EMODnet Bathymetry — European high-resolution DTM (OGC WCS)¶

Fetch a small EMODnet Bathymetry Digital Terrain Model (DTM) subset over a North Sea AOI, map the sea-floor depth, and see how the European DTM complements the global GEBCO / ETOPO grids. Unlike the ERDDAP griddap DEMs, EMODnet is read over OGC WCS through pyramids.Dataset.from_wcs — earthlens supplies only the coverage id, AOI, CRS, and protocol version, and never touches a competing array stack.

Setup¶

earthlens provides the unified EarthLens entry point; pyramids reads the written GeoTIFF; downloads go to a temporary directory.

In [ ]:

import tempfile

import matplotlib.pyplot as plt
import numpy as np
from pyramids.dataset import Dataset

from earthlens.bathymetry import Catalog
from earthlens.core import EarthLens

import tempfile import matplotlib.pyplot as plt import numpy as np from pyramids.dataset import Dataset from earthlens.bathymetry import Catalog from earthlens.core import EarthLens

The EMODnet rows in the catalog¶

The bathymetry catalog carries the latest EMODnet release as emodnet plus year-stamped older releases. Each is a wcs-transport row pointing at the EMODnet Bathymetry OGC WCS. Reading the catalog is offline.

In [ ]:

catalog = Catalog()
for dataset_id in sorted(d for d in catalog.datasets if d.startswith('emodnet')):
    row = catalog.get(dataset_id)
    print(f'{dataset_id:14} transport={row.transport:4} coverage={row.dataset_id}')

catalog = Catalog() for dataset_id in sorted(d for d in catalog.datasets if d.startswith('emodnet')): row = catalog.get(dataset_id) print(f'{dataset_id:14} transport={row.transport:4} coverage={row.dataset_id}')

Download an EMODnet subset over WCS¶

Build the request — the bathymetry source, the emodnet dataset, and a small North Sea AOI (aoi is [min_lon, min_lat, max_lon, max_lat]). download() issues the WCS GetCoverage, crops to the AOI, and returns the written GeoTIFF path(s).

In [ ]:

out = tempfile.mkdtemp()
paths = EarthLens(
    data_source='bathymetry',
    dataset='emodnet',
    aoi=[2.0, 53.0, 4.0, 55.0],
    path=out,
).download(progress_bar=False)
paths

out = tempfile.mkdtemp() paths = EarthLens( data_source='bathymetry', dataset='emodnet', aoi=[2.0, 53.0, 4.0, 55.0], path=out, ).download(progress_bar=False) paths

Read and map the sea floor¶

Read the GeoTIFF with pyramids and map the mean depth — every value in this all-water AOI is below sea level, so the depths are negative (metres).

In [ ]:

ds = Dataset.read_file(str(paths[0]))
arr = np.asarray(ds.read_array(), dtype='float32')
arr = arr[0] if arr.ndim == 3 else arr
print(
    'epsg',
    ds.epsg,
    '| shape',
    arr.shape,
    '| depth range',
    round(float(np.nanmin(arr))),
    '..',
    round(float(np.nanmax(arr))),
    'm',
)

ds = Dataset.read_file(str(paths[0])) arr = np.asarray(ds.read_array(), dtype='float32') arr = arr[0] if arr.ndim == 3 else arr print( 'epsg', ds.epsg, '| shape', arr.shape, '| depth range', round(float(np.nanmin(arr))), '..', round(float(np.nanmax(arr))), 'm', )

In [ ]:

plt.figure(figsize=(6, 5))
plt.imshow(arr, cmap='Blues_r')
plt.colorbar(label='mean depth (m, negative = below sea level)')
plt.title('EMODnet Bathymetry DTM (~3.75″) — southern North Sea')
plt.axis('off')
plt.show()

plt.figure(figsize=(6, 5)) plt.imshow(arr, cmap='Blues_r') plt.colorbar(label='mean depth (m, negative = below sea level)') plt.title('EMODnet Bathymetry DTM (~3.75″) — southern North Sea') plt.axis('off') plt.show()

European coverage — when to reach for a global DEM¶

EMODnet covers European seas and the extended NE-Atlantic domain, advertised as the native_bbox below (west, south, east, north). A request whose bbox extends beyond it warns that out-of-coverage cells come back as 0.0 fill, and a request entirely outside raises — pointing you at the global gebco_2020 / etopo1_ice DEMs for those areas.

In [ ]:

row = catalog.get('emodnet')
print('coverage extent (W, S, E, N):', row.native_bbox)
print('for areas outside it, use dataset="gebco_2020" or "etopo1_ice"')

row = catalog.get('emodnet') print('coverage extent (W, S, E, N):', row.native_bbox) print('for areas outside it, use dataset="gebco_2020" or "etopo1_ice"')

Attribution¶

• EMODnet Bathymetry — EMODnet Digital Bathymetry (DTM 2024), EMODnet Bathymetry Consortium (doi:10.12770/cf51df64-56f9-4a99-b1aa-36b8d7b743a1).

Provided under the EMODnet use conditions (attribution required). A DEM is a static grid with no time axis, so download(aggregate=...) is rejected.