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vlt Launches "reproduce": A New Tool Challenging the Limits of Package Provenance
vlt's new "reproduce" tool verifies npm packages against their source code, outperforming traditional provenance adoption in the JavaScript ecosystem.
An Xarray extension for Google Earth Engine.
Install with pip:
pip install --upgrade xee
Install with conda:
conda install -c conda-forge xee
Then, authenticate Earth Engine:
earthengine authenticate --quiet
Now, in your Python environment, make the following imports:
import ee
import xarray
Next, specify your EE-registered cloud project ID and initialize the EE client with the high volume API:
ee.Initialize(
project='my-project-id'
opt_url='https://earthengine-highvolume.googleapis.com')
Open any Earth Engine ImageCollection by specifying the Xarray engine as 'ee'
:
ds = xarray.open_dataset('ee://ECMWF/ERA5_LAND/HOURLY', engine='ee')
Open all bands in a specific projection (not the Xee default):
ds = xarray.open_dataset('ee://ECMWF/ERA5_LAND/HOURLY', engine='ee',
crs='EPSG:4326', scale=0.25)
Open an ImageCollection (maybe, with EE-side filtering or processing):
ic = ee.ImageCollection('ECMWF/ERA5_LAND/HOURLY').filterDate('1992-10-05', '1993-03-31')
ds = xarray.open_dataset(ic, engine='ee', crs='EPSG:4326', scale=0.25)
Open an ImageCollection with a specific EE projection or geometry:
ic = ee.ImageCollection('ECMWF/ERA5_LAND/HOURLY').filterDate('1992-10-05', '1993-03-31')
leg1 = ee.Geometry.Rectangle(113.33, -43.63, 153.56, -10.66)
ds = xarray.open_dataset(
ic,
engine='ee',
projection=ic.first().select(0).projection(),
geometry=leg1
)
Open multiple ImageCollections into one xarray.Dataset
, all with the same projection:
ds = xarray.open_mfdataset(['ee://ECMWF/ERA5_LAND/HOURLY', 'ee://NASA/GDDP-CMIP6'],
engine='ee', crs='EPSG:4326', scale=0.25)
Open a single Image by passing it to an ImageCollection:
i = ee.ImageCollection(ee.Image("LANDSAT/LC08/C02/T1_TOA/LC08_044034_20140318"))
ds = xarray.open_dataset(i, engine='ee')
Open any Earth Engine ImageCollection to match an existing transform:
raster = rioxarray.open_rasterio(...) # assume crs + transform is set
ds = xr.open_dataset(
'ee://ECMWF/ERA5_LAND/HOURLY',
engine='ee',
geometry=tuple(raster.rio.bounds()), # must be in EPSG:4326
projection=ee.Projection(
crs=str(raster.rio.crs), transform=raster.rio.transform()[:6]
),
)
See examples or docs for more uses and integrations.
If you encounter issues using Xee, you can:
The Xee integration tests only pass on Xee branches (no forks). Please run the
integration tests locally before sending a PR. To run the tests locally,
authenticate using earthengine authenticate
and run the following:
USE_ADC_CREDENTIALS=1 python -m unittest xee/ext_integration_test.py
This is not an official Google product.
Copyright 2023 Google LLC
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
https://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.
FAQs
A Google Earth Engine extension for Xarray.
We found that xee demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 5 open source maintainers collaborating on the project.
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