geedim


Namegeedim JSON
Version 1.7.2 PyPI version JSON
download
home_pagehttps://github.com/leftfield-geospatial/geedim
SummarySearch, composite and download Google Earth Engine imagery.
upload_time2023-06-10 19:54:07
maintainer
docs_urlNone
authorDugal Harris
requires_python>=3.6
licenseApache-2.0
keywords earth engine satellite imagery search download composite cloud shadow
VCS
bugtrack_url
requirements No requirements were recorded.
Travis-CI No Travis.
coveralls test coverage No coveralls.
            |Tests| |codecov| |PyPI version| |conda-forge version| |docs| |License|

``geedim``
==========

.. short_descr_start

Search, composite, and download `Google Earth Engine <https://earthengine.google.com/>`__ imagery, without size limits.

.. short_descr_end

.. description_start

Description
-----------

``geedim`` provides a command line interface and API for searching, compositing and downloading satellite imagery
from Google Earth Engine (EE). It optionally performs cloud/shadow masking, and cloud/shadow-free compositing on
supported collections. Images and composites can be downloaded; or exported to Google Drive, Earth Engine asset or
Google Cloud Storage. Images larger than the
`EE size limit <https://developers.google.com/earth-engine/apidocs/ee-image-getdownloadurl>`_ are split and downloaded
as separate tiles, then re-assembled into a single GeoTIFF.

.. description_end

See the documentation site for more detail: https://geedim.readthedocs.io/.

.. supp_im_start

Cloud/shadow support
~~~~~~~~~~~~~~~~~~~~

Any EE imagery can be searched, composited and downloaded by ``geedim``. Cloud/shadow masking, and cloud/shadow-free
compositing are supported on the following collections:

.. supp_im_end

+------------------------------------------+-------------------------------------------------------+
| EE name                                  | Description                                           |
+==========================================+=======================================================+
| `LANDSAT/LT04/C02/T1_L2                  | Landsat 4, collection 2, tier 1, level 2 surface      |
| <https://developers.google.com/earth-eng | reflectance.                                          |
| ine/datasets/catalog/LANDSAT_LT04_C02_T1 |                                                       |
| _L2>`_                                   |                                                       |
+------------------------------------------+-------------------------------------------------------+
| `LANDSAT/LT05/C02/T1_L2                  | Landsat 5, collection 2, tier 1, level 2 surface      |
| <https://developers.google.com/earth-eng | reflectance.                                          |
| ine/datasets/catalog/LANDSAT_LT05_C02_T1 |                                                       |
| _L2>`_                                   |                                                       |
+------------------------------------------+-------------------------------------------------------+
| `LANDSAT/LE07/C02/T1_L2                  | Landsat 7, collection 2, tier 1, level 2 surface      |
| <https://developers.google.com/earth-eng | reflectance.                                          |
| ine/datasets/catalog/LANDSAT_LE07_C02_T1 |                                                       |
| _L2>`_                                   |                                                       |
+------------------------------------------+-------------------------------------------------------+
| `LANDSAT/LC08/C02/T1_L2                  | Landsat 8, collection 2, tier 1, level 2 surface      |
| <https://developers.google.com/earth-eng | reflectance.                                          |
| ine/datasets/catalog/LANDSAT_LC08_C02_T1 |                                                       |
| _L2>`_                                   |                                                       |
+------------------------------------------+-------------------------------------------------------+
| `LANDSAT/LC09/C02/T1_L2                  | Landsat 9, collection 2, tier 1, level 2 surface      |
| <https://developers.google.com/earth-eng | reflectance.                                          |
| ine/datasets/catalog/LANDSAT_LC09_C02_T1 |                                                       |
| _L2>`_                                   |                                                       |
+------------------------------------------+-------------------------------------------------------+
| `COPERNICUS/S2                           | Sentinel-2, level 1C, top of atmosphere reflectance.  |
| <https://developers.google.com/earth-    |                                                       |
| engine/datasets/catalog/COPERNICUS_S2>`_ |                                                       |
+------------------------------------------+-------------------------------------------------------+
| `COPERNICUS/S2_SR                        | Sentinel-2, level 2A, surface reflectance.            |
| <https://developers.google.com/earth-eng |                                                       |
| ine/datasets/catalog/COPERNICUS_S2_SR>`_ |                                                       |
+------------------------------------------+-------------------------------------------------------+
| `COPERNICUS/S2_HARMONIZED                | Harmonised Sentinel-2, level 1C, top of atmosphere    |
| <https://developers.google.com/earth-eng | reflectance.                                          |
| ine/datasets/catalog/COPERNICUS_S2_HARMO |                                                       |
| NIZED>`_                                 |                                                       |
+------------------------------------------+-------------------------------------------------------+
| `COPERNICUS/S2_SR_HARMONIZED             | Harmonised Sentinel-2, level 2A, surface reflectance. |
| <https://developers.google.com/earth-eng |                                                       |
| ine/datasets/catalog/COPERNICUS_S2_SR_HA |                                                       |
| RMONIZED>`_                              |                                                       |
+------------------------------------------+-------------------------------------------------------+

.. install_start

Installation
------------

Requirements
~~~~~~~~~~~~

``geedim`` is a python 3 package, and requires users to be registered with `Google Earth
Engine <https://signup.earthengine.google.com>`__.

conda
~~~~~

Under Windows, using ``conda`` is the easiest way to resolve binary dependencies. The
`Miniconda <https://docs.conda.io/en/latest/miniconda.html>`__ installation provides a minimal ``conda``.

.. code:: shell

   conda install -c conda-forge geedim

pip
~~~

.. code:: shell

   pip install geedim

Authentication
~~~~~~~~~~~~~~

Following installation, Earth Engine should be authenticated:

.. code:: shell

   earthengine authenticate

.. install_end

Getting started
---------------

Command line interface
~~~~~~~~~~~~~~~~~~~~~~

.. cli_start

``geedim`` command line functionality is accessed through the commands:

-  ``search``: Search for images.
-  ``composite``: Create a composite image.
-  ``download``: Download image(s).
-  ``export``: Export image(s).
-  ``config``: Configure cloud/shadow masking.

Get help on ``geedim`` with:

.. code:: shell

   geedim --help

and help on a ``geedim`` command with:

.. code:: shell

   geedim <command> --help

Examples
^^^^^^^^

Search for Landsat-8 images, reporting cloudless portions.

.. code:: shell

   geedim search -c l8-c2-l2 -s 2021-06-01 -e 2021-07-01 --bbox 24 -33 24.1 -33.1 --cloudless-portion

Download a Landsat-8 image with cloud/shadow mask applied.

.. code:: shell

   geedim download -i LANDSAT/LC08/C02/T1_L2/LC08_172083_20210610 --bbox 24 -33 24.1 -33.1 --mask

Command pipelines
~~~~~~~~~~~~~~~~~

Multiple ``geedim`` commands can be chained together in a pipeline where image results from the previous command form
inputs to the current command. For example, if the ``composite`` command is chained with ``download`` command, the
created composite image will be downloaded, or if the ``search`` command is chained with the ``composite`` command, the
search result images will be composited.

Common command options are also piped between chained commands. For example, if the ``config`` command is chained with
other commands, the configuration specified with ``config`` will be applied to subsequent commands in the pipeline. Many
command combinations are possible.

.. _examples-1:

Examples
^^^^^^^^

Composite two Landsat-7 images and download the result:

.. code:: shell

   geedim composite -i LANDSAT/LE07/C02/T1_L2/LE07_173083_20100203 -i LANDSAT/LE07/C02/T1_L2/LE07_173083_20100219 download --bbox 22 -33.1 22.1 -33 --crs EPSG:3857 --scale 30

Composite the results of a Landsat-8 search and download the result.

.. code:: shell

   geedim search -c l8-c2-l2 -s 2019-02-01 -e 2019-03-01 --bbox 23 -33 23.2 -33.2 composite -cm q-mosaic download --scale 30 --crs EPSG:3857

Composite the results of a Landsat-8 search, export to Earth Engine asset, and download the asset image.

.. code:: shell

    geedim search -c l8-c2-l2 -s 2019-02-01 -e 2019-03-01 --bbox 23 -33 23.2 -33.2 composite -cm q-mosaic export --type asset --folder <your cloud project> --scale 30 --crs EPSG:3857 download

Search for Sentinel-2 SR images with a cloudless portion of at least 60%, using the ``qa`` mask-method to identify
clouds:

.. code:: shell

   geedim config --mask-method qa search -c s2-sr --cloudless-portion 60 -s 2022-01-01 -e 2022-01-14 --bbox 24 -34 24.5 -33.5

.. cli_end

API
~~~

Example
^^^^^^^

.. code:: python

   import geedim as gd

   gd.Initialize()  # initialise earth engine

   # geojson polygon to search / download
   region = {
       "type": "Polygon",
       "coordinates": [[[24, -33.6], [24, -33.53], [23.93, -33.53], [23.93, -33.6], [24, -33.6]]]
   }

   # make collection and search, reporting cloudless portions
   coll = gd.MaskedCollection.from_name('COPERNICUS/S2_SR')
   coll = coll.search('2019-01-10', '2019-01-21', region, cloudless_portion=0)
   print(coll.schema_table)
   print(coll.properties_table)

   # create and download an image
   im = gd.MaskedImage.from_id('COPERNICUS/S2_SR/20190115T080251_20190115T082230_T35HKC')
   im.download('s2_image.tif', region=region)

   # composite search results and download
   comp_im = coll.composite()
   comp_im.download('s2_comp_image.tif', region=region, crs='EPSG:32735', scale=30)

License
-------

This project is licensed under the terms of the `Apache-2.0 License <LICENSE>`__.

Contributing
------------

See the `documentation <https://geedim.readthedocs.io/en/latest/contributing.html>`__ for details.

Credits
-------

-  Tiled downloading was inspired by the work in `GEES2Downloader <https://github.com/cordmaur/GEES2Downloader>`__ under
   terms of the `MIT license <https://github.com/cordmaur/GEES2Downloader/blob/main/LICENSE>`__.
-  Medoid compositing was adapted from `gee_tools <https://github.com/gee-community/gee_tools>`__ under the terms of the
   `MIT license <https://github.com/gee-community/gee_tools/blob/master/LICENSE>`__.
-  Sentinel-2 cloud/shadow masking was adapted from `ee_extra <https://github.com/r-earthengine/ee_extra>`__ under
   terms of the `Apache-2.0 license <https://github.com/r-earthengine/ee_extra/blob/master/LICENSE>`__


.. |Tests| image:: https://github.com/leftfield-geospatial/geedim/actions/workflows/run-unit-tests.yml/badge.svg
   :target: https://github.com/leftfield-geospatial/geedim/actions/workflows/run-unit-tests.yml
.. |codecov| image:: https://codecov.io/gh/leftfield-geospatial/geedim/branch/main/graph/badge.svg?token=69GZNQ3TI3
   :target: https://codecov.io/gh/leftfield-geospatial/geedim
.. |PyPI version| image:: https://img.shields.io/pypi/v/geedim.svg
   :target: https://pypi.org/project/geedim/
.. |conda-forge version| image:: https://img.shields.io/conda/vn/conda-forge/geedim.svg
   :alt: conda-forge
   :target: https://anaconda.org/conda-forge/geedim
.. |docs| image:: https://readthedocs.org/projects/geedim/badge/?version=latest
   :target: https://geedim.readthedocs.io/en/latest/?badge=latest
.. |License| image:: https://img.shields.io/badge/License-Apache%202.0-blue.svg
   :target: https://opensource.org/licenses/Apache-2.0

            

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    "description": "|Tests| |codecov| |PyPI version| |conda-forge version| |docs| |License|\n\n``geedim``\n==========\n\n.. short_descr_start\n\nSearch, composite, and download `Google Earth Engine <https://earthengine.google.com/>`__ imagery, without size limits.\n\n.. short_descr_end\n\n.. description_start\n\nDescription\n-----------\n\n``geedim`` provides a command line interface and API for searching, compositing and downloading satellite imagery\nfrom Google Earth Engine (EE). It optionally performs cloud/shadow masking, and cloud/shadow-free compositing on\nsupported collections. Images and composites can be downloaded; or exported to Google Drive, Earth Engine asset or\nGoogle Cloud Storage. Images larger than the\n`EE size limit <https://developers.google.com/earth-engine/apidocs/ee-image-getdownloadurl>`_ are split and downloaded\nas separate tiles, then re-assembled into a single GeoTIFF.\n\n.. description_end\n\nSee the documentation site for more detail: https://geedim.readthedocs.io/.\n\n.. supp_im_start\n\nCloud/shadow support\n~~~~~~~~~~~~~~~~~~~~\n\nAny EE imagery can be searched, composited and downloaded by ``geedim``. Cloud/shadow masking, and cloud/shadow-free\ncompositing are supported on the following collections:\n\n.. supp_im_end\n\n+------------------------------------------+-------------------------------------------------------+\n| EE name                                  | Description                                           |\n+==========================================+=======================================================+\n| `LANDSAT/LT04/C02/T1_L2                  | Landsat 4, collection 2, tier 1, level 2 surface      |\n| <https://developers.google.com/earth-eng | reflectance.                                          |\n| ine/datasets/catalog/LANDSAT_LT04_C02_T1 |                                                       |\n| _L2>`_                                   |                                                       |\n+------------------------------------------+-------------------------------------------------------+\n| `LANDSAT/LT05/C02/T1_L2                  | Landsat 5, collection 2, tier 1, level 2 surface      |\n| <https://developers.google.com/earth-eng | reflectance.                                          |\n| ine/datasets/catalog/LANDSAT_LT05_C02_T1 |                                                       |\n| _L2>`_                                   |                                                       |\n+------------------------------------------+-------------------------------------------------------+\n| `LANDSAT/LE07/C02/T1_L2                  | Landsat 7, collection 2, tier 1, level 2 surface      |\n| <https://developers.google.com/earth-eng | reflectance.                                          |\n| ine/datasets/catalog/LANDSAT_LE07_C02_T1 |                                                       |\n| _L2>`_                                   |                                                       |\n+------------------------------------------+-------------------------------------------------------+\n| `LANDSAT/LC08/C02/T1_L2                  | Landsat 8, collection 2, tier 1, level 2 surface      |\n| <https://developers.google.com/earth-eng | reflectance.                                          |\n| ine/datasets/catalog/LANDSAT_LC08_C02_T1 |                                                       |\n| _L2>`_                                   |                                                       |\n+------------------------------------------+-------------------------------------------------------+\n| `LANDSAT/LC09/C02/T1_L2                  | Landsat 9, collection 2, tier 1, level 2 surface      |\n| <https://developers.google.com/earth-eng | reflectance.                                          |\n| ine/datasets/catalog/LANDSAT_LC09_C02_T1 |                                                       |\n| _L2>`_                                   |                                                       |\n+------------------------------------------+-------------------------------------------------------+\n| `COPERNICUS/S2                           | Sentinel-2, level 1C, top of atmosphere reflectance.  |\n| <https://developers.google.com/earth-    |                                                       |\n| engine/datasets/catalog/COPERNICUS_S2>`_ |                                                       |\n+------------------------------------------+-------------------------------------------------------+\n| `COPERNICUS/S2_SR                        | Sentinel-2, level 2A, surface reflectance.            |\n| <https://developers.google.com/earth-eng |                                                       |\n| ine/datasets/catalog/COPERNICUS_S2_SR>`_ |                                                       |\n+------------------------------------------+-------------------------------------------------------+\n| `COPERNICUS/S2_HARMONIZED                | Harmonised Sentinel-2, level 1C, top of atmosphere    |\n| <https://developers.google.com/earth-eng | reflectance.                                          |\n| ine/datasets/catalog/COPERNICUS_S2_HARMO |                                                       |\n| NIZED>`_                                 |                                                       |\n+------------------------------------------+-------------------------------------------------------+\n| `COPERNICUS/S2_SR_HARMONIZED             | Harmonised Sentinel-2, level 2A, surface reflectance. |\n| <https://developers.google.com/earth-eng |                                                       |\n| ine/datasets/catalog/COPERNICUS_S2_SR_HA |                                                       |\n| RMONIZED>`_                              |                                                       |\n+------------------------------------------+-------------------------------------------------------+\n\n.. install_start\n\nInstallation\n------------\n\nRequirements\n~~~~~~~~~~~~\n\n``geedim`` is a python 3 package, and requires users to be registered with `Google Earth\nEngine <https://signup.earthengine.google.com>`__.\n\nconda\n~~~~~\n\nUnder Windows, using ``conda`` is the easiest way to resolve binary dependencies. The\n`Miniconda <https://docs.conda.io/en/latest/miniconda.html>`__ installation provides a minimal ``conda``.\n\n.. code:: shell\n\n   conda install -c conda-forge geedim\n\npip\n~~~\n\n.. code:: shell\n\n   pip install geedim\n\nAuthentication\n~~~~~~~~~~~~~~\n\nFollowing installation, Earth Engine should be authenticated:\n\n.. code:: shell\n\n   earthengine authenticate\n\n.. install_end\n\nGetting started\n---------------\n\nCommand line interface\n~~~~~~~~~~~~~~~~~~~~~~\n\n.. cli_start\n\n``geedim`` command line functionality is accessed through the commands:\n\n-  ``search``: Search for images.\n-  ``composite``: Create a composite image.\n-  ``download``: Download image(s).\n-  ``export``: Export image(s).\n-  ``config``: Configure cloud/shadow masking.\n\nGet help on ``geedim`` with:\n\n.. code:: shell\n\n   geedim --help\n\nand help on a ``geedim`` command with:\n\n.. code:: shell\n\n   geedim <command> --help\n\nExamples\n^^^^^^^^\n\nSearch for Landsat-8 images, reporting cloudless portions.\n\n.. code:: shell\n\n   geedim search -c l8-c2-l2 -s 2021-06-01 -e 2021-07-01 --bbox 24 -33 24.1 -33.1 --cloudless-portion\n\nDownload a Landsat-8 image with cloud/shadow mask applied.\n\n.. code:: shell\n\n   geedim download -i LANDSAT/LC08/C02/T1_L2/LC08_172083_20210610 --bbox 24 -33 24.1 -33.1 --mask\n\nCommand pipelines\n~~~~~~~~~~~~~~~~~\n\nMultiple ``geedim`` commands can be chained together in a pipeline where image results from the previous command form\ninputs to the current command. For example, if the ``composite`` command is chained with ``download`` command, the\ncreated composite image will be downloaded, or if the ``search`` command is chained with the ``composite`` command, the\nsearch result images will be composited.\n\nCommon command options are also piped between chained commands. For example, if the ``config`` command is chained with\nother commands, the configuration specified with ``config`` will be applied to subsequent commands in the pipeline. Many\ncommand combinations are possible.\n\n.. _examples-1:\n\nExamples\n^^^^^^^^\n\nComposite two Landsat-7 images and download the result:\n\n.. code:: shell\n\n   geedim composite -i LANDSAT/LE07/C02/T1_L2/LE07_173083_20100203 -i LANDSAT/LE07/C02/T1_L2/LE07_173083_20100219 download --bbox 22 -33.1 22.1 -33 --crs EPSG:3857 --scale 30\n\nComposite the results of a Landsat-8 search and download the result.\n\n.. code:: shell\n\n   geedim search -c l8-c2-l2 -s 2019-02-01 -e 2019-03-01 --bbox 23 -33 23.2 -33.2 composite -cm q-mosaic download --scale 30 --crs EPSG:3857\n\nComposite the results of a Landsat-8 search, export to Earth Engine asset, and download the asset image.\n\n.. code:: shell\n\n    geedim search -c l8-c2-l2 -s 2019-02-01 -e 2019-03-01 --bbox 23 -33 23.2 -33.2 composite -cm q-mosaic export --type asset --folder <your cloud project> --scale 30 --crs EPSG:3857 download\n\nSearch for Sentinel-2 SR images with a cloudless portion of at least 60%, using the ``qa`` mask-method to identify\nclouds:\n\n.. code:: shell\n\n   geedim config --mask-method qa search -c s2-sr --cloudless-portion 60 -s 2022-01-01 -e 2022-01-14 --bbox 24 -34 24.5 -33.5\n\n.. cli_end\n\nAPI\n~~~\n\nExample\n^^^^^^^\n\n.. code:: python\n\n   import geedim as gd\n\n   gd.Initialize()  # initialise earth engine\n\n   # geojson polygon to search / download\n   region = {\n       \"type\": \"Polygon\",\n       \"coordinates\": [[[24, -33.6], [24, -33.53], [23.93, -33.53], [23.93, -33.6], [24, -33.6]]]\n   }\n\n   # make collection and search, reporting cloudless portions\n   coll = gd.MaskedCollection.from_name('COPERNICUS/S2_SR')\n   coll = coll.search('2019-01-10', '2019-01-21', region, cloudless_portion=0)\n   print(coll.schema_table)\n   print(coll.properties_table)\n\n   # create and download an image\n   im = gd.MaskedImage.from_id('COPERNICUS/S2_SR/20190115T080251_20190115T082230_T35HKC')\n   im.download('s2_image.tif', region=region)\n\n   # composite search results and download\n   comp_im = coll.composite()\n   comp_im.download('s2_comp_image.tif', region=region, crs='EPSG:32735', scale=30)\n\nLicense\n-------\n\nThis project is licensed under the terms of the `Apache-2.0 License <LICENSE>`__.\n\nContributing\n------------\n\nSee the `documentation <https://geedim.readthedocs.io/en/latest/contributing.html>`__ for details.\n\nCredits\n-------\n\n-  Tiled downloading was inspired by the work in `GEES2Downloader <https://github.com/cordmaur/GEES2Downloader>`__ under\n   terms of the `MIT license <https://github.com/cordmaur/GEES2Downloader/blob/main/LICENSE>`__.\n-  Medoid compositing was adapted from `gee_tools <https://github.com/gee-community/gee_tools>`__ under the terms of the\n   `MIT license <https://github.com/gee-community/gee_tools/blob/master/LICENSE>`__.\n-  Sentinel-2 cloud/shadow masking was adapted from `ee_extra <https://github.com/r-earthengine/ee_extra>`__ under\n   terms of the `Apache-2.0 license <https://github.com/r-earthengine/ee_extra/blob/master/LICENSE>`__\n\n\n.. |Tests| image:: https://github.com/leftfield-geospatial/geedim/actions/workflows/run-unit-tests.yml/badge.svg\n   :target: https://github.com/leftfield-geospatial/geedim/actions/workflows/run-unit-tests.yml\n.. |codecov| image:: https://codecov.io/gh/leftfield-geospatial/geedim/branch/main/graph/badge.svg?token=69GZNQ3TI3\n   :target: https://codecov.io/gh/leftfield-geospatial/geedim\n.. |PyPI version| image:: https://img.shields.io/pypi/v/geedim.svg\n   :target: https://pypi.org/project/geedim/\n.. |conda-forge version| image:: https://img.shields.io/conda/vn/conda-forge/geedim.svg\n   :alt: conda-forge\n   :target: https://anaconda.org/conda-forge/geedim\n.. |docs| image:: https://readthedocs.org/projects/geedim/badge/?version=latest\n   :target: https://geedim.readthedocs.io/en/latest/?badge=latest\n.. |License| image:: https://img.shields.io/badge/License-Apache%202.0-blue.svg\n   :target: https://opensource.org/licenses/Apache-2.0\n",
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