|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
------------
``geedim`` is a python 3 package, and requires users to be registered with `Google Earth
Engine <https://signup.earthengine.google.com>`__.
It can be installed with `pip <https://pip.pypa.io/>`_ or `conda <https://docs.anaconda.com/free/miniconda/>`_.
pip
~~~
.. code:: shell
pip install geedim
conda
~~~~~
.. code:: shell
conda install -c conda-forge 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 ``cloud-score`` mask-method to identify clouds:
.. code:: shell
geedim config --mask-method cloud-score search -c s2-sr-hm --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_HARMONIZED')
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_HARMONIZED/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=10)
License
-------
This project is licensed under the terms of the `Apache-2.0 License <https://github.com/leftfield-geospatial/geedim/blob/main/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\n``geedim`` is a python 3 package, and requires users to be registered with `Google Earth\nEngine <https://signup.earthengine.google.com>`__.\n\nIt can be installed with `pip <https://pip.pypa.io/>`_ or `conda <https://docs.anaconda.com/free/miniconda/>`_.\n\npip\n~~~\n\n.. code:: shell\n\n pip install geedim\n\nconda\n~~~~~\n\n.. code:: shell\n\n conda install -c conda-forge 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 ``cloud-score`` mask-method to identify clouds:\n\n.. code:: shell\n\n geedim config --mask-method cloud-score search -c s2-sr-hm --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_HARMONIZED')\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_HARMONIZED/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=10)\n\nLicense\n-------\n\nThis project is licensed under the terms of the `Apache-2.0 License <https://github.com/leftfield-geospatial/geedim/blob/main/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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