Source code for eoreader.products.sar.capella_product

# -*- coding: utf-8 -*-
# Copyright 2023, SERTIT-ICube - France,
# This file is part of eoreader project
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
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# distributed under the License is distributed on an "AS IS" BASIS,
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Capella products.
Take a look
`here <>`_.
import logging
from datetime import datetime
from enum import unique
from pathlib import Path
from typing import Union

import geopandas as gpd
from affine import Affine
from cloudpathlib import CloudPath
from dicttoxml import dicttoxml
from lxml import etree
from rasterio import CRS, transform
from sertit import files, vectors
from sertit.misc import ListEnum
from sertit.vectors import WGS84
from shapely.geometry import Point, box

from eoreader import DATETIME_FMT, EOREADER_NAME, cache
from eoreader.bands import SarBandNames as sab
from eoreader.exceptions import InvalidProductError
from eoreader.products import SarProduct, SarProductType
from eoreader.products.product import OrbitDirection

LOGGER = logging.getLogger(EOREADER_NAME)

[docs]@unique class CapellaProductType(ListEnum): """ Capella products types. Take a look `here <>`_. """ SLC = "SLC" """ Single Look Complex (SLC) - Contains both amplitude and phase of the radar signal - Range-compressed and focused SAR image in slant-range geometry - Georeferenced using orbit data and Range-Doppler projected """ GEC = "GEC" """ Geocoded Ellipsoid Corrected (GEC) - Contains amplitude information only - Range-compressed, detected, focused and multi-looked SAR image - Multi-look techniques applied to enhance radiometric resolution - Resampled and projected onto WGS84 ellipsoid with average scene center height - Universal Transverse Mercator (UTM) and Universal Polar Stereographic (UPS) projections """ GEO = "GEO" """ Geocoded Terrain Corrected (GEO) - Contains amplitude information only - Range-compressed, detected, focused and multi-looked SAR image - Multi-look techniques applied to enhance radiometric resolution - Terrain-height corrected using a high-resolution Digital Elevation Model (DEM) - Universal Transverse Mercator (UTM) and Universal Polar Stereographic (UPS) projections """ SICD = "SICD" """ Sensor Independent Complex Data (SICD) - Contains both amplitude and phase of the radar signal - Range-compressed and focused SAR image in slant-range geometry - Sensor independent format Not used by EOReader. """ SIDD = "SIDD" """ Sensor Independent Derived Data (SIDD) - Contains amplitude information only - Range-compressed, detected, focused and multi-looked SAR image - Multi-look techniques applied to enhance radiometric resolution - Planar Gridded Display (PGD) projection - Sensor independent format Not used by EOReader. """ CPHD = "CPHD" """ Compensated Phase History Data (CPHD) - Contains raw phase history data that is compensated for hardware timing & platform motion - Sensor independent format - Only available to United States Government customers Not used by EOReader. """
[docs]@unique class CapellaSensorMode(ListEnum): """ Capella imaging mode. Take a look `here <>`_. """ SM = "stripmap" """Stripmap""" SP = "spotlight" """Spotlight""" SS = "sliding_spotlight" """Sliding Spotlight"""
[docs]class CapellaProduct(SarProduct): """ Class for Capella Products Take a look `here <>`_. """
[docs] def __init__( self, product_path: Union[str, CloudPath, Path], archive_path: Union[str, CloudPath, Path] = None, output_path: Union[str, CloudPath, Path] = None, remove_tmp: bool = False, **kwargs, ) -> None: self._has_stac_mtd = False # Initialization from the super class super().__init__(product_path, archive_path, output_path, remove_tmp, **kwargs)
def _set_pixel_size(self) -> None: """ Set product default pixel size (in meters) See here `here <>`_ """ # Using az resolution if self.sensor_mode == CapellaSensorMode.SP: def_pixel_size = 0.35 def_res = 0.5 elif self.sensor_mode == CapellaSensorMode.SM: def_pixel_size = 0.6 def_res = 1.0 elif self.sensor_mode == CapellaSensorMode.SS: def_pixel_size = 0.8 def_res = 1.2 else: raise InvalidProductError(f"Unknown sensor mode: {self.sensor_mode}") self.pixel_size = def_pixel_size self.resolution = def_res def _set_instrument(self) -> None: """ Set instrument ICEYE: """ self.instrument = "SAR X-band" def _pre_init(self, **kwargs) -> None: """ Function used to pre_init the products (setting needs_extraction and so on) """ self._band_folder = self.path # SNAP cannot process its archive self.needs_extraction = True # Its original filename is its name self._use_filename = True # Post init done by the super class super()._pre_init(**kwargs) def _post_init(self, **kwargs) -> None: """ Function used to post_init the products (setting product-type, band names and so on) """ # Private attributes self.snap_filename = str(next(self.path.glob("*CAPELLA*.json")).name) self._raw_band_regex = f"{}.tif" # Post init done by the super class super()._post_init(**kwargs)
[docs] @cache def wgs84_extent(self) -> gpd.GeoDataFrame: """ Get the WGS84 extent of the file before any reprojection. This is useful when the SAR pre-process has not been done yet. .. code-block:: python >>> from eoreader.reader import Reader >>> path = r"1011117-766193" >>> prod = Reader().open(path) >>> prod.wgs84_extent() geometry 0 POLYGON ((108.09797 15.61011, 108.48224 15.678... Returns: gpd.GeoDataFrame: WGS84 extent as a gpd.GeoDataFrame """ if self._has_stac_mtd: mtd_file = next(self.path.glob(f"{}.json")) extent = else: extent = None root, _ = self.read_mtd() # Get image size height = int(root.findtext(".//rows")) width = int(root.findtext(".//columns")) # Investigate image geometry img_geom = root.find(".//image_geometry") geom_type = img_geom.findtext("type") # Use given geotransform if existing if geom_type == "geotransform": tf = [ float(it.text) for it in img_geom.find("geotransform").iterfind("item") ] # TODO: manage not WKT case crs = img_geom.find("coordinate_system").findtext("wkt") if crs: # Convert to rasterio west, south, east, north = transform.array_bounds( height, width, transform=Affine.from_gdal(*tf) ) extent = gpd.GeoDataFrame( geometry=[box(minx=west, miny=north, maxx=east, maxy=south)], crs=CRS.from_string(crs), ) # Use center pixel if extent is None: # Get center pixel point in UTM center_pixel = root.find(".//center_pixel") target_position = [ float(it.text) for it in center_pixel.find("target_position").iterfind("item") ] center_pix = gpd.GeoDataFrame( geometry=[Point(target_position)], crs={"proj": "geocent", "ellps": "WGS84", "datum": "WGS84"}, ).to_crs(WGS84) center_pix.to_crs(center_pix.extent_wgs84.estimate_utm_crs()) # Get pixel spacing in meters pixel_spacing_h = float(root.findtext(".//pixel_spacing_row")) pixel_spacing_w = float(root.findtext(".//pixel_spacing_column")) # Compute offset from center of image offset_h = pixel_spacing_h * height / 2 offset_w = pixel_spacing_w * width / 2 tl_corner = center_pix.translate(xoff=-offset_w, yoff=-offset_h) br_corner = center_pix.translate(xoff=offset_w, yoff=offset_h) extent = gpd.GeoDataFrame( geometry=[ box( minx=tl_corner.x.iat[0], miny=tl_corner.y.iat[0], maxx=br_corner.x.iat[0], maxy=br_corner.y.iat[0], ) ], crs=CRS.from_string(, ) return extent.to_crs(WGS84)
def _set_product_type(self) -> None: """Set products type""" # Open identifier prod_type = self.split_name[3] self.product_type = getattr(CapellaProductType, prod_type) if self.product_type in [CapellaProductType.GEO, CapellaProductType.GEC]: self.sar_prod_type = SarProductType.GDRG elif self.product_type == CapellaProductType.SLC: self.sar_prod_type = SarProductType.CPLX else: raise NotImplementedError( f"{self.product_type.value} product type is not handled by EOReader" ) def _set_sensor_mode(self) -> None: """Get sensor mode""" sensor_mode = self.split_name[2] self.sensor_mode = getattr(CapellaSensorMode, sensor_mode)
[docs] def get_datetime(self, as_datetime: bool = False) -> Union[str, datetime]: """ Get the product's acquisition datetime, with format :code:`YYYYMMDDTHHMMSS` <-> :code:`%Y%m%dT%H%M%S` .. code-block:: python >>> from eoreader.reader import Reader >>> path = r"1011117-766193" >>> prod = Reader().open(path) >>> prod.get_datetime(as_datetime=True) datetime.datetime(2020, 10, 28, 22, 46, 25) >>> prod.get_datetime(as_datetime=False) '20201028T224625' Args: as_datetime (bool): Return the date as a datetime.datetime. If false, returns a string. Returns: Union[str, datetime.datetime]: Its acquisition datetime """ if self.datetime is None: # Get MTD XML file root, _ = self.read_mtd() # Open identifier if self._has_stac_mtd: acq_date = root.findtext(".//datetime") else: acq_date = root.findtext(".//start_timestamp") if not acq_date: raise InvalidProductError( "datetime or start_timestamp not found in metadata!" ) # Convert to datetime (too many microseconds) date = datetime.strptime(acq_date.split(".")[0], "%Y-%m-%dT%H:%M:%S") else: date = self.datetime if not as_datetime: date = date.strftime(DATETIME_FMT) return date
def _get_name_constellation_specific(self) -> str: """ Set product real name from metadata Returns: str: True name of the product (from metadata) """ name = None for file in self.path.glob("*.tif"): if "preview" not in name = files.get_filename(file) return name @cache def _read_mtd(self) -> (etree._Element, dict): """ Read GeoJSON metadata and outputs its as a metadata XML root and its namespaces as an empty dict Returns: (etree._Element, dict): Metadata XML root and its namespaces as a dict """ # MTD are JSON try: try: mtd_file = next(self.path.glob(f"{}.json")) self._has_stac_mtd = True except StopIteration: try: LOGGER.warning( f"Non available STAC metadata for the product {}. Opening Extended Metadata instead." ) mtd_file = next(self.path.glob(f"{}*.json")) self._has_stac_mtd = False except StopIteration as ex: raise InvalidProductError( f"Metadata file not found in {self.path}" ) from ex data = files.read_json(mtd_file, print_file=False) root = etree.fromstring(dicttoxml(data)) except etree.XMLSyntaxError: raise InvalidProductError( f"Cannot convert metadata to XML for {self.path}!" ) return root, {}
[docs] def get_raw_band_paths(self, **kwargs) -> dict: """ Return the existing path of the VV band (as they come with the archived products). ICEYE product only contains a VV band ! Args: **kwargs: Additional arguments Returns: dict: Dictionary containing the path of every band existing in the raw products """ band_paths = {} try: pol = sab.from_value(self.split_name[4]) band_paths[pol] = files.get_file_in_dir( self._band_folder, self._raw_band_regex, exact_name=True, get_list=False ) except FileNotFoundError: raise InvalidProductError( "An ICEYE product should at least contain one band !" ) return band_paths
[docs] def get_quicklook_path(self) -> str: """ Get quicklook path if existing. Returns: str: Quicklook path """ quicklook_path = None try: quicklook_path = str(next(self.path.glob("*.png"))) except StopIteration: LOGGER.warning(f"No quicklook found in {self.condensed_name}") return quicklook_path
# @cache
[docs] def get_orbit_direction(self) -> OrbitDirection: """ Get cloud cover as given in the metadata .. code-block:: python >>> from eoreader.reader import Reader >>> path = r"" >>> prod = Reader().open(path) >>> prod.get_orbit_direction().value "DESCENDING" Returns: OrbitDirection: Orbit direction (ASCENDING/DESCENDING) """ ob = None if self._has_stac_mtd: root, _ = self.read_mtd() ob = root.findtext(".//key[@name='sat:orbit_state']") ob = OrbitDirection.from_value(ob.upper()) if ob is None: ob = super().get_orbit_direction() return ob