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4. Interfaces

Calvin Pang edited this page Apr 4, 2024 · 3 revisions

The Interface section provides users with instructions on how to interact with the repository using different interfaces, including WebUI, Jupyter Notebooks, and Command Line Interface (CLI).

By offering different interfaces catering to varying user needs and expertise levels, the Eyes on Australian Forests repository aims to provide a flexible and accessible platform for analysing satellite data and monitoring vegetation health in Australian forests. Users can choose the interface that best suits their requirements and level of expertise.

Before using any of the interfaces, please note that each interface will create a session-specific directory to store the files generated during the session. The session ID cannot be changed via the Basic WebUI interface; it can only be specified in the Jupyter Notebooks and CLI.

WebUI (Basic)

The repository provides a user-friendly web interfaces powered by Gradio for simple downloading and processing of satellite products.

To use the WebUI's:

  1. Activate the EoAF environment and navigate to the EoAF directory in your terminal.
  2. Run the appropriate script (e.g. webui/sentinel_ui.py) to launch the web interface.
    python webui/sentinel_ui.py
    
  3. Follow the on-screen instructions to interactively select the satellite source, date range and geographic area of interest.
  4. Click on the "Search" button to search for products and "Download" to initiate the download once confirmed.
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  1. Navigate to the "Process" tab and follow the on-screen instructions to interactively select your downloaded products and geographic area of interest.
  2. Click on the "Process Products" button to generate the NDVI, NDMI and NBR products as GeoTIFFs.
  3. Optionally, you may merge multiple satellite swaths across a time period into a single product.
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  1. Navigate to the "Visualisation" tab and follow the on-screen instructions to visualise your selected products as a ipyleaflet map.
  2. Click on "Generate Visualisation" and wait for a few moments before clicking on "Download Visualisation".
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  1. Open the *.html file via your web browser.
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Note: You will need to refresh your web browser whilst traversing across the different tabs to reload the File Explorer.

Jupyter Notebooks (Intermediate)

The repository provides Jupyter Notebooks for additional interactivity and customisation options for analysing satellite data. These notebooks allow users to explore data in more depth and apply custom processing algorithms.

To use the Jupyter Notebooks:

  1. Activate the EoAF environment and navigate to the EoAF directory in your terminal.
  2. Launch Jupyter Lab
    jupyter lab
    
  3. Open the appropriate notebook (e.g. sentinel-2.ipynb) in the Jupyter Notebook environment.
  4. Execute code cells sequentially and follow the instructions to interactively input your parameters to download, process and visualise satellite products.
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Command Line Interface (Advanced)

The repository provides a command-line interface (CLI) for automating the download and processing of satellite products based on user-defined search criteria. This interface is suitable for users familiar with command-line tools and scripting.

To use the CLI's:

  1. Activate the EoAF environment and navigate to the EoAF directory in your terminal.
  2. Run the appropriate script (e.g. src/landsat.py) with the --help flag to view the command line arguments.
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3. Run the appropriate script by specifying your search criteria and output directories as command line arguments.
python src/landsat.py --session-id Landsat_Test --start-date 2024-01-01 --end-date 2024-01-08 --shapefile shapefiles/small.shp -- 
collection ga_ls8c_ard_3 --crop --merge --download-from-thredds
  1. Monitor the progress of the processing pipeline and access the processed products in the specified output directories.
image

Note: All three interfaces will store the downloaded and processed products in the previously configured directories. You may export these for use in other applications such as QGIS or ArcGIS.

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