str, S2GmlMasks], band: Union[BandNames, str] = None
) -> 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
if isinstance(band, BandNames):
band_name = self.bands[band].id
else:
band_name = 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())
except DriverError:
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.CLOUDS:
band = "00"
# Get QI_DATA path
if isinstance(band, BandNames):
band_id = self.bands[band].id
else:
band_id = band
if self.is_archived:
mask_path = path.get_archived_rio_path(
self.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, **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, **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, **kwargs)
else:
return self._manage_nodata_gt_4_0(band_arr, band, **kwargs)
def _manage_invalid_pixels_lt_4_0(
self, band_arr: xr.DataArray, band: BandNames, **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 = features.rasterize(
nodata_det.geometry,
out_shape=(band_arr.rio.height, band_arr.rio.width),
fill=self._mask_true, # Outside detector = nodata (inverted compared to the usual)
default_value=self._mask_false, # Inside detector = not nodata
transform=transform.from_bounds(
*band_arr.rio.bounds(), band_arr.rio.width, band_arr.rio.height
),
dtype=np.uint8,
)
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 = features.rasterize(
nodata_pix.geometry,
out_shape=(band_arr.rio.height, band_arr.rio.width),
fill=self._mask_false, # Outside vector
default_value=self._mask_true, # Inside vector
transform=transform.from_bounds(
*band_arr.rio.bounds(), band_arr.rio.width, band_arr.rio.height
),
dtype=np.uint8,
)
mask[mask_pix] = self._mask_true
return self._set_nodata_mask(band_arr, mask)
def _manage_invalid_pixels_gt_4_0(
self, band_arr: xr.DataArray, band: BandNames, **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.FOOTPRINT,
band,
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.QUALITY,
band,
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, **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 = features.rasterize(
nodata_det.geometry,
out_shape=(band_arr.rio.height, band_arr.rio.width),
fill=self._mask_true, # Outside detector = nodata (inverted compared to the usual)
default_value=self._mask_false, # Inside detector = not nodata
transform=transform.from_bounds(
*band_arr.rio.bounds(), band_arr.rio.width, band_arr.rio.height
),
dtype=np.uint8,
)
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)
return self._set_nodata_mask(band_arr, mask)
def _manage_nodata_gt_4_0(
self, band_arr: xr.DataArray, band: BandNames, **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.FOOTPRINT,
band,
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 are specified
if not bands:
return {}
if pixel_size is None and size is not None:
pixel_size = self._pixel_size_from_img_size(size)
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 _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:
raise InvalidProductError(
"Azimuth or Zenith angles not found in metadata!"
)
except InvalidProductError as ex:
LOGGER.warning(f"{ex}: 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
"""
if band == SHADOWS:
has_band = False
else:
has_band = True
return has_band
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,
)
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_vec = self._open_mask_gt_4_0(
S2Jp2Masks.CLOUDS,
"00",
pixel_size=pixel_size,
size=size,
**kwargs,
)
for band in bands:
if band == ALL_CLOUDS:
cloud = cloud_vec[0, :, :] | cloud_vec[1, :, :]
elif band == CIRRUS:
cloud = cloud_vec[1, :, :] # CIRRUS = band 2
elif band == CLOUDS:
cloud = cloud_vec[0, :, :] # OPAQUE = band 1
elif band == RAW_CLOUDS:
cloud = cloud_vec
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.
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._processing_baseline < 4.0:
return self._open_clouds_lt_4_0(bands, pixel_size, size, **kwargs)
else:
return self._open_clouds_gt_4_0(bands, pixel_size, size, **kwargs)
def _rasterize(
self, xds: xr.DataArray, geometry: gpd.GeoDataFrame, nodata: np.ndarray
) -> 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 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=self._mask_false, # Pixels outside mask
default_value=self._mask_true, # 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=self._mask_false,
dtype=np.uint8,
)
return self._create_mask(xds, cond, nodata)
def _l2ap_geocode_data(self, l2ap_path: AnyPathType) -> (Affine, int, int, CRS):
"""
Geocode L2Ap data.
Args:
l2ap_path (AnyPathType): Band path to be geocoded
Returns:
(Affine, int, int, CRS): Transform, width, height and CRS of the band
"""
try:
if isinstance(l2ap_path, str):
l2ap_path = AnyPath(l2ap_path)
# Read metadata
root, ns = self.read_mtd()
# Determine wanted resolution
if "10m" in l2ap_path.name:
res = 10
elif "20m" in l2ap_path.name:
res = 20
else:
res = 60
# Open size
width = int(root.findtext(f".//Size[@resolution='{res}']/NCOLS"))
height = int(root.findtext(f".//Size[@resolution='{res}']/NROWS"))
# Open upper-left corner
ulx = float(root.findtext(f".//Geoposition[@resolution='{res}']/ULX"))
uly = float(root.findtext(f".//Geoposition[@resolution='{res}']/ULY"))
# Create transform
tf = transform.from_origin(ulx, uly, res, res)
except InvalidProductError as ex:
raise InvalidProductError(f"{ex}: cannot geocode the bands!")
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 / path.get_archived_path(
self.path, file_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 / path.get_archived_path(
self.path, file_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 = path.get_archived_rio_path(
self.path, file_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:
raise InvalidProductError(
"SENSING_ORBIT_DIRECTION not found in metadata!"
)
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 = None
""" STAC Item of the product """
self.item = super_kwargs.pop("item", None)
if self.item is None:
try:
self.item = Item.from_file(product_path)
except TypeError:
raise InvalidProductError(
"You should either fill 'product_path' or 'item'."
)
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:
raise FileNotFoundError(
f"Impossible to find an asset in {list(self.item.assets.keys())} close enough to '{file_id}'"
)
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_clean_band_path(
band, pixel_size=pixel_size, **kwargs
)
if clean_band.is_file():
band_paths[band] = clean_band
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"))
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")
