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This file contains a Copernicus Data Space Ecosystem data extraction class
for downloading satellite data
"""
########################################## Import dependencies #######################################################
import os
import json
import yaml
import inspect
import shutil
import re
import requests
from datetime import datetime, timedelta
from typing import List, Optional, Tuple
from oauthlib.oauth2 import BackendApplicationClient
from requests_oauthlib import OAuth2Session
from sentinelhub import bbox_to_dimensions, BBox
from io import BytesIO
import rasterio
from PIL import Image
import numpy as np
class CopernicusDataExtractor:
"""
A class for extracting satellite data from Copernicus Data Space Ecosystem.
This class uses the Copernicus SentinelHub Process API with OAuth2 authentication
to download processed satellite data with custom evalscripts.
Attributes:
parameters (dict): User input configurations
oauth_session (OAuth2Session): Authenticated OAuth2 session
consortium (str): the consortium for which we are downloading the data
timespan (list): Start and end date for data request
bbox (list): Region of Interest coordinates [min_lon, min_lat, max_lon, max_lat]
image_dimensions (tuple): Width and height in pixels. To keep previous imagery (requested using SH last year, we use SH bbox to dimensions method)
output_folder (str): dir location where to save retrieved data
datetimes (list): List of timestamps when satellite scanned ROI
evalscript (str): JavaScript evaluation script for processing
response_type (str): Type of output (rgb_nir, vi_values, s1_vv)
obtained_data (list): List of bands/indices in output
Methods:
__authenticate_copernicus: Authenticate with Copernicus OAuth2
_calculate_dimensions: Calculate image dimensions from bbox and resolution
_get_timestamps: Get available acquisition timestamps using Catalog API
_build_process_request: Build Process API request payload
_download_single_acquisition: Download data for one timestamp
data_request: Main method to download all data
set_evalscript: Change evalscript type
"""
def __init__(self, consortium = 'consortium0', evalscript='default_evalscript.js', crs = 'EPSG:4326'):
"""
Initialize the Copernicus Data Extractor.
Args:
evalscript (str): Name of the evalscript file to use for processing
"""
# our parameters
with open('config/pre_anonym_params.yml', 'r') as f:
self.parameters = yaml.safe_load(f)
# auth and create OAuth session
self.oauth_session = self.__authenticate_copernicus()
self.consortium = consortium.lower()
self.timespan = [self.parameters['start_date'], self.parameters['end_date']]
self.bbox = self.parameters['bbox'][self.consortium] # [min_lon, min_lat, max_lon, max_lat]
#self.image_dimensions = self._calculate_dimensions()
# keep previous method to mantain pixel placement and allignment w/ previously downloaded data
self.image_dimensions = bbox_to_dimensions(BBox(self.bbox, crs=crs), resolution=self.parameters['resolution'])
# output folder based on consortium
self.output_folder = os.path.join( os.getcwd() ,
"data", "01_raw",
self.parameters['consortia_data_folders'][self.consortium],
"satellite_data"
)
self.datetimes = []
# selected evalscript load
self.set_evalscript(evalscript)
def __authenticate_copernicus(self) -> OAuth2Session:
"""
Authenticate with Copernicus Data Space Ecosystem using OAuth2.
Returns:
OAuth2Session: Authenticated session with automatic token handling
Raises:
RuntimeError: If authentication fails
"""
# load OAuth credentials
with open('config/copernicus_oauth_config.json', 'r') as f:
oauth_credentials = json.load(f)
client_id = oauth_credentials['client_id']
client_secret = oauth_credentials['client_secret']
try:
# init OAuth2 session
client = BackendApplicationClient(client_id=client_id)
oauth = OAuth2Session(client=client)
# get token
token_url = 'https://identity.dataspace.copernicus.eu/auth/realms/CDSE/protocol/openid-connect/token'
token = oauth.fetch_token(
token_url=token_url,
client_secret=client_secret,
include_client_id=True
)
print('✓ Successfully authenticated with Copernicus Data Space Ecosystem.')
print(f'✓ Process API endpoint: https://sh.dataspace.copernicus.eu')
return oauth
except Exception as e:
raise RuntimeError(f"Copernicus authentication failed: {e}")
# to mantain previous pixel placement, for now we use SH method instead of running ours
def _calculate_dimensions(self) -> Tuple[int, int]:
"""
Calculate image dimensions from bbox and resolution.
Returns:
tuple: (width, height) in pixels
"""
from math import cos, radians
resolution = self.parameters.get('resolution', 10) # meters
# calculate width and height in meters (approximate)
min_lon, min_lat, max_lon, max_lat = self.bbox
# width at the center latitude
center_lat = (min_lat + max_lat) / 2
width_m = (max_lon - min_lon) * 111320 * cos(radians(center_lat))
height_m = (max_lat - min_lat) * 110540
# to pixels
width_px = int(width_m / resolution)
height_px = int(height_m / resolution)
return (width_px, height_px)
def _get_timestamps(self, timespan: Optional[List[str]] = None) -> List[str]:
"""
Get available satellite acquisition timestamps using STAC Catalog API.
Args:
timespan (list, optional): [start_date, end_date] in 'YYYY-MM-DD' format
Returns:
list: List of datetime strings
"""
if timespan:
if isinstance(timespan, list) and len(timespan) == 2:
self.timespan = timespan
print(f'New timespan: {timespan[0]} to {timespan[1]}')
else:
timespan = self.timespan
# through Copernicus STAC Catalog API
#catalog_url = "https://catalogue.dataspace.copernicus.eu/stac/search"
# this is the sentinelhub catalogue version. requires diff setup(way cloudcover eo is given if not sentinel1) and token in header
# also datetimespan is differently given
catalog_url = "https://sh.dataspace.copernicus.eu/api/v1/catalog/1.0.0/search"
# parse cloud cover
cloud_cover_max = 100
if 'cloud_cover' in self.parameters:
try:
cloud_str = self.parameters['cloud_cover']
cloud_cover_max = int(re.search(r'(\d+)', cloud_str).group(1))
except:
pass
stac_collection = self.parameters['collection']
# build STAC request
stac_request = {
"collections": [stac_collection],
"bbox": self.bbox,
"datetime": f"{self.timespan[0]}T00:00:00Z/{self.timespan[1]}T23:59:59Z",
#"datetime": [
# f"{self.timespan[0]}T00:00:00Z",
# f"{self.timespan[1]}T23:59:59Z"
#],
"limit": 100
}
# + cloud cover filter for optical data
#if 'sentinel1' not in self.parameters['collection'].lower():
# stac_request["query"] = {
# "eo:cloud_cover": {
# "lt": cloud_cover_max
# }
# }
if 'sentinel1' not in self.parameters['collection'].lower():
stac_request["filter"] = {
"op": "<",
"args": [
{"property": "eo:cloud_cover"},
cloud_cover_max
]
}
stac_request["filter-lang"] = "cql2-json"
try:
headers = {
"Authorization": f"Bearer {self.oauth_session.token['access_token']}"
}
all_features = []
next_token = None
while True:
req_payload = stac_request.copy()
if next_token is not None:
req_payload["next"] = next_token
response = requests.post(catalog_url, json=req_payload, timeout=30, headers=headers)
response.raise_for_status()
results = response.json()
# accumulate features
all_features.extend(results.get("features", []))
# check pagination token
context = results.get("context", {})
next_token = context.get("next")
if not next_token:
break
# timestamps
self.datetimes = [f['properties']['datetime'] for f in all_features]
print(f"✓ Found {len(self.datetimes)} acquisitions in timespan")
return self.datetimes
except requests.exceptions.HTTPError as e:
print(f'✗ Catalog search failed: {e}')
if hasattr(e.response, 'text'):
print(f' Response: {e.response.text[:300]}')
return []
except Exception as e:
print(f'✗ Catalog search failed: {e}')
return []
def _build_process_request(self, time_range: Tuple[str, str]) -> dict:
"""
Build Process API request payload.
Args:
time_range (tuple): (start_time, end_time) for the request
Returns:
dict: Request payload for Process API
"""
# map collection names to Process API types
#collection_map = {
# 'SENTINEL2_L2A': 'sentinel-2-l2a',
# 'SENTINEL2_L1C': 'sentinel-2-l1c',
# 'SENTINEL1_IW': 'sentinel-1-grd',
# 'SENTINEL1': 'sentinel-1-grd',
#}
process_collection = self.parameters['collection']
request = {
"input": {
"bounds": {
"properties": {"crs": "http://www.opengis.net/def/crs/OGC/1.3/CRS84"},
"bbox": self.bbox,
},
"data": [
{
"type": process_collection,
"dataFilter": {
"timeRange": {
"from": time_range[0],
"to": time_range[1],
}
},
}
],
},
"output": {
"width": self.image_dimensions[0],
"height": self.image_dimensions[1],
"responses": [
{
"identifier": self.response_type,
"format": {"type": "image/tiff"}
}
]
},
"evalscript": self.evalscript,
}
# + mosaicking order for optical data
if 'sentinel1' not in self.parameters['collection'].lower():
request["input"]["data"][0]["processing"] = {
"mosaickingOrder": "leastCC" # Least cloud cover
}
return request
# originally tried using STAC (was giving some probs), changed to sh catalog
def _download_single_acquisition(self, datetime_str: str, index: int, total: int) -> Optional[str]:
"""
Download data for a single acquisition.
Args:
datetime_str (str): Acquisition datetime
index (int): Current acquisition number
total (int): Total number of acquisitions
Returns:
str: Filename if successful, None otherwise
"""
print(f'\n[{index}/{total}] Processing: {datetime_str}')
# from datetime to date range (full day)
dt = datetime.fromisoformat(datetime_str.replace('Z', '+00:00'))
date_start = dt.date().strftime('%Y-%m-%d')
date_end = (dt.date() + timedelta(days=1)).strftime('%Y-%m-%d')
time_range = (f"{date_start}T00:00:00Z", f"{date_end}T00:00:00Z")
# build request
request_payload = self._build_process_request(time_range)
# call Process API
process_url = "https://sh.dataspace.copernicus.eu/api/v1/process"
try:
response = self.oauth_session.post(process_url, json=request_payload, timeout=120)
response.raise_for_status()
# save the TIFF!
output_dir = os.path.join(
os.path.dirname(os.path.abspath(inspect.getfile(inspect.currentframe()))),
self.output_folder
)
os.makedirs(output_dir, exist_ok=True)
# map collection names to Process API types
# save with this to keep previous nomenclature
collection_map = {
'sentinel-2-l2a': 'SENTINEL2_L2A',
'sentinel-2-l1c': 'SENTINEL2_L1C',
#'sentinel-1-grd': 'SENTINEL1_IW',
'sentinel-1-grd': 'SENTINEL1',
}
filename = f"{self.consortium}_{self.response_type}_{collection_map[self.parameters['collection']]}_{(datetime_str.split('.')[0] + 'Z').replace(':', '_')}.tiff"
output_path = os.path.join(output_dir, filename)
self._save_tiff_with_metadata(response.content, output_path)
print(f' ✓ Saved: {filename}')
return filename
except requests.exceptions.HTTPError as e:
print(f' ✗ HTTP Error: {e}')
if hasattr(e.response, 'text'):
print(f' Response: {e.response.text}')
# for debug: print the request payload
if e.response.status_code == 400:
print(f' Request payload was:')
print(f' Collection type: {request_payload["input"]["data"][0]["type"]}')
return None
except Exception as e:
print(f' ✗ Download failed: {e}')
return None
def _save_tiff_with_metadata(self, content: bytes, output_path: str):
"""
Save TIFF content with corrected metadata.
Args:
content (bytes): Raw TIFF data from API
output_path (str): Path to save corrected TIFF
"""
# Read from memory
with rasterio.open(BytesIO(content)) as src:
data = src.read()
profile = src.profile.copy()
# Fix metadata
profile.update({
'photometric': 'MINISBLACK',
'compress': 'deflate',
'interleave': 'band',
})
if 'extra_samples' in profile:
del profile['extra_samples']
# Write to disk with fixed metadata
with rasterio.open(output_path, 'w', **profile) as dst:
dst.write(data)
def data_request(self, timespan: Optional[List[str]] = None):
"""
Request and download satellite data for all available timestamps.
Args:
timespan (list, optional): [start_date, end_date] to override configured timespan
"""
print("\n" + "="*70)
print("COPERNICUS DATA EXTRACTION - Process API")
print("="*70)
# get available timestamps
if timespan:
timestamps = self._get_timestamps(timespan)
else:
timestamps = getattr(self, 'datetimes', [])
if not timestamps:
print('\n✗ No data available for the specified timespan and parameters.')
return
# download each acquisition
successful = 0
failed = 0
for i, dt in enumerate(timestamps, 1):
result = self._download_single_acquisition(dt, i, len(timestamps))
if result:
successful += 1
else:
failed += 1
# summary
print("\n" + "="*70)
print(f"SUMMARY: {successful} successful, {failed} failed out of {len(timestamps)} total")
print("="*70 + "\n")
def set_evalscript(self, new_evalscript: str):
"""
Load and set a new evaluation script for data processing.
Args:
new_evalscript (str): Filename of the evalscript in 'request_scripts' directory
"""
evalscript_path = os.path.join('config/request_scripts', new_evalscript)
with open(evalscript_path, 'r') as evalscript_file:
self.evalscript = evalscript_file.read()
# set response type based on evalscript
if new_evalscript == 'default_evalscript.js':
self.response_type = "rgb_nir"
self.obtained_data = ['red', 'green', 'blue', 'nir']
elif new_evalscript == 'sentinel1_evalscript.js':
self.response_type = "s1_vv"
self.obtained_data = ['vv']
else:
self.response_type = "vi_values"
# extract band/index names from evalscript
pattern = re.compile(r"(?:rgb_nir|vi_values|s1_vv):\s*\[([^\]]+)\]", re.DOTALL)
match = pattern.search(self.evalscript)
if match:
vi_values_content = match.group(1)
self.obtained_data = [value.strip() for value in vi_values_content.split(",")]
else:
self.obtained_data = []
print(f'✓ Evalscript set to: {new_evalscript}')
print(f' Response type: {self.response_type}')
print(f' Output layers: {len(self.obtained_data)}')
# Example usage
if __name__ == '__main__':
# init extractor with vegetation indices evalscript
extractor = CopernicusDataExtractor(evalscript='vis_evalscript.js')
# available timestamps test
timestamps = extractor._get_timestamps(timespan=['2023-12-29','2023-12-30'])
print(f'\nAvailable acquisitions: {len(timestamps)}')
# download data test and check in comparison with the one available before
extractor.data_request(['2025-01-29', '2025-01-30'])
print(f'\nObtained data layers: {extractor.obtained_data}')
print(f'\nObtained data layers: {extractor.obtained_data}') |