Skip to main content

Creator for Analysis Ready Data (ARD)

Project description

cedar - Create Earth engine Data cubes of Analytical Readiness

cedar is a library and application to help download and preprocess satellite data to be “analysis ready data” (ARD) “data cube” as quickly as possible. cedar has been designed primarily to preprocess Landsat data, and can help acquire data from the Google Earth Engine (GEE). It is based on tools within the Python ecosystem for geospatial data processing (rasterio), saving and working with N-dimensional data (netCDF4 and xarray), and parallelization (dask and distributed).

Branch

Tests

Coverage

Docs

master

Continuous integration test status

Test coverage

Documentation

Change Log

All notable changes will appear in this log.

For information on the style of this change log, see keepachangelog.com.

v0.0.4

  • Fixed bug in cedar clean command

  • The cedar convert program will now copy “pre-ARD” image metadata JSON files to the destination directory alongside the “pre-ARD” images (GeoTIFFs converted to NetCDF files). To prevent this behavior, pass --skip-metadata to the program.

  • Changes were made in where exceptions are handled for the case where a user requests a “pre-ARD” image that returns 0 search results (e.g., wrong time period for sensor, bad historic coverage, etc). By default, Order.add will not raise an EmptyCollectionError when you try to add a “pre-ARD” image that had 0 image results. You can force an error to be raised by setting error_if_empty=True in either Order.add or Tracker.submit.

v0.0.3

  • BREAKING CHANGE - Require image collection filters to be specified in the configuration file according to the image collection. This change has been made to prepare for using image collections that do not have the same filters (e.g., more than just LANDSAT/*/C01/T1_SR data)

  • Add a check to make sure that Order.name_template creates unique names for pre-ARD before continuing. If there are duplicate names, raises ValueError

  • Fix warning when calculating mean/std runtime of tasks that haven’t been updated (RuntimeWarning: Mean of empty slice…)

  • Provide better info in cedar status list when nothing is tracked because the tracking folder doesn’t exist

  • Fix bug when ordering but not using filters that resulted in 0 images being found

  • Validate image collection names using click argument callback in cedar submit CLI

  • Improve error propagation inside cedar.ordering.Order and cedar.tracker.Tracker. Order.add no longer catches and swallows EmptyCollectionError, which now is handled in Tracker.submit

v0.0.2

  • Fix bug in jsonschema validation by allowing tuples & lists to count as ‘array’

  • Added cedar status cancel command to cancel orders

  • Refactor internals to use TrackingMetadata model

v0.0.1.post1

  • Fix packaging issue (missing package data)

v0.0.1.post0

  • Fix packaging issue

v0.0.1

  • First public release

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

cedar-datacube-0.0.4.tar.gz (142.4 kB view hashes)

Uploaded Source

Built Distribution

cedar_datacube-0.0.4-py3-none-any.whl (64.9 kB view hashes)

Uploaded Python 3

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page