Module eoreader.products.product
Product, superclass of all EOReader satellites products
Expand source code
# -*- coding: utf-8 -*-
# Copyright 2021, 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.
""" Product, superclass of all EOReader satellites products """
# pylint: disable=W0107
from __future__ import annotations
import datetime as dt
import logging
import os
import tempfile
from abc import abstractmethod
from enum import unique
from functools import wraps
from typing import Any, Callable, Union
import geopandas as gpd
import numpy as np
import rasterio
import xarray as xr
from rasterio import crs as riocrs
from rasterio import warp
from rasterio.enums import Resampling
from eoreader.bands import index
from eoreader.bands.alias import *
from eoreader.bands.bands import BandNames
from eoreader.env_vars import CI_EOREADER_BAND_FOLDER, DEM_PATH
from eoreader.reader import Platform, Reader
from eoreader.utils import EOREADER_NAME
from sertit import files, misc, rasters, strings
from sertit.misc import ListEnum
from sertit.rasters import XDS_TYPE
from sertit.snap import MAX_CORES
LOGGER = logging.getLogger(EOREADER_NAME)
PRODUCT_FACTORY = Reader()
def path_or_dst(method: Callable) -> Callable:
"""
Path or dataset decorator: allows a function to ingest a path or a rasterio dataset
```python
>>> # Create mock function
>>> @path_or_dst
>>> def fct(dst):
>>> read(dst)
>>>
>>> # Test the two ways
>>> read1 = fct("path\\to\\raster.tif")
>>> with rasterio.open("path\\to\\raster.tif") as dst:
>>> read2 = fct(dst)
>>>
>>> # Test
>>> read1 == read2
True
```
Args:
method (Callable): Function to decorate
Returns:
Callable: decorated function
"""
@wraps(method)
def path_or_dst_wrapper(
self, path_or_ds: Union[str, rasterio.DatasetReader], *args, **kwargs
) -> Any:
"""
Path or dataset wrapper
Args:
self: Class
path_or_ds (Union[str, rasterio.DatasetReader]): Raster path or its dataset
*args: args
**kwargs: kwargs
Returns:
Any: regular output
"""
if isinstance(path_or_ds, str):
with rasterio.open(path_or_ds) as dst:
out = method(self, dst, *args, **kwargs)
else:
out = method(self, path_or_ds, *args, **kwargs)
return out
return path_or_dst_wrapper
@unique
class SensorType(ListEnum):
"""
Sensor type of the products, optical or SAR
"""
OPTICAL = "Optical"
"""For optical data"""
SAR = "SAR"
"""For SAR data"""
class Product:
"""Super class of EOReader Products"""
def __init__(
self, product_path: str, archive_path: str = None, output_path: str = None
) -> None:
self.name = files.get_filename(product_path)
"""Product name (its filename without any extension)."""
self.split_name = self._get_split_name()
"""Split name, to retrieve every information from its filename (dates, tile, product type...)."""
self.archive_path = archive_path if archive_path else product_path
"""Archive path, same as the product path if not specified.
Useful when you want to know where both the extracted and archived version of your product are stored."""
self.path = product_path
"""Usable path to the product, either extracted or archived path, according to the satellite."""
self.is_archived = os.path.isfile(self.path)
""" Is the archived product is processed
(a products is considered as archived if its products path is a directory)."""
self.needs_extraction = True
"""Does this products needs to be extracted to be processed ? (`True` by default)."""
# The output will be given later
if output_path:
self._tmp = None
self._output = output_path
os.makedirs(output_path, exist_ok=True)
else:
self._tmp = tempfile.TemporaryDirectory()
self._output = self._tmp.name
"""Output directory of the product, to write orthorectified data for example."""
# Get the products date and datetime
self.date = self.get_date(as_date=True)
"""Acquisition date."""
self.datetime = self.get_datetime(as_datetime=True)
"""Acquisition datetime."""
self.tile_name = None
"""Tile if possible (for data that can be piled, for example S2 and Landsats)."""
self.sensor_type = None
"""Sensor type, SAR or optical."""
self.product_type = None
"""Product type, satellite-related field, such as L1C or L2A for Sentinel-2 data."""
self.band_names = None
"""Band mapping between band wrapping names such as `GREEN` and band real number such as `03` for Sentinel-2."""
self.is_reference = False
"""If the product is a reference, used for algorithms that need pre and post data, such as fire detection."""
self.corresponding_ref = []
"""The corresponding reference products to the current one
(if the product is not a reference but has a reference data corresponding to it).
A list because of multiple ref in case of non-stackable products (S3, S1...)"""
self.nodata = -9999
""" Product nodata, set to 0 by default. Please do not touch this or all index will fail. """
# Mask values
self._mask_true = 1
self._mask_false = 0
self.platform = self._get_platform()
"""Product platform, such as Sentinel-2"""
# Post initialization
self._post_init()
# Set product type, needs to be done after the post-initialization
self._set_product_type()
# Set the resolution, needs to be done when knowing the product type
self.resolution = self._set_resolution()
"""
Default resolution in meters of the current product.
For SAR product, we use Ground Range resolution as we will automatically orthorectify the tiles.
"""
self.condensed_name = self._get_condensed_name()
"""
Condensed name, the filename with only useful data to keep the name unique
(ie. `20191215T110441_S2_30TXP_L2A_122756`).
Used to shorten names and paths.
"""
self.sat_id = self.platform.name
"""Satellite ID, i.e. `S2` for Sentinel-2"""
# TODO: manage self.needs_extraction
def __del__(self):
"""Cleaning up _tmp directory"""
if self._tmp:
self._tmp.cleanup()
@abstractmethod
def _post_init(self) -> None:
"""
Function used to post_init the products
(setting sensor type, band names and so on)
"""
raise NotImplementedError("This method should be implemented by a child class")
def footprint(self) -> gpd.GeoDataFrame:
"""
Get UTM footprint of the products (without nodata, *in french == emprise utile*)
```python
>>> from eoreader.reader import Reader
>>> path = r"S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE.zip"
>>> prod = Reader().open(path)
>>> prod.footprint()
index geometry
0 0 POLYGON ((199980.000 4500000.000, 199980.000 4...
```
Returns:
gpd.GeoDataFrame: Footprint as a GeoDataFrame
"""
def_band = self.get_default_band()
default_xda = self.load(def_band)[
def_band
] # Forced to load as the nodata may not be positioned by default
return rasters.get_footprint(default_xda)
@abstractmethod
def extent(self) -> gpd.GeoDataFrame:
"""
Get UTM extent of the tile
```python
>>> from eoreader.reader import Reader
>>> path = r"S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE.zip"
>>> prod = Reader().open(path)
>>> prod.utm_extent()
geometry
0 POLYGON ((309780.000 4390200.000, 309780.000 4...
```
Returns:
gpd.GeoDataFrame: Footprint in UTM
"""
raise NotImplementedError("This method should be implemented by a child class")
@abstractmethod
def crs(self) -> riocrs.CRS:
"""
Get UTM projection of the tile
```python
>>> from eoreader.reader import Reader
>>> path = r"S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE.zip"
>>> prod = Reader().open(path)
>>> prod.utm_crs()
CRS.from_epsg(32630)
```
Returns:
crs.CRS: CRS object
"""
raise NotImplementedError("This method should be implemented by a child class")
def _get_band_folder(self):
"""Manage the case of CI SNAP Bands"""
# Manage CI SNAP band
ci_band_folder = os.environ.get(CI_EOREADER_BAND_FOLDER)
if ci_band_folder and os.path.isdir(ci_band_folder):
band_folder = ci_band_folder
else:
band_folder = self.output
return band_folder
@abstractmethod
def _set_resolution(self) -> float:
"""
Set product default resolution (in meters)
"""
raise NotImplementedError("This method should be implemented by a child class")
@abstractmethod
def _set_product_type(self) -> None:
"""
Set product type
"""
raise NotImplementedError("This method should be implemented by a child class")
@classmethod
def _get_platform(cls) -> Platform:
class_module = cls.__module__.split(".")[-1]
sat_id = class_module.split("_")[0].upper()
return getattr(Platform, sat_id)
@abstractmethod
def _get_condensed_name(self) -> str:
"""
Set product condensed name.
Returns:
str: Condensed name
"""
raise NotImplementedError("This method should be implemented by a child class")
def _get_split_name(self) -> list:
"""
Get split name (erasing empty strings in it by precaution, especially for S1 and S3 data)
Returns:
list: Split products name
"""
return [x for x in self.name.split("_") if x]
@abstractmethod
def get_datetime(self, as_datetime: bool = False) -> Union[str, dt.datetime]:
"""
Get the product's acquisition datetime, with format `YYYYMMDDTHHMMSS` <-> `%Y%m%dT%H%M%S`
```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
"""
raise NotImplementedError("This method should be implemented by a child class")
def get_date(self, as_date: bool = False) -> Union[str, dt.date]:
"""
Get the product's acquisition date.
```python
>>> from eoreader.reader import Reader
>>> path = r"S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE.zip"
>>> prod = Reader().open(path)
>>> prod.get_date(as_date=True)
datetime.datetime(2020, 8, 24, 0, 0)
>>> prod.get_date(as_date=False)
'20200824'
```
Args:
as_date (bool): Return the date as a datetime.date. If false, returns a string.
Returns:
str: Its acquisition date
"""
date = self.get_datetime().split("T")[0]
if as_date:
date = strings.str_to_date(date, date_format="%Y%m%d")
return date
@abstractmethod
def get_default_band_path(self) -> str:
"""
Get default band path (among the existing ones).
Usually `GREEN` band for optical data and the first existing one between `VV` and `HH` for SAR data.
```python
>>> from eoreader.reader import Reader
>>> path = r"S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE.zip"
>>> prod = Reader().open(path)
>>> prod.get_default_band_path()
'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'
```
Returns:
str: Default band path
"""
raise NotImplementedError("This method should be implemented by a child class")
@abstractmethod
def get_default_band(self) -> BandNames:
"""
Get default band:
Usually `GREEN` band for optical data and the first existing one between `VV` and `HH` for SAR data.
```python
>>> from eoreader.reader import Reader
>>> path = r"S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE.zip"
>>> prod = Reader().open(path)
>>> prod.get_default_band()
<OpticalBandNames.GREEN: 'GREEN'>
```
Returns:
str: Default band
"""
raise NotImplementedError("This method should be implemented by a child class")
def get_existing_bands(self) -> list:
"""
Return the existing bands.
```python
>>> from eoreader.reader import Reader
>>> path = r"S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE.zip"
>>> prod = Reader().open(path)
>>> prod.get_existing_bands()
[<OpticalBandNames.CA: 'COASTAL_AEROSOL'>,
<OpticalBandNames.BLUE: 'BLUE'>,
<OpticalBandNames.GREEN: 'GREEN'>,
<OpticalBandNames.RED: 'RED'>,
<OpticalBandNames.VRE_1: 'VEGETATION_RED_EDGE_1'>,
<OpticalBandNames.VRE_2: 'VEGETATION_RED_EDGE_2'>,
<OpticalBandNames.VRE_3: 'VEGETATION_RED_EDGE_3'>,
<OpticalBandNames.NIR: 'NIR'>,
<OpticalBandNames.NNIR: 'NARROW_NIR'>,
<OpticalBandNames.WV: 'WATER_VAPOUR'>,
<OpticalBandNames.CIRRUS: 'CIRRUS'>,
<OpticalBandNames.SWIR_1: 'SWIR_1'>,
<OpticalBandNames.SWIR_2: 'SWIR_2'>]
```
Returns:
list: List of existing bands in the products
"""
raise NotImplementedError("This method should be implemented by a child class")
@abstractmethod
def get_existing_band_paths(self) -> dict:
"""
Return the existing band paths.
```python
>>> from eoreader.reader import Reader
>>> path = r"S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE.zip"
>>> prod = Reader().open(path)
>>> prod.get_existing_band_paths()
{
<OpticalBandNames.CA: 'COASTAL_AEROSOL'>: '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_B01.jp2',
...,
<OpticalBandNames.SWIR_2: 'SWIR_2'>: '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_B12.jp2'
}
```
Returns:
dict: Dictionary containing the path of each queried band
"""
raise NotImplementedError("This method should be implemented by a child class")
def get_band_paths(self, band_list: list, resolution: float = None) -> dict:
"""
Return the paths of required bands.
```python
>>> from eoreader.reader import Reader
>>> from eoreader.bands.alias import *
>>> path = r"S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE.zip"
>>> prod = Reader().open(path)
>>> prod.get_band_paths([GREEN, RED])
{
<OpticalBandNames.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',
<OpticalBandNames.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
resolution (float): Band resolution
Returns:
dict: Dictionary containing the path of each queried band
"""
raise NotImplementedError("This method should be implemented by a child class")
@abstractmethod
def read_mtd(self) -> Any:
"""
Read metadata and outputs the metadata XML root and its namespace most of the time,
except from L8-collection 1 data which outputs a pandas DataFrame
```python
>>> from eoreader.reader import Reader
>>> path = r"S1A_IW_GRDH_1SDV_20191215T060906_20191215T060931_030355_0378F7_3696.zip"
>>> prod = Reader().open(path)
>>> prod.read_mtd()
(<Element product at 0x1832895d788>, '')
```
Returns:
Any: Metadata XML root and its namespace or pd.DataFrame
"""
raise NotImplementedError("This method should be implemented by a child class")
# pylint: disable=W0613
@path_or_dst
def _read_band(
self,
dataset,
resolution: Union[tuple, list, float] = None,
size: Union[list, tuple] = None,
) -> XDS_TYPE:
"""
Read band from disk.
.. WARNING::
For optical data, invalid pixels are not managed here
Args:
dataset (Dataset): Band dataset
resolution (Union[tuple, list, float]): Resolution of the wanted band, in dataset resolution unit (X, Y)
size (Union[tuple, list]): Size of the array (width, height). Not used if resolution is provided.
Returns:
XDS_TYPE: Band xarray
"""
raise NotImplementedError("This method should be implemented by a child class")
@abstractmethod
def _load_bands(
self, band_list: list, resolution: float = None, size: Union[list, tuple] = None
) -> dict:
"""
Load bands as numpy arrays with the same resolution (and same metadata).
Args:
band_list (list): List of the wanted bands
resolution (int): Band resolution in meters
size (Union[tuple, list]): Size of the array (width, height). Not used if resolution is provided.
Returns:
dict: Dictionary {band_name, band_xarray}
"""
raise NotImplementedError("This method should be implemented by a child class")
def _load_dem(
self, band_list: list, resolution: float = None, size: Union[list, tuple] = None
) -> dict:
"""
Load bands as numpy arrays with the same resolution (and same metadata).
Args:
band_list (list): List of the wanted bands
resolution (int): Band resolution in meters
size (Union[tuple, list]): Size of the array (width, height). Not used if resolution is provided.
Returns:
dict: Dictionary {band_name, band_xarray}
"""
dem_bands = {}
if band_list:
dem_path = os.environ.get(DEM_PATH) # We already checked if it exists
for band in band_list:
assert is_dem(band)
if band == DEM:
path = self._warp_dem(dem_path, resolution=resolution, size=size)
elif band == SLOPE:
path = self._compute_slope(
dem_path, resolution=resolution, size=size
)
elif band == HILLSHADE:
path = self._compute_hillshade(
dem_path, resolution=resolution, size=size
)
else:
raise InvalidTypeError(f"Unknown DEM band: {band}")
dem_bands[band] = rasters.read(path, resolution=resolution, size=size)
return dem_bands
def load(
self,
bands: Union[list, BandNames, Callable],
resolution: float = None,
size: Union[list, tuple] = None,
) -> dict:
"""
Open the bands and compute the wanted index.
The bands will be purged of nodata and invalid pixels,
the nodata will be set to 0 and the bands will be masked arrays in float.
Bands that come out this function at the same time are collocated and therefore have the same shapes.
This can be broken if you load data separately. Its is best to always load DEM data with some real bands.
```python
>>> from eoreader.reader import Reader
>>> from eoreader.bands.alias import *
>>> path = r"S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE.zip"
>>> prod = Reader().open(path)
>>> bands = prod.load([GREEN, NDVI], resolution=20)
>>> bands
'''
{
<function NDVI at 0x000001EFFFF5DD08>: <xarray.DataArray 'NDVI' (band: 1, y: 5490, x: 5490)>
array([[[0.949506 , 0.92181516, 0.9279379 , ..., 1.8002278 ,
1.5424857 , 1.6747767 ],
[0.95369846, 0.91685396, 0.8957871 , ..., 1.5847116 ,
1.5248713 , 1.5011379 ],
[2.9928885 , 1.3031474 , 1.0076253 , ..., 1.5969834 ,
1.5590671 , 1.5018653 ],
...,
[1.4245619 , 1.6115025 , 1.6201663 , ..., 1.2387121 ,
1.4025431 , 1.800678 ],
[1.5627214 , 1.822388 , 1.7245892 , ..., 1.1694248 ,
1.2573677 , 1.5767351 ],
[1.653781 , 1.6424649 , 1.5923225 , ..., 1.3072611 ,
1.2181134 , 1.2478763 ]]], dtype=float32)
Coordinates:
* band (band) int32 1
* y (y) float64 4.5e+06 4.5e+06 4.5e+06 ... 4.39e+06 4.39e+06
* x (x) float64 2e+05 2e+05 2e+05 ... 3.097e+05 3.098e+05 3.098e+05
spatial_ref int32 0,
<OpticalBandNames.GREEN: 'GREEN'>: <xarray.DataArray (band: 1, y: 5490, x: 5490)>
array([[[0.0615 , 0.061625, 0.061 , ..., 0.12085 , 0.120225,
0.113575],
[0.061075, 0.06045 , 0.06025 , ..., 0.114625, 0.119625,
0.117625],
[0.06475 , 0.06145 , 0.060925, ..., 0.111475, 0.114925,
0.115175],
...,
[0.1516 , 0.14195 , 0.1391 , ..., 0.159975, 0.14145 ,
0.127075],
[0.140325, 0.125975, 0.131875, ..., 0.18245 , 0.1565 ,
0.13015 ],
[0.133475, 0.1341 , 0.13345 , ..., 0.15565 , 0.170675,
0.16405 ]]], dtype=float32)
Coordinates:
* band (band) int32 1
* y (y) float64 4.5e+06 4.5e+06 4.5e+06 ... 4.39e+06 4.39e+06
* x (x) float64 2e+05 2e+05 2e+05 ... 3.097e+05 3.098e+05 3.098e+05
spatial_ref int32 0
}
'''
```
Args:
bands (Union[list, BandNames, Callable]): Band list
resolution (float): Resolution of the band, in meters
size (Union[tuple, list]): Size of the array (width, height). Not used if resolution is provided.
Returns:
dict: {band_name, band xarray}
"""
if not resolution and not size:
resolution = self.resolution
# Check if all bands are valid
if not isinstance(bands, list):
bands = [bands]
band_dict = self._load(bands, resolution, size)
# Manage the case of arrays of different size -> collocate arrays if needed
band_dict = self._collocate_bands(band_dict)
# Convert to xarray dataset when all the bands have the same size
# TODO: cannot convert as we have non-string index
# xds = xr.Dataset(band_dict)
# Sort bands to the asked order
# xds.reindex({"band": bands})
return band_dict
@abstractmethod
def _load(
self, bands: list, resolution: float = None, size: Union[list, tuple] = None
) -> dict:
"""
Core function loading data bands
Args:
bands (list): Band list
resolution (float): Resolution of the band, in meters
size (Union[tuple, list]): Size of the array (width, height). Not used if resolution is provided.
Returns:
Dictionary {band_name, band_xarray}
"""
raise NotImplementedError("This method should be implemented by a child class")
def has_band(self, band: Union[BandNames, Callable]) -> bool:
"""
Does this products has the specified band ?
By band, we mean:
- satellite band
- index
- DEM band
- cloud band
```python
>>> from eoreader.reader import Reader
>>> from eoreader.bands.alias import *
>>> path = r"S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE.zip"
>>> prod = Reader().open(path)
>>> prod.has_band(GREEN)
True
>>> prod.has_band(TIR_2)
False
>>> prod.has_band(NDVI)
True
>>> prod.has_band(SHADOWS)
False
>>> prod.has_band(HILLSHADE)
True
```
Args:
band (Union[obn, sbn]): Optical or SAR band
Returns:
bool: True if the products has the specified band
"""
if is_dem(band):
if self.sensor_type == SensorType.SAR and band == HILLSHADE:
has_band = False
else:
has_band = True
elif is_clouds(band):
has_band = self._has_cloud_band(band)
elif is_index(band):
has_band = self._has_index(band)
else:
has_band = band in self.get_existing_bands()
return has_band
def _has_cloud_band(self, band: BandNames) -> bool:
"""
Does this products has the specified cloud band ?
```python
>>> from eoreader.reader import Reader
>>> from eoreader.bands.alias import *
>>> path = r"S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE.zip"
>>> prod = Reader().open(path)
>>> prod.has_cloud_band(CLOUDS)
True
```
"""
raise NotImplementedError("This method should be implemented by a child class")
def _has_index(self, idx: Callable) -> bool:
"""
Cen the specified index be computed from this products ?
```python
>>> from eoreader.reader import Reader
>>> from eoreader.bands.alias import *
>>> path = r"S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE.zip"
>>> prod = Reader().open(path)
>>> prod.has_index(NDVI)
True
```
Args:
idx (Callable): Index
Returns:
bool: True if the specified index can be computed with this products's bands
"""
index_bands = index.get_needed_bands(idx)
return all(np.isin(index_bands, self.get_existing_bands()))
def __gt__(self, other: Product) -> bool:
"""
Overload greater than for eoreader -> compare the dates:
The greater products is the one acquired the last.
Args:
other (Product): Other products to be compared with this one
Returns:
bool: True if this products has been acquired after the other
"""
return self.date > other.date
def __ge__(self, other: Product) -> bool:
"""
Overload greater than for eoreader -> compare the dates:
The greater products is the one acquired the last.
Args:
other (Product): Other products to be compared with this one
Returns:
bool: True if this products has been acquired after or in the same time than the other
"""
return self.date >= other.date
def __eq__(self, other: Product) -> bool:
"""
Overload greater than for eoreader -> compare the dates:
The greater products is the one acquired the last.
Args:
other (Product): Other products to be compared with this one
Returns:
bool: True if this products has been acquired in the same time than the other
"""
return self.date == other.date
def __ne__(self, other: Product) -> bool:
"""
Overload greater than for eoreader -> compare the dates:
The greater products is the one acquired the last.
Args:
other (Product): Other products to be compared with this one
Returns:
bool: True if this products has been acquired not in the same time than the other
"""
return self.date != other.date
def __le__(self, other: Product) -> bool:
"""
Overload greater than for eoreader -> compare the dates:
The greater products is the one acquired the last.
Args:
other (Product): Other products to be compared with this one
Returns:
bool: True if this products has been acquired before or in the same time than the other
"""
return self.date <= other.date
def __lt__(self, other: Product) -> bool:
"""
Overload greater than for eoreader -> compare the dates:
The greater products is the one acquired the last.
Args:
other (Product): Other products to be compared with this one
Returns:
bool: True if this products has been acquired before the other
"""
return self.date < other.date
@property
def output(self) -> str:
"""Output directory of the product, to write orthorectified data for example."""
return self._output
@output.setter
def output(self, value: str):
"""Output directory of the product, to write orthorectified data for example."""
self._output = value
if not os.path.isdir(self._output):
os.makedirs(self._output, exist_ok=True)
def _warp_dem(
self,
dem_path: str = "",
resolution: Union[float, tuple] = None,
size: Union[list, tuple] = None,
resampling: Resampling = Resampling.bilinear,
) -> str:
"""
Get this products DEM, warped to this products footprint and CRS.
If no DEM is giving (or non existing or non intersecting the products):
- Using EUDEM over Europe
- Using MERIT DEM everwhere else
```python
>>> from eoreader.reader import Reader
>>> from eoreader.bands.alias import *
>>> path = r"S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE.zip"
>>> prod = Reader().open(path)
>>> prod.warp_dem(resolution=20) # In meters
'/path/to/20200824T110631_S2_T30TTK_L1C_150432_DEM.tif'
```
Args:
dem_path (str): DEM path, using EUDEM/MERIT DEM if none
resolution (Union[float, tuple]): Resolution in meters. If not specified, use the product resolution.
resampling (Resampling): Resampling method
size (Union[tuple, list]): Size of the array (width, height). Not used if resolution is provided.
Returns:
str: DEM path (as a VRT)
"""
warped_dem_path = os.path.join(
self._get_band_folder(), f"{self.condensed_name}_DEM.tif"
)
if os.path.isfile(warped_dem_path):
LOGGER.debug("Already existing DEM for %s. Skipping process.", self.name)
else:
LOGGER.debug("Warping DEM for %s", self.name)
# Check existence (SRTM)
if not os.path.isfile(dem_path):
raise FileNotFoundError(f"DEM file does not exist here: {dem_path}")
# Reproject DEM into products CRS
with rasterio.open(self.get_default_band_path()) as prod_dst:
LOGGER.debug("Using DEM: %s", dem_path)
with rasterio.open(dem_path) as dem_ds:
# Get adjusted transform and shape (with new resolution)
if size is not None and resolution is None:
try:
# Get destination transform
out_h = size[1]
out_w = size[0]
# Get destination transform
coeff_x = prod_dst.width / out_w
coeff_y = prod_dst.height / out_h
dst_tr = prod_dst.transform
dst_tr *= dst_tr.scale(coeff_x, coeff_y)
except (TypeError, KeyError):
raise ValueError(
f"Size should exist (as resolution is None)"
f" and castable to a list: {size}"
)
else:
# Refine resolution
if resolution is None:
resolution = self.resolution
res_x = (
resolution[0]
if isinstance(resolution, (tuple, list))
else resolution
)
res_y = (
resolution[1]
if isinstance(resolution, (tuple, list))
else resolution
)
# Get destination transform
dst_tr = prod_dst.transform
coeff_x = np.abs(res_x / dst_tr.a)
coeff_y = np.abs(res_y / dst_tr.e)
dst_tr *= dst_tr.scale(coeff_x, coeff_y)
# Get destination transform
out_w = int(np.round(prod_dst.width / coeff_x))
out_h = int(np.round(prod_dst.height / coeff_y))
# Get empty output
reprojected_array = np.zeros(
(prod_dst.count, out_h, out_w), dtype=np.float32
)
# Write reprojected DEM: here do not use utils.write()
out_meta = prod_dst.meta.copy()
out_meta["dtype"] = reprojected_array.dtype
out_meta["transform"] = dst_tr
out_meta["driver"] = "GTiff"
out_meta["width"] = out_w
out_meta["height"] = out_h
with rasterio.open(warped_dem_path, "w", **out_meta) as out_dst:
out_dst.write(reprojected_array)
# Reproject
warp.reproject(
source=rasterio.band(dem_ds, range(1, dem_ds.count + 1)),
destination=rasterio.band(
out_dst, range(1, out_dst.count + 1)
),
resampling=resampling,
num_threads=MAX_CORES,
)
return warped_dem_path
@abstractmethod
def _compute_hillshade(
self,
dem_path: str = "",
resolution: Union[float, tuple] = None,
size: Union[list, tuple] = None,
resampling: Resampling = Resampling.bilinear,
) -> str:
"""
Compute Hillshade mask
Args:
dem_path (str): DEM path, using EUDEM/MERIT DEM if none
resolution (Union[float, tuple]): Resolution in meters. If not specified, use the product resolution.
size (Union[tuple, list]): Size of the array (width, height). Not used if resolution is provided.
resampling (Resampling): Resampling method
Returns:
str: Hillshade mask path
"""
raise NotImplementedError("This method should be implemented by a child class")
def _compute_slope(
self,
dem_path: str = "",
resolution: Union[float, tuple] = None,
size: Union[list, tuple] = None,
resampling: Resampling = Resampling.bilinear,
) -> str:
"""
Compute slope mask
Args:
dem_path (str): DEM path, using EUDEM/MERIT DEM if none
resolution (Union[float, tuple]): Resolution in meters. If not specified, use the product resolution.
size (Union[tuple, list]): Size of the array (width, height). Not used if resolution is provided.
resampling (Resampling): Resampling method
Returns:
str: Slope mask path
"""
# Warp DEM
warped_dem_path = self._warp_dem(dem_path, resolution, size, resampling)
# Get slope path
slope_dem = os.path.join(self.output, f"{self.condensed_name}_SLOPE.tif")
if os.path.isfile(slope_dem):
LOGGER.debug(
"Already existing slope DEM for %s. Skipping process.", self.name
)
else:
LOGGER.debug("Computing slope for %s", self.name)
cmd_slope = [
"gdaldem",
"--config",
"NUM_THREADS",
MAX_CORES,
"slope",
"-compute_edges",
strings.to_cmd_string(warped_dem_path),
strings.to_cmd_string(slope_dem),
"-p",
]
# Run command
misc.run_cli(cmd_slope)
return slope_dem
@staticmethod
def _collocate_bands(bands: dict, master_xds: XDS_TYPE = None) -> dict:
"""
Collocate all bands from a dict if needed (if a raster shape is different)
Args:
bands (dict): Dict of bands to collocate if needed
Returns:
dict: Collocated bands
"""
for band_id, band in bands.items():
if master_xds is None:
master_xds = band # Master array is the first one in this case
if band.shape != master_xds.shape:
bands[band_id] = rasters.collocate(
master_xds=master_xds, slave_xds=band
)
bands[band_id] = bands[band_id].assign_coords(
{
"x": master_xds.x,
"y": master_xds.y,
}
) # Bug for now, tiny difference in coords
return bands
# pylint: disable=R0913
# Too many arguments (6/5)
def stack(
self,
bands: list,
resolution: float = None,
stack_path: str = None,
save_as_int: bool = False,
) -> xr.DataArray:
"""
Stack bands and index of a products.
```python
>>> from eoreader.reader import Reader
>>> from eoreader.bands.alias import *
>>> path = r"S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE.zip"
>>> prod = Reader().open(path)
>>> stack = prod.stack([NDVI, MNDWI, GREEN], resolution=20) # In meters
>>> stack
'''
<xarray.DataArray 'NDVI_MNDWI_GREEN' (z: 3, y: 5490, x: 5490)>
array([[[ 0.949506 , 0.92181516, 0.9279379 , ..., 1.8002278 ,
1.5424857 , 1.6747767 ],
[ 0.95369846, 0.91685396, 0.8957871 , ..., 1.5847116 ,
1.5248713 , 1.5011379 ],
[ 2.9928885 , 1.3031474 , 1.0076253 , ..., 1.5969834 ,
1.5590671 , 1.5018653 ],
...,
[ 1.4245619 , 1.6115025 , 1.6201663 , ..., 1.2387121 ,
1.4025431 , 1.800678 ],
[ 1.5627214 , 1.822388 , 1.7245892 , ..., 1.1694248 ,
1.2573677 , 1.5767351 ],
[ 1.653781 , 1.6424649 , 1.5923225 , ..., 1.3072611 ,
1.2181134 , 1.2478763 ]],
[[ 0.27066118, 0.23466069, 0.18792598, ..., -0.4611526 ,
-0.49751845, -0.4865216 ],
[ 0.22425456, 0.28004232, 0.27851456, ..., -0.5032771 ,
-0.501796 , -0.502669 ],
[-0.07466951, 0.06360884, 0.1207174 , ..., -0.50617427,
-0.50219285, -0.5034222 ],
[-0.47076276, -0.4705828 , -0.4747971 , ..., -0.32138503,
-0.36619243, -0.37428448],
[-0.4826967 , -0.5032287 , -0.48544118, ..., -0.278925 ,
-0.31404778, -0.36052078],
[-0.488381 , -0.48253912, -0.4697526 , ..., -0.38105175,
-0.30813277, -0.27739233]],
[[ 0.0615 , 0.061625 , 0.061 , ..., 0.12085 ,
0.120225 , 0.113575 ],
[ 0.061075 , 0.06045 , 0.06025 , ..., 0.114625 ,
0.119625 , 0.117625 ],
[ 0.06475 , 0.06145 , 0.060925 , ..., 0.111475 ,
0.114925 , 0.115175 ],
...,
[ 0.1516 , 0.14195 , 0.1391 , ..., 0.159975 ,
0.14145 , 0.127075 ],
[ 0.140325 , 0.125975 , 0.131875 , ..., 0.18245 ,
0.1565 , 0.13015 ],
[ 0.133475 , 0.1341 , 0.13345 , ..., 0.15565 ,
0.170675 , 0.16405 ]]], dtype=float32)
Coordinates:
* y (y) float64 4.5e+06 4.5e+06 4.5e+06 ... 4.39e+06 4.39e+06
* x (x) float64 2e+05 2e+05 2e+05 ... 3.097e+05 3.098e+05 3.098e+05
spatial_ref int32 0
* z (z) MultiIndex
- variable (z) object 'NDVI' 'MNDWI' 'GREEN'
- band (z) int64 1 1 1
-Attributes:
long_name: ['NDVI', 'MNDWI', 'GREEN']
'''
```
Args:
bands (list): Bands and index combination
resolution (float): Stack resolution. . If not specified, use the product resolution.
stack_path (str): Stack path
save_as_int (bool): Save stack as integers (uint16 and therefore multiply the values by 10.000)
Returns:
xr.DataArray: Stack as a DataArray
"""
if not resolution:
resolution = self.resolution
# Create the analysis stack
band_dict = self.load(bands, resolution)
# Convert into dataset with str as names
xds = xr.Dataset(
data_vars={to_str(key)[0]: val for key, val in band_dict.items()},
coords=band_dict[bands[0]].coords,
)
# Force nodata
stack = xds.to_stacked_array(new_dim="z", sample_dims=("x", "y"))
stack = stack.transpose("z", "y", "x")
# Save as integer
if save_as_int:
dtype = np.uint16
stack = (stack * 10000).astype(dtype)
else:
dtype = np.float32
stack = stack.astype(dtype)
# Some updates
stack = rasters.set_nodata(stack, self.nodata)
band_list = to_str(list(band_dict.keys()))
stack.attrs["long_name"] = band_list
stack = stack.rename("_".join(band_list))
# Write on disk
if stack_path:
rasters.write(stack, stack_path, dtype=dtype)
# Close datasets
for val in band_dict.values():
val.close()
return stack
@staticmethod
def _check_dem_path() -> None:
""" Check if DEM is set and exists"""
if DEM_PATH not in os.environ:
raise ValueError(
f"Dem path not set, unable to compute DEM bands! "
f"Please set the environment variable {DEM_PATH}."
)
else:
dem_path = os.environ.get(DEM_PATH)
if not os.path.isfile(dem_path):
raise FileNotFoundError(
f"{dem_path} is not a file! "
f"Please set the environment variable {DEM_PATH} to an existing file."
)
Functions
def path_or_dst(
method)
-
Path or dataset decorator: allows a function to ingest a path or a rasterio dataset
>>> # Create mock function >>> @path_or_dst >>> def fct(dst): >>> read(dst) >>> >>> # Test the two ways >>> read1 = fct("path\to\raster.tif") >>> with rasterio.open("path\to\raster.tif") as dst: >>> read2 = fct(dst) >>> >>> # Test >>> read1 == read2 True
Args
method
:Callable
- Function to decorate
Returns
Callable
- decorated function
Expand source code
def path_or_dst(method: Callable) -> Callable: """ Path or dataset decorator: allows a function to ingest a path or a rasterio dataset ```python >>> # Create mock function >>> @path_or_dst >>> def fct(dst): >>> read(dst) >>> >>> # Test the two ways >>> read1 = fct("path\\to\\raster.tif") >>> with rasterio.open("path\\to\\raster.tif") as dst: >>> read2 = fct(dst) >>> >>> # Test >>> read1 == read2 True ``` Args: method (Callable): Function to decorate Returns: Callable: decorated function """ @wraps(method) def path_or_dst_wrapper( self, path_or_ds: Union[str, rasterio.DatasetReader], *args, **kwargs ) -> Any: """ Path or dataset wrapper Args: self: Class path_or_ds (Union[str, rasterio.DatasetReader]): Raster path or its dataset *args: args **kwargs: kwargs Returns: Any: regular output """ if isinstance(path_or_ds, str): with rasterio.open(path_or_ds) as dst: out = method(self, dst, *args, **kwargs) else: out = method(self, path_or_ds, *args, **kwargs) return out return path_or_dst_wrapper
Classes
class SensorType (value, names=None, *, module=None, qualname=None, type=None, start=1)
-
Sensor type of the products, optical or SAR
Expand source code
class SensorType(ListEnum): """ Sensor type of the products, optical or SAR """ OPTICAL = "Optical" """For optical data""" SAR = "SAR" """For SAR data"""
Ancestors
- sertit.misc.ListEnum
- enum.Enum
Class variables
var OPTICAL
-
For optical data
var SAR
-
For SAR data
class Product (product_path, archive_path=None, output_path=None)
-
Super class of EOReader Products
Expand source code
class Product: """Super class of EOReader Products""" def __init__( self, product_path: str, archive_path: str = None, output_path: str = None ) -> None: self.name = files.get_filename(product_path) """Product name (its filename without any extension).""" self.split_name = self._get_split_name() """Split name, to retrieve every information from its filename (dates, tile, product type...).""" self.archive_path = archive_path if archive_path else product_path """Archive path, same as the product path if not specified. Useful when you want to know where both the extracted and archived version of your product are stored.""" self.path = product_path """Usable path to the product, either extracted or archived path, according to the satellite.""" self.is_archived = os.path.isfile(self.path) """ Is the archived product is processed (a products is considered as archived if its products path is a directory).""" self.needs_extraction = True """Does this products needs to be extracted to be processed ? (`True` by default).""" # The output will be given later if output_path: self._tmp = None self._output = output_path os.makedirs(output_path, exist_ok=True) else: self._tmp = tempfile.TemporaryDirectory() self._output = self._tmp.name """Output directory of the product, to write orthorectified data for example.""" # Get the products date and datetime self.date = self.get_date(as_date=True) """Acquisition date.""" self.datetime = self.get_datetime(as_datetime=True) """Acquisition datetime.""" self.tile_name = None """Tile if possible (for data that can be piled, for example S2 and Landsats).""" self.sensor_type = None """Sensor type, SAR or optical.""" self.product_type = None """Product type, satellite-related field, such as L1C or L2A for Sentinel-2 data.""" self.band_names = None """Band mapping between band wrapping names such as `GREEN` and band real number such as `03` for Sentinel-2.""" self.is_reference = False """If the product is a reference, used for algorithms that need pre and post data, such as fire detection.""" self.corresponding_ref = [] """The corresponding reference products to the current one (if the product is not a reference but has a reference data corresponding to it). A list because of multiple ref in case of non-stackable products (S3, S1...)""" self.nodata = -9999 """ Product nodata, set to 0 by default. Please do not touch this or all index will fail. """ # Mask values self._mask_true = 1 self._mask_false = 0 self.platform = self._get_platform() """Product platform, such as Sentinel-2""" # Post initialization self._post_init() # Set product type, needs to be done after the post-initialization self._set_product_type() # Set the resolution, needs to be done when knowing the product type self.resolution = self._set_resolution() """ Default resolution in meters of the current product. For SAR product, we use Ground Range resolution as we will automatically orthorectify the tiles. """ self.condensed_name = self._get_condensed_name() """ Condensed name, the filename with only useful data to keep the name unique (ie. `20191215T110441_S2_30TXP_L2A_122756`). Used to shorten names and paths. """ self.sat_id = self.platform.name """Satellite ID, i.e. `S2` for Sentinel-2""" # TODO: manage self.needs_extraction def __del__(self): """Cleaning up _tmp directory""" if self._tmp: self._tmp.cleanup() @abstractmethod def _post_init(self) -> None: """ Function used to post_init the products (setting sensor type, band names and so on) """ raise NotImplementedError("This method should be implemented by a child class") def footprint(self) -> gpd.GeoDataFrame: """ Get UTM footprint of the products (without nodata, *in french == emprise utile*) ```python >>> from eoreader.reader import Reader >>> path = r"S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE.zip" >>> prod = Reader().open(path) >>> prod.footprint() index geometry 0 0 POLYGON ((199980.000 4500000.000, 199980.000 4... ``` Returns: gpd.GeoDataFrame: Footprint as a GeoDataFrame """ def_band = self.get_default_band() default_xda = self.load(def_band)[ def_band ] # Forced to load as the nodata may not be positioned by default return rasters.get_footprint(default_xda) @abstractmethod def extent(self) -> gpd.GeoDataFrame: """ Get UTM extent of the tile ```python >>> from eoreader.reader import Reader >>> path = r"S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE.zip" >>> prod = Reader().open(path) >>> prod.utm_extent() geometry 0 POLYGON ((309780.000 4390200.000, 309780.000 4... ``` Returns: gpd.GeoDataFrame: Footprint in UTM """ raise NotImplementedError("This method should be implemented by a child class") @abstractmethod def crs(self) -> riocrs.CRS: """ Get UTM projection of the tile ```python >>> from eoreader.reader import Reader >>> path = r"S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE.zip" >>> prod = Reader().open(path) >>> prod.utm_crs() CRS.from_epsg(32630) ``` Returns: crs.CRS: CRS object """ raise NotImplementedError("This method should be implemented by a child class") def _get_band_folder(self): """Manage the case of CI SNAP Bands""" # Manage CI SNAP band ci_band_folder = os.environ.get(CI_EOREADER_BAND_FOLDER) if ci_band_folder and os.path.isdir(ci_band_folder): band_folder = ci_band_folder else: band_folder = self.output return band_folder @abstractmethod def _set_resolution(self) -> float: """ Set product default resolution (in meters) """ raise NotImplementedError("This method should be implemented by a child class") @abstractmethod def _set_product_type(self) -> None: """ Set product type """ raise NotImplementedError("This method should be implemented by a child class") @classmethod def _get_platform(cls) -> Platform: class_module = cls.__module__.split(".")[-1] sat_id = class_module.split("_")[0].upper() return getattr(Platform, sat_id) @abstractmethod def _get_condensed_name(self) -> str: """ Set product condensed name. Returns: str: Condensed name """ raise NotImplementedError("This method should be implemented by a child class") def _get_split_name(self) -> list: """ Get split name (erasing empty strings in it by precaution, especially for S1 and S3 data) Returns: list: Split products name """ return [x for x in self.name.split("_") if x] @abstractmethod def get_datetime(self, as_datetime: bool = False) -> Union[str, dt.datetime]: """ Get the product's acquisition datetime, with format `YYYYMMDDTHHMMSS` <-> `%Y%m%dT%H%M%S` ```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 """ raise NotImplementedError("This method should be implemented by a child class") def get_date(self, as_date: bool = False) -> Union[str, dt.date]: """ Get the product's acquisition date. ```python >>> from eoreader.reader import Reader >>> path = r"S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE.zip" >>> prod = Reader().open(path) >>> prod.get_date(as_date=True) datetime.datetime(2020, 8, 24, 0, 0) >>> prod.get_date(as_date=False) '20200824' ``` Args: as_date (bool): Return the date as a datetime.date. If false, returns a string. Returns: str: Its acquisition date """ date = self.get_datetime().split("T")[0] if as_date: date = strings.str_to_date(date, date_format="%Y%m%d") return date @abstractmethod def get_default_band_path(self) -> str: """ Get default band path (among the existing ones). Usually `GREEN` band for optical data and the first existing one between `VV` and `HH` for SAR data. ```python >>> from eoreader.reader import Reader >>> path = r"S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE.zip" >>> prod = Reader().open(path) >>> prod.get_default_band_path() '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' ``` Returns: str: Default band path """ raise NotImplementedError("This method should be implemented by a child class") @abstractmethod def get_default_band(self) -> BandNames: """ Get default band: Usually `GREEN` band for optical data and the first existing one between `VV` and `HH` for SAR data. ```python >>> from eoreader.reader import Reader >>> path = r"S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE.zip" >>> prod = Reader().open(path) >>> prod.get_default_band() <OpticalBandNames.GREEN: 'GREEN'> ``` Returns: str: Default band """ raise NotImplementedError("This method should be implemented by a child class") def get_existing_bands(self) -> list: """ Return the existing bands. ```python >>> from eoreader.reader import Reader >>> path = r"S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE.zip" >>> prod = Reader().open(path) >>> prod.get_existing_bands() [<OpticalBandNames.CA: 'COASTAL_AEROSOL'>, <OpticalBandNames.BLUE: 'BLUE'>, <OpticalBandNames.GREEN: 'GREEN'>, <OpticalBandNames.RED: 'RED'>, <OpticalBandNames.VRE_1: 'VEGETATION_RED_EDGE_1'>, <OpticalBandNames.VRE_2: 'VEGETATION_RED_EDGE_2'>, <OpticalBandNames.VRE_3: 'VEGETATION_RED_EDGE_3'>, <OpticalBandNames.NIR: 'NIR'>, <OpticalBandNames.NNIR: 'NARROW_NIR'>, <OpticalBandNames.WV: 'WATER_VAPOUR'>, <OpticalBandNames.CIRRUS: 'CIRRUS'>, <OpticalBandNames.SWIR_1: 'SWIR_1'>, <OpticalBandNames.SWIR_2: 'SWIR_2'>] ``` Returns: list: List of existing bands in the products """ raise NotImplementedError("This method should be implemented by a child class") @abstractmethod def get_existing_band_paths(self) -> dict: """ Return the existing band paths. ```python >>> from eoreader.reader import Reader >>> path = r"S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE.zip" >>> prod = Reader().open(path) >>> prod.get_existing_band_paths() { <OpticalBandNames.CA: 'COASTAL_AEROSOL'>: '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_B01.jp2', ..., <OpticalBandNames.SWIR_2: 'SWIR_2'>: '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_B12.jp2' } ``` Returns: dict: Dictionary containing the path of each queried band """ raise NotImplementedError("This method should be implemented by a child class") def get_band_paths(self, band_list: list, resolution: float = None) -> dict: """ Return the paths of required bands. ```python >>> from eoreader.reader import Reader >>> from eoreader.bands.alias import * >>> path = r"S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE.zip" >>> prod = Reader().open(path) >>> prod.get_band_paths([GREEN, RED]) { <OpticalBandNames.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', <OpticalBandNames.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 resolution (float): Band resolution Returns: dict: Dictionary containing the path of each queried band """ raise NotImplementedError("This method should be implemented by a child class") @abstractmethod def read_mtd(self) -> Any: """ Read metadata and outputs the metadata XML root and its namespace most of the time, except from L8-collection 1 data which outputs a pandas DataFrame ```python >>> from eoreader.reader import Reader >>> path = r"S1A_IW_GRDH_1SDV_20191215T060906_20191215T060931_030355_0378F7_3696.zip" >>> prod = Reader().open(path) >>> prod.read_mtd() (<Element product at 0x1832895d788>, '') ``` Returns: Any: Metadata XML root and its namespace or pd.DataFrame """ raise NotImplementedError("This method should be implemented by a child class") # pylint: disable=W0613 @path_or_dst def _read_band( self, dataset, resolution: Union[tuple, list, float] = None, size: Union[list, tuple] = None, ) -> XDS_TYPE: """ Read band from disk. .. WARNING:: For optical data, invalid pixels are not managed here Args: dataset (Dataset): Band dataset resolution (Union[tuple, list, float]): Resolution of the wanted band, in dataset resolution unit (X, Y) size (Union[tuple, list]): Size of the array (width, height). Not used if resolution is provided. Returns: XDS_TYPE: Band xarray """ raise NotImplementedError("This method should be implemented by a child class") @abstractmethod def _load_bands( self, band_list: list, resolution: float = None, size: Union[list, tuple] = None ) -> dict: """ Load bands as numpy arrays with the same resolution (and same metadata). Args: band_list (list): List of the wanted bands resolution (int): Band resolution in meters size (Union[tuple, list]): Size of the array (width, height). Not used if resolution is provided. Returns: dict: Dictionary {band_name, band_xarray} """ raise NotImplementedError("This method should be implemented by a child class") def _load_dem( self, band_list: list, resolution: float = None, size: Union[list, tuple] = None ) -> dict: """ Load bands as numpy arrays with the same resolution (and same metadata). Args: band_list (list): List of the wanted bands resolution (int): Band resolution in meters size (Union[tuple, list]): Size of the array (width, height). Not used if resolution is provided. Returns: dict: Dictionary {band_name, band_xarray} """ dem_bands = {} if band_list: dem_path = os.environ.get(DEM_PATH) # We already checked if it exists for band in band_list: assert is_dem(band) if band == DEM: path = self._warp_dem(dem_path, resolution=resolution, size=size) elif band == SLOPE: path = self._compute_slope( dem_path, resolution=resolution, size=size ) elif band == HILLSHADE: path = self._compute_hillshade( dem_path, resolution=resolution, size=size ) else: raise InvalidTypeError(f"Unknown DEM band: {band}") dem_bands[band] = rasters.read(path, resolution=resolution, size=size) return dem_bands def load( self, bands: Union[list, BandNames, Callable], resolution: float = None, size: Union[list, tuple] = None, ) -> dict: """ Open the bands and compute the wanted index. The bands will be purged of nodata and invalid pixels, the nodata will be set to 0 and the bands will be masked arrays in float. Bands that come out this function at the same time are collocated and therefore have the same shapes. This can be broken if you load data separately. Its is best to always load DEM data with some real bands. ```python >>> from eoreader.reader import Reader >>> from eoreader.bands.alias import * >>> path = r"S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE.zip" >>> prod = Reader().open(path) >>> bands = prod.load([GREEN, NDVI], resolution=20) >>> bands ''' { <function NDVI at 0x000001EFFFF5DD08>: <xarray.DataArray 'NDVI' (band: 1, y: 5490, x: 5490)> array([[[0.949506 , 0.92181516, 0.9279379 , ..., 1.8002278 , 1.5424857 , 1.6747767 ], [0.95369846, 0.91685396, 0.8957871 , ..., 1.5847116 , 1.5248713 , 1.5011379 ], [2.9928885 , 1.3031474 , 1.0076253 , ..., 1.5969834 , 1.5590671 , 1.5018653 ], ..., [1.4245619 , 1.6115025 , 1.6201663 , ..., 1.2387121 , 1.4025431 , 1.800678 ], [1.5627214 , 1.822388 , 1.7245892 , ..., 1.1694248 , 1.2573677 , 1.5767351 ], [1.653781 , 1.6424649 , 1.5923225 , ..., 1.3072611 , 1.2181134 , 1.2478763 ]]], dtype=float32) Coordinates: * band (band) int32 1 * y (y) float64 4.5e+06 4.5e+06 4.5e+06 ... 4.39e+06 4.39e+06 * x (x) float64 2e+05 2e+05 2e+05 ... 3.097e+05 3.098e+05 3.098e+05 spatial_ref int32 0, <OpticalBandNames.GREEN: 'GREEN'>: <xarray.DataArray (band: 1, y: 5490, x: 5490)> array([[[0.0615 , 0.061625, 0.061 , ..., 0.12085 , 0.120225, 0.113575], [0.061075, 0.06045 , 0.06025 , ..., 0.114625, 0.119625, 0.117625], [0.06475 , 0.06145 , 0.060925, ..., 0.111475, 0.114925, 0.115175], ..., [0.1516 , 0.14195 , 0.1391 , ..., 0.159975, 0.14145 , 0.127075], [0.140325, 0.125975, 0.131875, ..., 0.18245 , 0.1565 , 0.13015 ], [0.133475, 0.1341 , 0.13345 , ..., 0.15565 , 0.170675, 0.16405 ]]], dtype=float32) Coordinates: * band (band) int32 1 * y (y) float64 4.5e+06 4.5e+06 4.5e+06 ... 4.39e+06 4.39e+06 * x (x) float64 2e+05 2e+05 2e+05 ... 3.097e+05 3.098e+05 3.098e+05 spatial_ref int32 0 } ''' ``` Args: bands (Union[list, BandNames, Callable]): Band list resolution (float): Resolution of the band, in meters size (Union[tuple, list]): Size of the array (width, height). Not used if resolution is provided. Returns: dict: {band_name, band xarray} """ if not resolution and not size: resolution = self.resolution # Check if all bands are valid if not isinstance(bands, list): bands = [bands] band_dict = self._load(bands, resolution, size) # Manage the case of arrays of different size -> collocate arrays if needed band_dict = self._collocate_bands(band_dict) # Convert to xarray dataset when all the bands have the same size # TODO: cannot convert as we have non-string index # xds = xr.Dataset(band_dict) # Sort bands to the asked order # xds.reindex({"band": bands}) return band_dict @abstractmethod def _load( self, bands: list, resolution: float = None, size: Union[list, tuple] = None ) -> dict: """ Core function loading data bands Args: bands (list): Band list resolution (float): Resolution of the band, in meters size (Union[tuple, list]): Size of the array (width, height). Not used if resolution is provided. Returns: Dictionary {band_name, band_xarray} """ raise NotImplementedError("This method should be implemented by a child class") def has_band(self, band: Union[BandNames, Callable]) -> bool: """ Does this products has the specified band ? By band, we mean: - satellite band - index - DEM band - cloud band ```python >>> from eoreader.reader import Reader >>> from eoreader.bands.alias import * >>> path = r"S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE.zip" >>> prod = Reader().open(path) >>> prod.has_band(GREEN) True >>> prod.has_band(TIR_2) False >>> prod.has_band(NDVI) True >>> prod.has_band(SHADOWS) False >>> prod.has_band(HILLSHADE) True ``` Args: band (Union[obn, sbn]): Optical or SAR band Returns: bool: True if the products has the specified band """ if is_dem(band): if self.sensor_type == SensorType.SAR and band == HILLSHADE: has_band = False else: has_band = True elif is_clouds(band): has_band = self._has_cloud_band(band) elif is_index(band): has_band = self._has_index(band) else: has_band = band in self.get_existing_bands() return has_band def _has_cloud_band(self, band: BandNames) -> bool: """ Does this products has the specified cloud band ? ```python >>> from eoreader.reader import Reader >>> from eoreader.bands.alias import * >>> path = r"S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE.zip" >>> prod = Reader().open(path) >>> prod.has_cloud_band(CLOUDS) True ``` """ raise NotImplementedError("This method should be implemented by a child class") def _has_index(self, idx: Callable) -> bool: """ Cen the specified index be computed from this products ? ```python >>> from eoreader.reader import Reader >>> from eoreader.bands.alias import * >>> path = r"S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE.zip" >>> prod = Reader().open(path) >>> prod.has_index(NDVI) True ``` Args: idx (Callable): Index Returns: bool: True if the specified index can be computed with this products's bands """ index_bands = index.get_needed_bands(idx) return all(np.isin(index_bands, self.get_existing_bands())) def __gt__(self, other: Product) -> bool: """ Overload greater than for eoreader -> compare the dates: The greater products is the one acquired the last. Args: other (Product): Other products to be compared with this one Returns: bool: True if this products has been acquired after the other """ return self.date > other.date def __ge__(self, other: Product) -> bool: """ Overload greater than for eoreader -> compare the dates: The greater products is the one acquired the last. Args: other (Product): Other products to be compared with this one Returns: bool: True if this products has been acquired after or in the same time than the other """ return self.date >= other.date def __eq__(self, other: Product) -> bool: """ Overload greater than for eoreader -> compare the dates: The greater products is the one acquired the last. Args: other (Product): Other products to be compared with this one Returns: bool: True if this products has been acquired in the same time than the other """ return self.date == other.date def __ne__(self, other: Product) -> bool: """ Overload greater than for eoreader -> compare the dates: The greater products is the one acquired the last. Args: other (Product): Other products to be compared with this one Returns: bool: True if this products has been acquired not in the same time than the other """ return self.date != other.date def __le__(self, other: Product) -> bool: """ Overload greater than for eoreader -> compare the dates: The greater products is the one acquired the last. Args: other (Product): Other products to be compared with this one Returns: bool: True if this products has been acquired before or in the same time than the other """ return self.date <= other.date def __lt__(self, other: Product) -> bool: """ Overload greater than for eoreader -> compare the dates: The greater products is the one acquired the last. Args: other (Product): Other products to be compared with this one Returns: bool: True if this products has been acquired before the other """ return self.date < other.date @property def output(self) -> str: """Output directory of the product, to write orthorectified data for example.""" return self._output @output.setter def output(self, value: str): """Output directory of the product, to write orthorectified data for example.""" self._output = value if not os.path.isdir(self._output): os.makedirs(self._output, exist_ok=True) def _warp_dem( self, dem_path: str = "", resolution: Union[float, tuple] = None, size: Union[list, tuple] = None, resampling: Resampling = Resampling.bilinear, ) -> str: """ Get this products DEM, warped to this products footprint and CRS. If no DEM is giving (or non existing or non intersecting the products): - Using EUDEM over Europe - Using MERIT DEM everwhere else ```python >>> from eoreader.reader import Reader >>> from eoreader.bands.alias import * >>> path = r"S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE.zip" >>> prod = Reader().open(path) >>> prod.warp_dem(resolution=20) # In meters '/path/to/20200824T110631_S2_T30TTK_L1C_150432_DEM.tif' ``` Args: dem_path (str): DEM path, using EUDEM/MERIT DEM if none resolution (Union[float, tuple]): Resolution in meters. If not specified, use the product resolution. resampling (Resampling): Resampling method size (Union[tuple, list]): Size of the array (width, height). Not used if resolution is provided. Returns: str: DEM path (as a VRT) """ warped_dem_path = os.path.join( self._get_band_folder(), f"{self.condensed_name}_DEM.tif" ) if os.path.isfile(warped_dem_path): LOGGER.debug("Already existing DEM for %s. Skipping process.", self.name) else: LOGGER.debug("Warping DEM for %s", self.name) # Check existence (SRTM) if not os.path.isfile(dem_path): raise FileNotFoundError(f"DEM file does not exist here: {dem_path}") # Reproject DEM into products CRS with rasterio.open(self.get_default_band_path()) as prod_dst: LOGGER.debug("Using DEM: %s", dem_path) with rasterio.open(dem_path) as dem_ds: # Get adjusted transform and shape (with new resolution) if size is not None and resolution is None: try: # Get destination transform out_h = size[1] out_w = size[0] # Get destination transform coeff_x = prod_dst.width / out_w coeff_y = prod_dst.height / out_h dst_tr = prod_dst.transform dst_tr *= dst_tr.scale(coeff_x, coeff_y) except (TypeError, KeyError): raise ValueError( f"Size should exist (as resolution is None)" f" and castable to a list: {size}" ) else: # Refine resolution if resolution is None: resolution = self.resolution res_x = ( resolution[0] if isinstance(resolution, (tuple, list)) else resolution ) res_y = ( resolution[1] if isinstance(resolution, (tuple, list)) else resolution ) # Get destination transform dst_tr = prod_dst.transform coeff_x = np.abs(res_x / dst_tr.a) coeff_y = np.abs(res_y / dst_tr.e) dst_tr *= dst_tr.scale(coeff_x, coeff_y) # Get destination transform out_w = int(np.round(prod_dst.width / coeff_x)) out_h = int(np.round(prod_dst.height / coeff_y)) # Get empty output reprojected_array = np.zeros( (prod_dst.count, out_h, out_w), dtype=np.float32 ) # Write reprojected DEM: here do not use utils.write() out_meta = prod_dst.meta.copy() out_meta["dtype"] = reprojected_array.dtype out_meta["transform"] = dst_tr out_meta["driver"] = "GTiff" out_meta["width"] = out_w out_meta["height"] = out_h with rasterio.open(warped_dem_path, "w", **out_meta) as out_dst: out_dst.write(reprojected_array) # Reproject warp.reproject( source=rasterio.band(dem_ds, range(1, dem_ds.count + 1)), destination=rasterio.band( out_dst, range(1, out_dst.count + 1) ), resampling=resampling, num_threads=MAX_CORES, ) return warped_dem_path @abstractmethod def _compute_hillshade( self, dem_path: str = "", resolution: Union[float, tuple] = None, size: Union[list, tuple] = None, resampling: Resampling = Resampling.bilinear, ) -> str: """ Compute Hillshade mask Args: dem_path (str): DEM path, using EUDEM/MERIT DEM if none resolution (Union[float, tuple]): Resolution in meters. If not specified, use the product resolution. size (Union[tuple, list]): Size of the array (width, height). Not used if resolution is provided. resampling (Resampling): Resampling method Returns: str: Hillshade mask path """ raise NotImplementedError("This method should be implemented by a child class") def _compute_slope( self, dem_path: str = "", resolution: Union[float, tuple] = None, size: Union[list, tuple] = None, resampling: Resampling = Resampling.bilinear, ) -> str: """ Compute slope mask Args: dem_path (str): DEM path, using EUDEM/MERIT DEM if none resolution (Union[float, tuple]): Resolution in meters. If not specified, use the product resolution. size (Union[tuple, list]): Size of the array (width, height). Not used if resolution is provided. resampling (Resampling): Resampling method Returns: str: Slope mask path """ # Warp DEM warped_dem_path = self._warp_dem(dem_path, resolution, size, resampling) # Get slope path slope_dem = os.path.join(self.output, f"{self.condensed_name}_SLOPE.tif") if os.path.isfile(slope_dem): LOGGER.debug( "Already existing slope DEM for %s. Skipping process.", self.name ) else: LOGGER.debug("Computing slope for %s", self.name) cmd_slope = [ "gdaldem", "--config", "NUM_THREADS", MAX_CORES, "slope", "-compute_edges", strings.to_cmd_string(warped_dem_path), strings.to_cmd_string(slope_dem), "-p", ] # Run command misc.run_cli(cmd_slope) return slope_dem @staticmethod def _collocate_bands(bands: dict, master_xds: XDS_TYPE = None) -> dict: """ Collocate all bands from a dict if needed (if a raster shape is different) Args: bands (dict): Dict of bands to collocate if needed Returns: dict: Collocated bands """ for band_id, band in bands.items(): if master_xds is None: master_xds = band # Master array is the first one in this case if band.shape != master_xds.shape: bands[band_id] = rasters.collocate( master_xds=master_xds, slave_xds=band ) bands[band_id] = bands[band_id].assign_coords( { "x": master_xds.x, "y": master_xds.y, } ) # Bug for now, tiny difference in coords return bands # pylint: disable=R0913 # Too many arguments (6/5) def stack( self, bands: list, resolution: float = None, stack_path: str = None, save_as_int: bool = False, ) -> xr.DataArray: """ Stack bands and index of a products. ```python >>> from eoreader.reader import Reader >>> from eoreader.bands.alias import * >>> path = r"S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE.zip" >>> prod = Reader().open(path) >>> stack = prod.stack([NDVI, MNDWI, GREEN], resolution=20) # In meters >>> stack ''' <xarray.DataArray 'NDVI_MNDWI_GREEN' (z: 3, y: 5490, x: 5490)> array([[[ 0.949506 , 0.92181516, 0.9279379 , ..., 1.8002278 , 1.5424857 , 1.6747767 ], [ 0.95369846, 0.91685396, 0.8957871 , ..., 1.5847116 , 1.5248713 , 1.5011379 ], [ 2.9928885 , 1.3031474 , 1.0076253 , ..., 1.5969834 , 1.5590671 , 1.5018653 ], ..., [ 1.4245619 , 1.6115025 , 1.6201663 , ..., 1.2387121 , 1.4025431 , 1.800678 ], [ 1.5627214 , 1.822388 , 1.7245892 , ..., 1.1694248 , 1.2573677 , 1.5767351 ], [ 1.653781 , 1.6424649 , 1.5923225 , ..., 1.3072611 , 1.2181134 , 1.2478763 ]], [[ 0.27066118, 0.23466069, 0.18792598, ..., -0.4611526 , -0.49751845, -0.4865216 ], [ 0.22425456, 0.28004232, 0.27851456, ..., -0.5032771 , -0.501796 , -0.502669 ], [-0.07466951, 0.06360884, 0.1207174 , ..., -0.50617427, -0.50219285, -0.5034222 ], [-0.47076276, -0.4705828 , -0.4747971 , ..., -0.32138503, -0.36619243, -0.37428448], [-0.4826967 , -0.5032287 , -0.48544118, ..., -0.278925 , -0.31404778, -0.36052078], [-0.488381 , -0.48253912, -0.4697526 , ..., -0.38105175, -0.30813277, -0.27739233]], [[ 0.0615 , 0.061625 , 0.061 , ..., 0.12085 , 0.120225 , 0.113575 ], [ 0.061075 , 0.06045 , 0.06025 , ..., 0.114625 , 0.119625 , 0.117625 ], [ 0.06475 , 0.06145 , 0.060925 , ..., 0.111475 , 0.114925 , 0.115175 ], ..., [ 0.1516 , 0.14195 , 0.1391 , ..., 0.159975 , 0.14145 , 0.127075 ], [ 0.140325 , 0.125975 , 0.131875 , ..., 0.18245 , 0.1565 , 0.13015 ], [ 0.133475 , 0.1341 , 0.13345 , ..., 0.15565 , 0.170675 , 0.16405 ]]], dtype=float32) Coordinates: * y (y) float64 4.5e+06 4.5e+06 4.5e+06 ... 4.39e+06 4.39e+06 * x (x) float64 2e+05 2e+05 2e+05 ... 3.097e+05 3.098e+05 3.098e+05 spatial_ref int32 0 * z (z) MultiIndex - variable (z) object 'NDVI' 'MNDWI' 'GREEN' - band (z) int64 1 1 1 -Attributes: long_name: ['NDVI', 'MNDWI', 'GREEN'] ''' ``` Args: bands (list): Bands and index combination resolution (float): Stack resolution. . If not specified, use the product resolution. stack_path (str): Stack path save_as_int (bool): Save stack as integers (uint16 and therefore multiply the values by 10.000) Returns: xr.DataArray: Stack as a DataArray """ if not resolution: resolution = self.resolution # Create the analysis stack band_dict = self.load(bands, resolution) # Convert into dataset with str as names xds = xr.Dataset( data_vars={to_str(key)[0]: val for key, val in band_dict.items()}, coords=band_dict[bands[0]].coords, ) # Force nodata stack = xds.to_stacked_array(new_dim="z", sample_dims=("x", "y")) stack = stack.transpose("z", "y", "x") # Save as integer if save_as_int: dtype = np.uint16 stack = (stack * 10000).astype(dtype) else: dtype = np.float32 stack = stack.astype(dtype) # Some updates stack = rasters.set_nodata(stack, self.nodata) band_list = to_str(list(band_dict.keys())) stack.attrs["long_name"] = band_list stack = stack.rename("_".join(band_list)) # Write on disk if stack_path: rasters.write(stack, stack_path, dtype=dtype) # Close datasets for val in band_dict.values(): val.close() return stack @staticmethod def _check_dem_path() -> None: """ Check if DEM is set and exists""" if DEM_PATH not in os.environ: raise ValueError( f"Dem path not set, unable to compute DEM bands! " f"Please set the environment variable {DEM_PATH}." ) else: dem_path = os.environ.get(DEM_PATH) if not os.path.isfile(dem_path): raise FileNotFoundError( f"{dem_path} is not a file! " f"Please set the environment variable {DEM_PATH} to an existing file." )
Subclasses
Instance variables
var output
-
Output directory of the product, to write orthorectified data for example.
Expand source code
@property def output(self) -> str: """Output directory of the product, to write orthorectified data for example.""" return self._output
var name
-
Product name (its filename without any extension).
var split_name
-
Split name, to retrieve every information from its filename (dates, tile, product type…).
var archive_path
-
Archive path, same as the product path if not specified. Useful when you want to know where both the extracted and archived version of your product are stored.
var path
-
Usable path to the product, either extracted or archived path, according to the satellite.
var is_archived
-
Is the archived product is processed (a products is considered as archived if its products path is a directory).
var needs_extraction
-
Does this products needs to be extracted to be processed ? (
True
by default). var date
-
Acquisition date.
var datetime
-
Acquisition datetime.
var tile_name
-
Tile if possible (for data that can be piled, for example S2 and Landsats).
var sensor_type
-
Sensor type, SAR or optical.
var product_type
-
Product type, satellite-related field, such as L1C or L2A for Sentinel-2 data.
var band_names
-
Band mapping between band wrapping names such as
GREEN
and band real number such as03
for Sentinel-2. var is_reference
-
If the product is a reference, used for algorithms that need pre and post data, such as fire detection.
var corresponding_ref
-
The corresponding reference products to the current one (if the product is not a reference but has a reference data corresponding to it). A list because of multiple ref in case of non-stackable products (S3, S1…)
var nodata
-
Product nodata, set to 0 by default. Please do not touch this or all index will fail.
var platform
-
Product platform, such as Sentinel-2
var resolution
-
Default resolution in meters of the current product. For SAR product, we use Ground Range resolution as we will automatically orthorectify the tiles.
var condensed_name
-
Condensed name, the filename with only useful data to keep the name unique (ie.
20191215T110441_S2_30TXP_L2A_122756
). Used to shorten names and paths. var sat_id
-
Satellite ID, i.e.
S2
for Sentinel-2
Methods
def footprint(
self)
-
Get UTM footprint of the products (without nodata, in french == emprise utile)
>>> from eoreader.reader import Reader >>> path = r"S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE.zip" >>> prod = Reader().open(path) >>> prod.footprint() index geometry 0 0 POLYGON ((199980.000 4500000.000, 199980.000 4...
Returns
gpd.GeoDataFrame
- Footprint as a GeoDataFrame
Expand source code
def footprint(self) -> gpd.GeoDataFrame: """ Get UTM footprint of the products (without nodata, *in french == emprise utile*) ```python >>> from eoreader.reader import Reader >>> path = r"S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE.zip" >>> prod = Reader().open(path) >>> prod.footprint() index geometry 0 0 POLYGON ((199980.000 4500000.000, 199980.000 4... ``` Returns: gpd.GeoDataFrame: Footprint as a GeoDataFrame """ def_band = self.get_default_band() default_xda = self.load(def_band)[ def_band ] # Forced to load as the nodata may not be positioned by default return rasters.get_footprint(default_xda)
def extent(
self)
-
Get UTM extent of the tile
>>> from eoreader.reader import Reader >>> path = r"S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE.zip" >>> prod = Reader().open(path) >>> prod.utm_extent() geometry 0 POLYGON ((309780.000 4390200.000, 309780.000 4...
Returns
gpd.GeoDataFrame
- Footprint in UTM
Expand source code
@abstractmethod def extent(self) -> gpd.GeoDataFrame: """ Get UTM extent of the tile ```python >>> from eoreader.reader import Reader >>> path = r"S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE.zip" >>> prod = Reader().open(path) >>> prod.utm_extent() geometry 0 POLYGON ((309780.000 4390200.000, 309780.000 4... ``` Returns: gpd.GeoDataFrame: Footprint in UTM """ raise NotImplementedError("This method should be implemented by a child class")
def crs(
self)
-
Get UTM projection of the tile
>>> from eoreader.reader import Reader >>> path = r"S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE.zip" >>> prod = Reader().open(path) >>> prod.utm_crs() CRS.from_epsg(32630)
Returns
crs.CRS
- CRS object
Expand source code
@abstractmethod def crs(self) -> riocrs.CRS: """ Get UTM projection of the tile ```python >>> from eoreader.reader import Reader >>> path = r"S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE.zip" >>> prod = Reader().open(path) >>> prod.utm_crs() CRS.from_epsg(32630) ``` Returns: crs.CRS: CRS object """ raise NotImplementedError("This method should be implemented by a child class")
def get_datetime(
self,
as_datetime=False)-
Get the product's acquisition datetime, with format
YYYYMMDDTHHMMSS
<->%Y%m%dT%H%M%S
>>> 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
Expand source code
@abstractmethod def get_datetime(self, as_datetime: bool = False) -> Union[str, dt.datetime]: """ Get the product's acquisition datetime, with format `YYYYMMDDTHHMMSS` <-> `%Y%m%dT%H%M%S` ```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 """ raise NotImplementedError("This method should be implemented by a child class")
def get_date(
self,
as_date=False)-
Get the product's acquisition date.
>>> from eoreader.reader import Reader >>> path = r"S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE.zip" >>> prod = Reader().open(path) >>> prod.get_date(as_date=True) datetime.datetime(2020, 8, 24, 0, 0) >>> prod.get_date(as_date=False) '20200824'
Args
as_date
:bool
- Return the date as a datetime.date. If false, returns a string.
Returns
str
- Its acquisition date
Expand source code
def get_date(self, as_date: bool = False) -> Union[str, dt.date]: """ Get the product's acquisition date. ```python >>> from eoreader.reader import Reader >>> path = r"S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE.zip" >>> prod = Reader().open(path) >>> prod.get_date(as_date=True) datetime.datetime(2020, 8, 24, 0, 0) >>> prod.get_date(as_date=False) '20200824' ``` Args: as_date (bool): Return the date as a datetime.date. If false, returns a string. Returns: str: Its acquisition date """ date = self.get_datetime().split("T")[0] if as_date: date = strings.str_to_date(date, date_format="%Y%m%d") return date
def get_default_band_path(
self)
-
Get default band path (among the existing ones).
Usually
GREEN
band for optical data and the first existing one betweenVV
andHH
for SAR data.>>> from eoreader.reader import Reader >>> path = r"S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE.zip" >>> prod = Reader().open(path) >>> prod.get_default_band_path() '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'
Returns
str
- Default band path
Expand source code
@abstractmethod def get_default_band_path(self) -> str: """ Get default band path (among the existing ones). Usually `GREEN` band for optical data and the first existing one between `VV` and `HH` for SAR data. ```python >>> from eoreader.reader import Reader >>> path = r"S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE.zip" >>> prod = Reader().open(path) >>> prod.get_default_band_path() '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' ``` Returns: str: Default band path """ raise NotImplementedError("This method should be implemented by a child class")
def get_default_band(
self)
-
Get default band: Usually
GREEN
band for optical data and the first existing one betweenVV
andHH
for SAR data.>>> from eoreader.reader import Reader >>> path = r"S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE.zip" >>> prod = Reader().open(path) >>> prod.get_default_band() <OpticalBandNames.GREEN: 'GREEN'>
Returns
str
- Default band
Expand source code
@abstractmethod def get_default_band(self) -> BandNames: """ Get default band: Usually `GREEN` band for optical data and the first existing one between `VV` and `HH` for SAR data. ```python >>> from eoreader.reader import Reader >>> path = r"S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE.zip" >>> prod = Reader().open(path) >>> prod.get_default_band() <OpticalBandNames.GREEN: 'GREEN'> ``` Returns: str: Default band """ raise NotImplementedError("This method should be implemented by a child class")
def get_existing_bands(
self)
-
Return the existing bands.
>>> from eoreader.reader import Reader >>> path = r"S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE.zip" >>> prod = Reader().open(path) >>> prod.get_existing_bands() [<OpticalBandNames.CA: 'COASTAL_AEROSOL'>, <OpticalBandNames.BLUE: 'BLUE'>, <OpticalBandNames.GREEN: 'GREEN'>, <OpticalBandNames.RED: 'RED'>, <OpticalBandNames.VRE_1: 'VEGETATION_RED_EDGE_1'>, <OpticalBandNames.VRE_2: 'VEGETATION_RED_EDGE_2'>, <OpticalBandNames.VRE_3: 'VEGETATION_RED_EDGE_3'>, <OpticalBandNames.NIR: 'NIR'>, <OpticalBandNames.NNIR: 'NARROW_NIR'>, <OpticalBandNames.WV: 'WATER_VAPOUR'>, <OpticalBandNames.CIRRUS: 'CIRRUS'>, <OpticalBandNames.SWIR_1: 'SWIR_1'>, <OpticalBandNames.SWIR_2: 'SWIR_2'>]
Returns
list
- List of existing bands in the products
Expand source code
def get_existing_bands(self) -> list: """ Return the existing bands. ```python >>> from eoreader.reader import Reader >>> path = r"S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE.zip" >>> prod = Reader().open(path) >>> prod.get_existing_bands() [<OpticalBandNames.CA: 'COASTAL_AEROSOL'>, <OpticalBandNames.BLUE: 'BLUE'>, <OpticalBandNames.GREEN: 'GREEN'>, <OpticalBandNames.RED: 'RED'>, <OpticalBandNames.VRE_1: 'VEGETATION_RED_EDGE_1'>, <OpticalBandNames.VRE_2: 'VEGETATION_RED_EDGE_2'>, <OpticalBandNames.VRE_3: 'VEGETATION_RED_EDGE_3'>, <OpticalBandNames.NIR: 'NIR'>, <OpticalBandNames.NNIR: 'NARROW_NIR'>, <OpticalBandNames.WV: 'WATER_VAPOUR'>, <OpticalBandNames.CIRRUS: 'CIRRUS'>, <OpticalBandNames.SWIR_1: 'SWIR_1'>, <OpticalBandNames.SWIR_2: 'SWIR_2'>] ``` Returns: list: List of existing bands in the products """ raise NotImplementedError("This method should be implemented by a child class")
def get_existing_band_paths(
self)
-
Return the existing band paths.
>>> from eoreader.reader import Reader >>> path = r"S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE.zip" >>> prod = Reader().open(path) >>> prod.get_existing_band_paths() { <OpticalBandNames.CA: 'COASTAL_AEROSOL'>: '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_B01.jp2', ..., <OpticalBandNames.SWIR_2: 'SWIR_2'>: '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_B12.jp2' }
Returns
dict
- Dictionary containing the path of each queried band
Expand source code
@abstractmethod def get_existing_band_paths(self) -> dict: """ Return the existing band paths. ```python >>> from eoreader.reader import Reader >>> path = r"S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE.zip" >>> prod = Reader().open(path) >>> prod.get_existing_band_paths() { <OpticalBandNames.CA: 'COASTAL_AEROSOL'>: '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_B01.jp2', ..., <OpticalBandNames.SWIR_2: 'SWIR_2'>: '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_B12.jp2' } ``` Returns: dict: Dictionary containing the path of each queried band """ raise NotImplementedError("This method should be implemented by a child class")
def get_band_paths(
self,
band_list,
resolution=None)-
Return the paths of required bands.
>>> from eoreader.reader import Reader >>> from eoreader.bands.alias import * >>> path = r"S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE.zip" >>> prod = Reader().open(path) >>> prod.get_band_paths([GREEN, RED]) { <OpticalBandNames.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', <OpticalBandNames.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
resolution
:float
- Band resolution
Returns
dict
- Dictionary containing the path of each queried band
Expand source code
def get_band_paths(self, band_list: list, resolution: float = None) -> dict: """ Return the paths of required bands. ```python >>> from eoreader.reader import Reader >>> from eoreader.bands.alias import * >>> path = r"S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE.zip" >>> prod = Reader().open(path) >>> prod.get_band_paths([GREEN, RED]) { <OpticalBandNames.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', <OpticalBandNames.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 resolution (float): Band resolution Returns: dict: Dictionary containing the path of each queried band """ raise NotImplementedError("This method should be implemented by a child class")
def read_mtd(
self)
-
Read metadata and outputs the metadata XML root and its namespace most of the time, except from L8-collection 1 data which outputs a pandas DataFrame
>>> from eoreader.reader import Reader >>> path = r"S1A_IW_GRDH_1SDV_20191215T060906_20191215T060931_030355_0378F7_3696.zip" >>> prod = Reader().open(path) >>> prod.read_mtd() (<Element product at 0x1832895d788>, '')
Returns
Any
- Metadata XML root and its namespace or pd.DataFrame
Expand source code
@abstractmethod def read_mtd(self) -> Any: """ Read metadata and outputs the metadata XML root and its namespace most of the time, except from L8-collection 1 data which outputs a pandas DataFrame ```python >>> from eoreader.reader import Reader >>> path = r"S1A_IW_GRDH_1SDV_20191215T060906_20191215T060931_030355_0378F7_3696.zip" >>> prod = Reader().open(path) >>> prod.read_mtd() (<Element product at 0x1832895d788>, '') ``` Returns: Any: Metadata XML root and its namespace or pd.DataFrame """ raise NotImplementedError("This method should be implemented by a child class")
def load(
self,
bands,
resolution=None,
size=None)-
Open the bands and compute the wanted index.
The bands will be purged of nodata and invalid pixels, the nodata will be set to 0 and the bands will be masked arrays in float.
Bands that come out this function at the same time are collocated and therefore have the same shapes. This can be broken if you load data separately. Its is best to always load DEM data with some real bands.
>>> from eoreader.reader import Reader >>> from eoreader.bands.alias import * >>> path = r"S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE.zip" >>> prod = Reader().open(path) >>> bands = prod.load([GREEN, NDVI], resolution=20) >>> bands ''' { <function NDVI at 0x000001EFFFF5DD08>: <xarray.DataArray 'NDVI' (band: 1, y: 5490, x: 5490)> array([[[0.949506 , 0.92181516, 0.9279379 , ..., 1.8002278 , 1.5424857 , 1.6747767 ], [0.95369846, 0.91685396, 0.8957871 , ..., 1.5847116 , 1.5248713 , 1.5011379 ], [2.9928885 , 1.3031474 , 1.0076253 , ..., 1.5969834 , 1.5590671 , 1.5018653 ], ..., [1.4245619 , 1.6115025 , 1.6201663 , ..., 1.2387121 , 1.4025431 , 1.800678 ], [1.5627214 , 1.822388 , 1.7245892 , ..., 1.1694248 , 1.2573677 , 1.5767351 ], [1.653781 , 1.6424649 , 1.5923225 , ..., 1.3072611 , 1.2181134 , 1.2478763 ]]], dtype=float32) Coordinates: * band (band) int32 1 * y (y) float64 4.5e+06 4.5e+06 4.5e+06 ... 4.39e+06 4.39e+06 * x (x) float64 2e+05 2e+05 2e+05 ... 3.097e+05 3.098e+05 3.098e+05 spatial_ref int32 0, <OpticalBandNames.GREEN: 'GREEN'>: <xarray.DataArray (band: 1, y: 5490, x: 5490)> array([[[0.0615 , 0.061625, 0.061 , ..., 0.12085 , 0.120225, 0.113575], [0.061075, 0.06045 , 0.06025 , ..., 0.114625, 0.119625, 0.117625], [0.06475 , 0.06145 , 0.060925, ..., 0.111475, 0.114925, 0.115175], ..., [0.1516 , 0.14195 , 0.1391 , ..., 0.159975, 0.14145 , 0.127075], [0.140325, 0.125975, 0.131875, ..., 0.18245 , 0.1565 , 0.13015 ], [0.133475, 0.1341 , 0.13345 , ..., 0.15565 , 0.170675, 0.16405 ]]], dtype=float32) Coordinates: * band (band) int32 1 * y (y) float64 4.5e+06 4.5e+06 4.5e+06 ... 4.39e+06 4.39e+06 * x (x) float64 2e+05 2e+05 2e+05 ... 3.097e+05 3.098e+05 3.098e+05 spatial_ref int32 0 } '''
Args
bands
:Union[list, BandNames, Callable]
- Band list
resolution
:float
- Resolution of the band, in meters
size
:Union[tuple, list]
- Size of the array (width, height). Not used if resolution is provided.
Returns
dict
- {band_name, band xarray}
Expand source code
def load( self, bands: Union[list, BandNames, Callable], resolution: float = None, size: Union[list, tuple] = None, ) -> dict: """ Open the bands and compute the wanted index. The bands will be purged of nodata and invalid pixels, the nodata will be set to 0 and the bands will be masked arrays in float. Bands that come out this function at the same time are collocated and therefore have the same shapes. This can be broken if you load data separately. Its is best to always load DEM data with some real bands. ```python >>> from eoreader.reader import Reader >>> from eoreader.bands.alias import * >>> path = r"S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE.zip" >>> prod = Reader().open(path) >>> bands = prod.load([GREEN, NDVI], resolution=20) >>> bands ''' { <function NDVI at 0x000001EFFFF5DD08>: <xarray.DataArray 'NDVI' (band: 1, y: 5490, x: 5490)> array([[[0.949506 , 0.92181516, 0.9279379 , ..., 1.8002278 , 1.5424857 , 1.6747767 ], [0.95369846, 0.91685396, 0.8957871 , ..., 1.5847116 , 1.5248713 , 1.5011379 ], [2.9928885 , 1.3031474 , 1.0076253 , ..., 1.5969834 , 1.5590671 , 1.5018653 ], ..., [1.4245619 , 1.6115025 , 1.6201663 , ..., 1.2387121 , 1.4025431 , 1.800678 ], [1.5627214 , 1.822388 , 1.7245892 , ..., 1.1694248 , 1.2573677 , 1.5767351 ], [1.653781 , 1.6424649 , 1.5923225 , ..., 1.3072611 , 1.2181134 , 1.2478763 ]]], dtype=float32) Coordinates: * band (band) int32 1 * y (y) float64 4.5e+06 4.5e+06 4.5e+06 ... 4.39e+06 4.39e+06 * x (x) float64 2e+05 2e+05 2e+05 ... 3.097e+05 3.098e+05 3.098e+05 spatial_ref int32 0, <OpticalBandNames.GREEN: 'GREEN'>: <xarray.DataArray (band: 1, y: 5490, x: 5490)> array([[[0.0615 , 0.061625, 0.061 , ..., 0.12085 , 0.120225, 0.113575], [0.061075, 0.06045 , 0.06025 , ..., 0.114625, 0.119625, 0.117625], [0.06475 , 0.06145 , 0.060925, ..., 0.111475, 0.114925, 0.115175], ..., [0.1516 , 0.14195 , 0.1391 , ..., 0.159975, 0.14145 , 0.127075], [0.140325, 0.125975, 0.131875, ..., 0.18245 , 0.1565 , 0.13015 ], [0.133475, 0.1341 , 0.13345 , ..., 0.15565 , 0.170675, 0.16405 ]]], dtype=float32) Coordinates: * band (band) int32 1 * y (y) float64 4.5e+06 4.5e+06 4.5e+06 ... 4.39e+06 4.39e+06 * x (x) float64 2e+05 2e+05 2e+05 ... 3.097e+05 3.098e+05 3.098e+05 spatial_ref int32 0 } ''' ``` Args: bands (Union[list, BandNames, Callable]): Band list resolution (float): Resolution of the band, in meters size (Union[tuple, list]): Size of the array (width, height). Not used if resolution is provided. Returns: dict: {band_name, band xarray} """ if not resolution and not size: resolution = self.resolution # Check if all bands are valid if not isinstance(bands, list): bands = [bands] band_dict = self._load(bands, resolution, size) # Manage the case of arrays of different size -> collocate arrays if needed band_dict = self._collocate_bands(band_dict) # Convert to xarray dataset when all the bands have the same size # TODO: cannot convert as we have non-string index # xds = xr.Dataset(band_dict) # Sort bands to the asked order # xds.reindex({"band": bands}) return band_dict
def has_band(
self,
band)-
Does this products has the specified band ?
By band, we mean:
- satellite band
- index
- DEM band
- cloud band
>>> from eoreader.reader import Reader >>> from eoreader.bands.alias import * >>> path = r"S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE.zip" >>> prod = Reader().open(path) >>> prod.has_band(GREEN) True >>> prod.has_band(TIR_2) False >>> prod.has_band(NDVI) True >>> prod.has_band(SHADOWS) False >>> prod.has_band(HILLSHADE) True
Args
band
:Union[obn, sbn]
- Optical or SAR band
Returns
bool
- True if the products has the specified band
Expand source code
def has_band(self, band: Union[BandNames, Callable]) -> bool: """ Does this products has the specified band ? By band, we mean: - satellite band - index - DEM band - cloud band ```python >>> from eoreader.reader import Reader >>> from eoreader.bands.alias import * >>> path = r"S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE.zip" >>> prod = Reader().open(path) >>> prod.has_band(GREEN) True >>> prod.has_band(TIR_2) False >>> prod.has_band(NDVI) True >>> prod.has_band(SHADOWS) False >>> prod.has_band(HILLSHADE) True ``` Args: band (Union[obn, sbn]): Optical or SAR band Returns: bool: True if the products has the specified band """ if is_dem(band): if self.sensor_type == SensorType.SAR and band == HILLSHADE: has_band = False else: has_band = True elif is_clouds(band): has_band = self._has_cloud_band(band) elif is_index(band): has_band = self._has_index(band) else: has_band = band in self.get_existing_bands() return has_band
def stack(
self,
bands,
resolution=None,
stack_path=None,
save_as_int=False)-
Stack bands and index of a products.
>>> from eoreader.reader import Reader >>> from eoreader.bands.alias import * >>> path = r"S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE.zip" >>> prod = Reader().open(path) >>> stack = prod.stack([NDVI, MNDWI, GREEN], resolution=20) # In meters >>> stack ''' <xarray.DataArray 'NDVI_MNDWI_GREEN' (z: 3, y: 5490, x: 5490)> array([[[ 0.949506 , 0.92181516, 0.9279379 , ..., 1.8002278 , 1.5424857 , 1.6747767 ], [ 0.95369846, 0.91685396, 0.8957871 , ..., 1.5847116 , 1.5248713 , 1.5011379 ], [ 2.9928885 , 1.3031474 , 1.0076253 , ..., 1.5969834 , 1.5590671 , 1.5018653 ], ..., [ 1.4245619 , 1.6115025 , 1.6201663 , ..., 1.2387121 , 1.4025431 , 1.800678 ], [ 1.5627214 , 1.822388 , 1.7245892 , ..., 1.1694248 , 1.2573677 , 1.5767351 ], [ 1.653781 , 1.6424649 , 1.5923225 , ..., 1.3072611 , 1.2181134 , 1.2478763 ]], [[ 0.27066118, 0.23466069, 0.18792598, ..., -0.4611526 , -0.49751845, -0.4865216 ], [ 0.22425456, 0.28004232, 0.27851456, ..., -0.5032771 , -0.501796 , -0.502669 ], [-0.07466951, 0.06360884, 0.1207174 , ..., -0.50617427, -0.50219285, -0.5034222 ], [-0.47076276, -0.4705828 , -0.4747971 , ..., -0.32138503, -0.36619243, -0.37428448], [-0.4826967 , -0.5032287 , -0.48544118, ..., -0.278925 , -0.31404778, -0.36052078], [-0.488381 , -0.48253912, -0.4697526 , ..., -0.38105175, -0.30813277, -0.27739233]], [[ 0.0615 , 0.061625 , 0.061 , ..., 0.12085 , 0.120225 , 0.113575 ], [ 0.061075 , 0.06045 , 0.06025 , ..., 0.114625 , 0.119625 , 0.117625 ], [ 0.06475 , 0.06145 , 0.060925 , ..., 0.111475 , 0.114925 , 0.115175 ], ..., [ 0.1516 , 0.14195 , 0.1391 , ..., 0.159975 , 0.14145 , 0.127075 ], [ 0.140325 , 0.125975 , 0.131875 , ..., 0.18245 , 0.1565 , 0.13015 ], [ 0.133475 , 0.1341 , 0.13345 , ..., 0.15565 , 0.170675 , 0.16405 ]]], dtype=float32) Coordinates: * y (y) float64 4.5e+06 4.5e+06 4.5e+06 ... 4.39e+06 4.39e+06 * x (x) float64 2e+05 2e+05 2e+05 ... 3.097e+05 3.098e+05 3.098e+05 spatial_ref int32 0 * z (z) MultiIndex - variable (z) object 'NDVI' 'MNDWI' 'GREEN' - band (z) int64 1 1 1 -Attributes: long_name: ['NDVI', 'MNDWI', 'GREEN'] '''
Args
bands
:list
- Bands and index combination
resolution
:float
- Stack resolution. . If not specified, use the product resolution.
stack_path
:str
- Stack path
save_as_int
:bool
- Save stack as integers (uint16 and therefore multiply the values by 10.000)
Returns
xr.DataArray
- Stack as a DataArray
Expand source code
def stack( self, bands: list, resolution: float = None, stack_path: str = None, save_as_int: bool = False, ) -> xr.DataArray: """ Stack bands and index of a products. ```python >>> from eoreader.reader import Reader >>> from eoreader.bands.alias import * >>> path = r"S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE.zip" >>> prod = Reader().open(path) >>> stack = prod.stack([NDVI, MNDWI, GREEN], resolution=20) # In meters >>> stack ''' <xarray.DataArray 'NDVI_MNDWI_GREEN' (z: 3, y: 5490, x: 5490)> array([[[ 0.949506 , 0.92181516, 0.9279379 , ..., 1.8002278 , 1.5424857 , 1.6747767 ], [ 0.95369846, 0.91685396, 0.8957871 , ..., 1.5847116 , 1.5248713 , 1.5011379 ], [ 2.9928885 , 1.3031474 , 1.0076253 , ..., 1.5969834 , 1.5590671 , 1.5018653 ], ..., [ 1.4245619 , 1.6115025 , 1.6201663 , ..., 1.2387121 , 1.4025431 , 1.800678 ], [ 1.5627214 , 1.822388 , 1.7245892 , ..., 1.1694248 , 1.2573677 , 1.5767351 ], [ 1.653781 , 1.6424649 , 1.5923225 , ..., 1.3072611 , 1.2181134 , 1.2478763 ]], [[ 0.27066118, 0.23466069, 0.18792598, ..., -0.4611526 , -0.49751845, -0.4865216 ], [ 0.22425456, 0.28004232, 0.27851456, ..., -0.5032771 , -0.501796 , -0.502669 ], [-0.07466951, 0.06360884, 0.1207174 , ..., -0.50617427, -0.50219285, -0.5034222 ], [-0.47076276, -0.4705828 , -0.4747971 , ..., -0.32138503, -0.36619243, -0.37428448], [-0.4826967 , -0.5032287 , -0.48544118, ..., -0.278925 , -0.31404778, -0.36052078], [-0.488381 , -0.48253912, -0.4697526 , ..., -0.38105175, -0.30813277, -0.27739233]], [[ 0.0615 , 0.061625 , 0.061 , ..., 0.12085 , 0.120225 , 0.113575 ], [ 0.061075 , 0.06045 , 0.06025 , ..., 0.114625 , 0.119625 , 0.117625 ], [ 0.06475 , 0.06145 , 0.060925 , ..., 0.111475 , 0.114925 , 0.115175 ], ..., [ 0.1516 , 0.14195 , 0.1391 , ..., 0.159975 , 0.14145 , 0.127075 ], [ 0.140325 , 0.125975 , 0.131875 , ..., 0.18245 , 0.1565 , 0.13015 ], [ 0.133475 , 0.1341 , 0.13345 , ..., 0.15565 , 0.170675 , 0.16405 ]]], dtype=float32) Coordinates: * y (y) float64 4.5e+06 4.5e+06 4.5e+06 ... 4.39e+06 4.39e+06 * x (x) float64 2e+05 2e+05 2e+05 ... 3.097e+05 3.098e+05 3.098e+05 spatial_ref int32 0 * z (z) MultiIndex - variable (z) object 'NDVI' 'MNDWI' 'GREEN' - band (z) int64 1 1 1 -Attributes: long_name: ['NDVI', 'MNDWI', 'GREEN'] ''' ``` Args: bands (list): Bands and index combination resolution (float): Stack resolution. . If not specified, use the product resolution. stack_path (str): Stack path save_as_int (bool): Save stack as integers (uint16 and therefore multiply the values by 10.000) Returns: xr.DataArray: Stack as a DataArray """ if not resolution: resolution = self.resolution # Create the analysis stack band_dict = self.load(bands, resolution) # Convert into dataset with str as names xds = xr.Dataset( data_vars={to_str(key)[0]: val for key, val in band_dict.items()}, coords=band_dict[bands[0]].coords, ) # Force nodata stack = xds.to_stacked_array(new_dim="z", sample_dims=("x", "y")) stack = stack.transpose("z", "y", "x") # Save as integer if save_as_int: dtype = np.uint16 stack = (stack * 10000).astype(dtype) else: dtype = np.float32 stack = stack.astype(dtype) # Some updates stack = rasters.set_nodata(stack, self.nodata) band_list = to_str(list(band_dict.keys())) stack.attrs["long_name"] = band_list stack = stack.rename("_".join(band_list)) # Write on disk if stack_path: rasters.write(stack, stack_path, dtype=dtype) # Close datasets for val in band_dict.values(): val.close() return stack