93 lines
3.1 KiB
Python
93 lines
3.1 KiB
Python
import os
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from pathlib import Path
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from datetime import datetime
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from dotenv import load_dotenv
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import openeo
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import requests
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import netCDF4
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import numpy as np
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import rasterio
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from rasterio.transform import from_bounds
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load_dotenv()
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datetime_range = "2024-01-01/2024-01-03"
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lon, lat = 11.320308, 47.116171
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bbox_size = 0.009
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bbox = [lon - bbox_size/2, lat - bbox_size/2, lon + bbox_size/2, lat + bbox_size/2]
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bands = {"SDR_Oa04": "blue", "SDR_Oa06": "green", "SDR_Oa08": "red", "SDR_Oa17": "nir"}
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output_dir = Path("data/innsbruck/2024/s3/")
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output_dir.mkdir(parents=True, exist_ok=True)
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band_map = {"SDR_Oa04": "B04", "SDR_Oa06": "B06", "SDR_Oa08": "B08", "SDR_Oa17": "B17"}
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openeo_bands = [band_map.get(b, b) for b in bands.keys()]
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start_date, end_date = datetime_range.split("/")
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spatial_extent = {
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"west": bbox[0], "east": bbox[2],
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"south": bbox[1], "north": bbox[3]
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}
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token_response = requests.post(
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"https://identity.dataspace.copernicus.eu/auth/realms/CDSE/protocol/openid-connect/token",
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data={
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"grant_type": "password",
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"username": os.getenv("CDSE_USER"),
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"password": os.getenv("CDSE_PASSWORD"),
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"client_id": "cdse-public"
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}
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)
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token_response.raise_for_status()
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tokens = token_response.json()
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access_token = tokens["access_token"]
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conn = openeo.connect("openeo.dataspace.copernicus.eu")
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conn.authenticate_oidc_access_token(access_token)
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datacube = conn.load_collection(
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"SENTINEL3_OLCI_L1B",
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spatial_extent=spatial_extent,
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temporal_extent=[start_date, end_date],
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bands=openeo_bands,
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).resample_spatial(projection=32632)
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output_file = output_dir / "s3_data.nc"
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datacube.download(str(output_file), format="NetCDF")
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nc = netCDF4.Dataset(str(output_file), 'r')
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times = netCDF4.num2date(nc.variables['t'][:], nc.variables['t'].units)
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x_coords = nc.variables['x'][:]
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y_coords = nc.variables['y'][:]
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band_vars = sorted([v for v in nc.variables.keys() if v.startswith('B') and v[1:].isdigit()])
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band_names = [list(bands.keys())[openeo_bands.index(b)] for b in band_vars]
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transform = from_bounds(
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float(x_coords.min()), float(y_coords.min()),
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float(x_coords.max()), float(y_coords.max()),
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len(x_coords), len(y_coords)
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)
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date_counts = {}
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for t_idx, time_val in enumerate(times):
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dt = time_val if isinstance(time_val, datetime) else netCDF4.num2date(nc.variables['t'][t_idx], nc.variables['t'].units)
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date_str = dt.strftime("%Y%m%d")
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increment = date_counts.get(date_str, 0)
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date_counts[date_str] = increment + 1
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band_data = [nc.variables[b][t_idx, :, :] for b in band_vars]
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stacked = np.stack(band_data, axis=0)
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output_path = output_dir / f"{date_str}_{increment}.geotiff"
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with rasterio.open(
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output_path, 'w',
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driver='GTiff', height=len(y_coords), width=len(x_coords),
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count=len(band_data), dtype=stacked.dtype, crs='EPSG:32632',
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transform=transform, compress='lzw'
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) as dst:
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dst.write(stacked)
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for i, band_name in enumerate(band_names, 1):
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dst.set_band_description(i, band_name)
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print(f"Saved: {output_path}")
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nc.close()
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os.remove(output_file)
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