.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "_auto_examples/first_steps_create_datacube.py"
.. LINE NUMBERS ARE GIVEN BELOW.

.. only:: html

    .. note::
        :class: sphx-glr-download-link-note

        :ref:`Go to the end <sphx_glr_download__auto_examples_first_steps_create_datacube.py>`
        to download the full example code.

.. rst-class:: sphx-glr-example-title

.. _sphx_glr__auto_examples_first_steps_create_datacube.py:


First steps to create a datacube
===============================================================

To create a datacube using Earth Data Store from EarthDaily you have two possibilities.

The first one is the more classic one, you request items, then you build your datacube, and then you can mask pixels using a cloudmask asset.
The second one is the most turnkey one, the one we recommend, it allows to do all the process at once.

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Import librairies
-------------------------------------------

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.. code-block:: Python


    from matplotlib import pyplot as plt

    import earthdaily
    from earthdaily import EarthDataStore, datasets








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Loading geometry

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.. code-block:: Python


    geometry = datasets.load_pivot()








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Init earthdatastore with environment variables or default credentials
----------------------------------------------------------------------------

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.. code-block:: Python


    eds = EarthDataStore()








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Create datacube (in one step)
--------------------------------------------------

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.. code-block:: Python


    s2_datacube = eds.datacube(
        "sentinel-2-l2a",
        assets=["blue", "green", "red", "nir"],
        intersects=geometry,
        datetime=["2022-08-01", "2022-08-09"],
        mask_with="native",  # equal to "scl" for sentinel-2
        clear_cover=50,
    )

    s2_datacube.clear_percent.plot.scatter(x="time")
    plt.title("Percentage of clear pixels on the study site")
    plt.show()

    s2_datacube.ed.plot_rgb(vmin=0, vmax=0.2, col="time", col_wrap=4)




.. rst-class:: sphx-glr-horizontal


    *

      .. image-sg:: /_auto_examples/images/sphx_glr_first_steps_create_datacube_001.png
         :alt: Percentage of clear pixels on the study site
         :srcset: /_auto_examples/images/sphx_glr_first_steps_create_datacube_001.png
         :class: sphx-glr-multi-img

    *

      .. image-sg:: /_auto_examples/images/sphx_glr_first_steps_create_datacube_002.png
         :alt: time = 2022-08-02, time = 2022-08-05, time = 2022-08-07
         :srcset: /_auto_examples/images/sphx_glr_first_steps_create_datacube_002.png
         :class: sphx-glr-multi-img


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 .. code-block:: none


    <xarray.plot.facetgrid.FacetGrid object at 0x7f5fd00dc350>



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Create datacube in three steps
--------------------------------------------------

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Request items

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.. code-block:: Python


    items = eds.search(
        "sentinel-2-l2a",
        intersects=geometry,
        datetime=["2022-08-01", "2022-08-09"],
    )








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Creata datacube (independent from being log into earthdatastore)
We request the "scl" assets which is the native cloudmask

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.. code-block:: Python


    s2_datacube = earthdaily.earthdatastore.datacube(
        items, assets=["blue", "green", "red", "nir", "scl"], intersects=geometry
    )








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Mask datacube

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.. code-block:: Python


    # intersects or bbox are asked in order to compute accurate mask statistics

    s2_datacube = earthdaily.earthdatastore.mask.Mask(s2_datacube, intersects=geometry).scl(
        mask_statistics=True
    )

    s2_datacube = earthdaily.earthdatastore.mask.filter_clear_cover(
        s2_datacube, 50
    )  # at least 50% of clear pixels
    #
    s2_datacube.ed.plot_rgb(vmin=0, vmax=0.2, col="time", col_wrap=4)



.. image-sg:: /_auto_examples/images/sphx_glr_first_steps_create_datacube_003.png
   :alt: time = 2022-08-02, time = 2022-08-05, time = 2022-08-07
   :srcset: /_auto_examples/images/sphx_glr_first_steps_create_datacube_003.png
   :class: sphx-glr-single-img


.. rst-class:: sphx-glr-script-out

 .. code-block:: none


    <xarray.plot.facetgrid.FacetGrid object at 0x7f5fc4392850>




.. rst-class:: sphx-glr-timing

   **Total running time of the script:** (0 minutes 10.490 seconds)


.. _sphx_glr_download__auto_examples_first_steps_create_datacube.py:

.. only:: html

  .. container:: sphx-glr-footer sphx-glr-footer-example

    .. container:: sphx-glr-download sphx-glr-download-jupyter

      :download:`Download Jupyter notebook: first_steps_create_datacube.ipynb <first_steps_create_datacube.ipynb>`

    .. container:: sphx-glr-download sphx-glr-download-python

      :download:`Download Python source code: first_steps_create_datacube.py <first_steps_create_datacube.py>`

    .. container:: sphx-glr-download sphx-glr-download-zip

      :download:`Download zipped: first_steps_create_datacube.zip <first_steps_create_datacube.zip>`


.. only:: html

 .. rst-class:: sphx-glr-signature

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