# -*- 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.
"""
VHR (very high resoplution) super class.
See `here <https://earth.esa.int/eogateway/documents/20142/37627/DigitalGlobe-Standard-Imagery.pdf>`_
for more information.
"""
import logging
import os
from abc import abstractmethod
from typing import Union
import affine
import numpy as np
import rasterio
import xarray as xr
from rasterio import rpc
from rasterio import shutil as rio_shutil
from rasterio import warp
from rasterio.crs import CRS
from rasterio.enums import Resampling
from rasterio.vrt import WarpedVRT
from sertit import AnyPath, path, rasters, rasters_rio
from sertit.snap import MAX_CORES
from sertit.types import AnyPathStrType, AnyPathType
from eoreader import EOREADER_NAME, utils
from eoreader.bands import BandNames
from eoreader.env_vars import DEM_PATH, TILE_SIZE
from eoreader.exceptions import InvalidProductError
from eoreader.keywords import DEM_KW
from eoreader.products import OpticalProduct
from eoreader.utils import DEFAULT_TILE_SIZE
LOGGER = logging.getLogger(EOREADER_NAME)
[docs]
class VhrProduct(OpticalProduct):
"""
Super Class of VHR products.
Implementing mechanisms for orthorectification, default transform...
"""
[docs]
def __init__(
self,
product_path: AnyPathStrType,
archive_path: AnyPathStrType = None,
output_path: AnyPathStrType = None,
remove_tmp: bool = False,
**kwargs,
) -> None:
self.ortho_path = None
"""
Orthorectified path.
Can be set to use manually orthorectified or pansharpened data, especially useful for VHR data on steep terrain.
"""
self._proj_prod_type = []
self.band_combi = None
"""
Band combination, i.e. PAN, PMS, MS...
"""
# Order id (product name more or less)
self._order_id = None
# Resolutions
self._pan_res = None
self._ms_res = None
self._job_id = None
self._raw_nodata = 0
# 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)
"""
# VHR products are stacked
self.is_stacked = True
# 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)
"""
# Job ID
self._job_id = self._get_job_id()
# Post init done by the super class
super()._post_init(**kwargs)
[docs]
def get_default_band_path(self, **kwargs) -> AnyPathType:
"""
Get default band (:code:`GREEN` for optical data) path.
.. WARNING:
If you are using a non orthorectified product, this function will orthorectify the stack.
To do so, you **MUST** provide a DEM through the EOREADER_DEM_PATH environment variable
.. WARNING:
If you are using a non-projected product, this function will reproject the stack.
.. code-block:: python
>>> from eoreader.reader import Reader
>>> path = r"IMG_PHR1B_PMS_001"
>>> prod = Reader().open(path)
>>> prod.get_default_band_path()
'IMG_PHR1A_PMS_001/DIM_PHR1A_PMS_202005110231585_ORT_5547047101.XML'
Args:
kwargs: Additional arguments
Returns:
AnyPathType: Default band path
"""
return self._get_default_utm_band(self.pixel_size, **kwargs)
@abstractmethod
def _get_raw_crs(self) -> CRS:
"""
Get raw CRS of the tile
Returns:
rasterio.crs.CRS: CRS object
"""
raise NotImplementedError
def _get_ortho_path(self, **kwargs) -> AnyPathType:
"""
Get the orthorectified path of the bands.
Returns:
AnyPathType: Orthorectified path
"""
if self.product_type in self._proj_prod_type:
ortho_name = f"{self.condensed_name}_ortho.tif"
ortho_path, ortho_exists = self._get_out_path(ortho_name)
if not ortho_exists:
LOGGER.info(
"Manually orthorectified stack not given by the user. "
"Reprojecting whole stack, this may take a while. "
"(May be inaccurate on steep terrain, depending on the DEM pixel size)"
)
# Reproject and write on disk data
dem_path = self._get_dem_path(**kwargs)
with rasterio.open(str(self._get_tile_path())) as src:
if "rpcs" in kwargs:
rpcs = kwargs.pop("rpcs")
else:
rpcs = src.rpcs
if not rpcs:
raise InvalidProductError(
"Your projected VHR data doesn't have any RPC. "
"EOReader cannot orthorectify it!"
)
out_arr, meta = self._reproject(
src.read(), src.meta, rpcs, dem_path, **kwargs
)
rasters_rio.write(out_arr, meta, ortho_path, tags=src.tags())
else:
ortho_path = self._get_tile_path()
return ortho_path
[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"IMG_PHR1B_PMS_001"
>>> prod = Reader().open(path)
>>> prod.get_band_paths([GREEN, RED])
{
<SpectralBandNames.GREEN: 'GREEN'>:
'IMG_PHR1A_PMS_001/DIM_PHR1A_PMS_202005110231585_ORT_5547047101.XML',
<SpectralBandNames.RED: 'RED'>:
'IMG_PHR1A_PMS_001/DIM_PHR1A_PMS_202005110231585_ORT_5547047101.XML'
}
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
"""
if not self.ortho_path:
self.ortho_path = self._get_ortho_path(**kwargs)
# Processed path names
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:
# First look for reprojected bands
reproj_path = self._get_utm_band_path(
band=band.name, pixel_size=pixel_size
)
if not reproj_path.is_file():
# Then for original data
band_path = self.ortho_path
else:
band_path = reproj_path
band_paths[band] = band_path
return band_paths
def _get_dem_path(self, **kwargs) -> str:
"""
Get DEM path
Returns:
str: DEM path
"""
# Get DEM path
dem_path = os.environ.get(DEM_PATH, kwargs.get(DEM_KW))
if not dem_path:
raise ValueError(
f"As you are using a non orthorectified VHR product ({self.path}), "
f"you must provide a valid DEM through the {DEM_PATH} environment variable"
)
else:
if path.is_cloud_path(dem_path):
raise ValueError(
"gdalwarp cannot process DEM stored on cloud with 'RPC_DEM' argument, "
"hence cloud-stored DEM cannot be used with non orthorectified DIMAP data."
f"(DEM: {dem_path}, DIMAP data: {self.name})"
)
return dem_path
def _reproject(
self, src_arr: np.ndarray, src_meta: dict, rpcs: rpc.RPC, dem_path, **kwargs
) -> (np.ndarray, dict):
"""
Reproject using RPCs (cannot use another pixel size than src to ensure RPCs are valid)
Args:
src_arr (np.ndarray): Array to reproject
src_meta (dict): Metadata
rpcs (rpc.RPC): RPCs
dem_path (str): DEM path
Returns:
(np.ndarray, dict): Reprojected array and its metadata
"""
# Set RPC keywords
LOGGER.debug(f"Orthorectifying data with {dem_path}")
kwargs = {
"RPC_DEM": dem_path,
"RPC_DEM_MISSING_VALUE": 0,
"OSR_USE_ETMERC": "YES",
"BIGTIFF": "IF_NEEDED",
}
# Reproject
# WARNING: may not give correct output pixel size
out_arr, dst_transform = warp.reproject(
src_arr,
rpcs=rpcs,
src_crs=self._get_raw_crs(),
src_nodata=self._raw_nodata,
dst_crs=self.crs(),
dst_resolution=self.pixel_size,
dst_nodata=self._raw_nodata, # input data should be in integer
num_threads=MAX_CORES,
resampling=Resampling.bilinear,
**kwargs,
)
# Get dims
count, height, width = out_arr.shape
# Update metadata
meta = src_meta.copy()
meta["transform"] = dst_transform
meta["driver"] = "GTiff"
meta["compress"] = "lzw"
meta["nodata"] = self._raw_nodata
meta["crs"] = self.crs()
meta["width"] = width
meta["height"] = height
meta["count"] = count
return out_arr, meta
def _read_band(
self,
band_path: AnyPathType,
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
"""
with rasterio.open(str(band_path)) as dst:
dst_crs = dst.crs
# Compute pixel_size from size (if needed)
if pixel_size is None and size is not None:
pixel_size = self._pixel_size_from_img_size(size)
# Reproj path in case
reproj_path = self._get_utm_band_path(band=band.name, pixel_size=pixel_size)
# Manage the case if we got a LAT LON product
if not dst_crs.is_projected:
if not reproj_path.is_file():
reproj_path = self._get_utm_band_path(
band=band.name, pixel_size=pixel_size, writable=True
)
# Warp band if needed
self._warp_band(
band_path,
reproj_path=reproj_path,
pixel_size=pixel_size,
)
# Read band
LOGGER.debug(f"Reading warped {band.name}.")
band_arr = utils.read(
reproj_path,
pixel_size=pixel_size,
size=size,
resampling=Resampling.bilinear,
indexes=[self.bands[band].id],
**kwargs,
)
# Manage the case if we open a simple band (EOReader processed bands)
elif dst.count == 1:
# Read band
band_arr = utils.read(
band_path,
pixel_size=pixel_size,
size=size,
resampling=Resampling.bilinear,
**kwargs,
)
# Manage the case if we open a stack (native DIMAP bands)
else:
# Read band
band_arr = utils.read(
band_path,
pixel_size=pixel_size,
size=size,
resampling=Resampling.bilinear,
indexes=[self.bands[band].id],
**kwargs,
)
# Pop useless long name
if "long_name" in band_arr.attrs:
band_arr.attrs.pop("long_name")
return band_arr
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 {}
# Get band paths
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 _manage_invalid_pixels(
self, band_arr: xr.DataArray, band: BandNames, **kwargs
) -> xr.DataArray:
"""
Manage invalid pixels (Nodata, saturated, defective...)
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
"""
return self._manage_nodata(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 nodata not set, set it here
if not band_arr.rio.encoded_nodata:
band_arr = rasters.set_nodata(band_arr, self._raw_nodata)
return band_arr
def _get_condensed_name(self) -> str:
"""
Get PlanetScope products condensed name ({date}_PLD_{product_type}_{band_combi}).
Returns:
str: Condensed name
"""
return f"{self.get_datetime()}_{self.constellation.name}_{self.product_type.name}_{self.band_combi.name}_{self._job_id}"
def _get_path(self, filename: str = "", extension: str = "") -> AnyPathType:
"""
Get either the archived path of the normal path of an asset
Args:
filename (str): Filename with wildcards
extension (str): Extension
Returns:
Union[list, AnyPathType]: Path or list of paths (needs this because of potential mosaic)
"""
prod_path = []
try:
if filename and not filename.startswith("*"):
filename = f"*{filename}"
if self.is_archived:
prod_path = path.get_archived_rio_path(
self.path,
rf".{filename}.*\.{extension}",
)
else:
prod_path = next(self.path.glob(f"{filename}*.{extension}"))
except (FileNotFoundError, IndexError, StopIteration):
raise InvalidProductError(
f"No file corresponding to *{filename}*.{extension} found in {self.path}"
)
return prod_path
def _get_utm_band_path(
self,
band: str,
pixel_size: Union[float, tuple, list] = None,
writable: bool = False,
) -> AnyPathType:
"""
Create the UTM band path
Args:
band (str): Band in string as written on the filepath
pixel_size (Union[float, tuple, list]): Pixel size of the wanted UTM band
writable (bool): Do we need to write the UTM band ?
Returns:
AnyPathType: UTM band path
"""
res_str = self._pixel_size_to_str(pixel_size)
return self._get_band_folder(writable).joinpath(
f"{self.condensed_name}_{band}_{res_str}.vrt"
)
def _warp_band(
self,
band_path: AnyPathStrType,
reproj_path: AnyPathStrType,
pixel_size: float = None,
) -> None:
"""
Warp band to UTM
Args:
band_path (AnyPathStrType): Band path to warp
reproj_path (AnyPathStrType): Path where to write the reprojected band
pixel_size (int): Band pixel size in meters
"""
# Do not warp if existing file
if reproj_path.is_file():
return
if not pixel_size:
pixel_size = self.pixel_size
LOGGER.info(
f"Warping {path.get_filename(band_path)} to UTM with a {pixel_size} m pixel size."
)
# Read band
with rasterio.open(str(band_path)) as src:
# Calculate transform
utm_tr, utm_w, utm_h = warp.calculate_default_transform(
src.crs,
self.crs(),
src.width,
src.height,
*src.bounds,
resolution=pixel_size,
)
vrt_options = {
"crs": self.crs(),
"transform": utm_tr,
"height": utm_h,
"width": utm_w,
# TODO: go nearest to speed up results ?
"resampling": Resampling.bilinear,
"nodata": self._raw_nodata,
# Float32 is the max possible
"warp_mem_limit": 32
* int(os.getenv(TILE_SIZE, DEFAULT_TILE_SIZE)) ** 2
/ 1e6,
"dtype": src.meta["dtype"],
"num_threads": MAX_CORES,
}
with rasterio.Env(
**{"GDAL_NUM_THREADS": "ALL_CPUS", "NUM_THREADS": "ALL_CPUS"}
):
with WarpedVRT(src, **vrt_options) as vrt:
rio_shutil.copy(vrt, reproj_path, driver="vrt")
def _get_default_utm_band(
self, pixel_size: float = None, size: Union[list, tuple] = None
) -> AnyPathType:
"""
Get the default UTM band:
- If one already exists, get it
- If not, create reproject (if needed) the GREEN band
Args:
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:
str: Default UTM path
"""
# Manage pixel_size
if pixel_size is None and size is not None:
pixel_size = self._pixel_size_from_img_size(size)
def_res = pixel_size if pixel_size else self.pixel_size
# Get default band path
default_band = self.get_default_band()
def_path = self.get_band_paths([default_band], pixel_size=def_res)[default_band]
# First look for reprojected bands
res_str = self._pixel_size_to_str(pixel_size)
warped_regex = f"*{self.condensed_name}_*_{res_str}.tif"
reproj_bands = list(self._get_band_folder().glob(warped_regex))
if len(reproj_bands) == 0:
# Check in the writeable band folder
reproj_bands = list(self._get_band_folder(writable=True).glob(warped_regex))
if len(reproj_bands) == 0:
# Manage the case if we got a LAT LON product
with rasterio.open(str(def_path)) as dst:
dst_crs = dst.crs
if not dst_crs.is_projected:
def_band = self.get_default_band()
utm_path = self._get_utm_band_path(
band=def_band.name, pixel_size=pixel_size
)
# Warp band if needed
if not utm_path.is_file():
utm_path = self._get_utm_band_path(
band=def_band.name, pixel_size=pixel_size, writable=True
)
self._warp_band(
def_path,
reproj_path=utm_path,
pixel_size=pixel_size,
)
else:
utm_path = def_path
else:
utm_path = AnyPath(reproj_bands[0])
else:
utm_path = AnyPath(reproj_bands[0])
return utm_path
@abstractmethod
def _get_tile_path(self) -> AnyPathType:
"""
Get the VHR tile path
Returns:
AnyPathType: VHR filepath
"""
raise NotImplementedError
@abstractmethod
def _get_job_id(self) -> AnyPathType:
"""
Get VHR job ID
Returns:
AnyPathType: VHR product ID
"""
raise NotImplementedError
[docs]
def get_raw_band_paths(self, **kwargs) -> dict:
"""
Return the raw band paths.
Args:
kwargs: Additional arguments
Returns:
dict: Dictionary containing the path of each queried band
"""
raw_band_paths = {}
for band in self.get_existing_bands():
raw_band_paths[band] = self._get_tile_path()
return raw_band_paths