Step 3 - Stage-in the EO data

The Jupyter Notebooks process local Earth Observation data. As such we have prepared a set of Jupyter notebooks that stage-in the EO data required for the implementation of application.

The stage-in notebooks are published on a software repository hosted by GitLab at the URL https://gitlab.com/ellip/quick-start/jupyterlab/stage-in.

At this stage, the stage-in Jupyter Notebooks are:

  • Sentinel1 - stage-in
  • Landsat8 - stage-in
  • Envisat - stage-in

Procedure

This step will clone the Stage-in Jupyter Notebooks git repository on the local sandbox and thus provide a simple way to stage-in EO data.

  • On the JupyterLab Launcher, start a new Terminal
  • Type the commands below to set the HOME to /workspace and clone the stage-in notebooks:
cd /workspace
git clone https://gitlab.com/ellip/quick-start/jupyterlab/stage-in

This will create a new folder under /workspace.

  • Using the JupyterLab Left Sidebar, browse the stage-in folder and open the stage-in Jupyter Notebook Sentinel1 - stage-in.
  • Click Kernel/Restart Kernel and Run All Cells:

Kernel/Restart Kernel and Run All Cells

  • Wait for the conclusion,
Note: It can take several minutes to conclude. You can be sure that it has finished when all the cells have number within the squared parentheses. On the other hand, the symbol [*] close to a cell means that the execution of that cell is ongoing.
[ ]:

* Once completed, use the left panel to inspect the content of the 'data' folder.
There is now a Sentinel-1 product downloaded locally.

Going further

Input identifier and input reference

The Stage-in Jupyter Notebook executed earlier creates two output cells that are worth drawing your attention to:

Ellip Workflows reserved keywords

The first cellis:

[5]:

print 'input_identifier = \'%s\'' % s1_identifier

input_identifier = 'S1A_IW_GRDH_1SDV_20171210T182024_20171210T182049_019644_021603_0A33'

The output will be used in the Step 4 - Implement the data transformation steps.

input_identifier is thus a reserved keyword in a Jupyter Notebook streaming executable. This variable will be used to open the product using SNAP.

The second cell is:

[4]:

print 'input_reference = \'%s\'' % input_reference

input_reference = 'https://catalog.terradue.com/sentinel1/search?format=atom&uid=S1A_IW_GRDH_1SDV_20171210T182024_20171210T182049_019644_021603_0A33'

The output will be used in the Step 4 - Implement the data transformation steps.

input_reference is thus a reserved keyword in a Jupyter Notebook streaming executable. It can be used for querying metadata about the product to the Catalogue.

Next step

Now that there’s a Sentinel-1 product staged-in, proceed with Step 4 - Implement the data transformation steps