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Tutorials on GEDI Science Data Products from the DWeb

Author: ORNL DAAC & EASIER Data
Date: August 26, 2021
Updated on: October 1, 2024
Contact for the ORNL DAAC: [email protected]
Contact for EASIER Data: [email protected]
Keywords: lidar, GEDI, AGBD, aboveground biomass, IPFS, Filecoin

Overview

The EASIER Data Initiative is exploring the use of decentralized web technologies such as IPFS and Filecoin to store and distribute Earth science data. These tutorials demonstrate how to discover, access, and use GEDI science data products from decentralized sources using the DWeb. The GEDI collection is maintained and archived at the ORNL DAAC. GEDI L3, L4A, and L4B data products are available from decentralized and centralized sources, as noted in various data tools and services.

Getting Started: Clone repo and deploy poetry project

This project uses Poetry for dependency management and is compatible with Python versions >=3.11. To install all necessary dependencies, follow these steps:

  1. Install Poetry if you haven't already:

    curl -sSL https://install.python-poetry.org | python3 -
  2. Clone the repository:

    git clone https://github.com/easierdata/gedi_tutorials.git
    cd gedi_tutorials
  3. Install the dependencies:

    poetry install
  4. Generate the configuration file by running the following command.

    poetry run edit-config

    A file named config.json is generated in the root directory and can be modified by re-running the command. See this page for more details on the available commands.

  5. Run Jupyter Notebook and start with a tutorial.

    poetry run jupyter notebook

GEDI L4A Footprint Level Aboveground Biomass Density

📗 Jupyter Notebooks

  1. Search and download GEDI L4A dataset: search and download GEDI L4A granules over an area of interest to a local machine
  2. Subset GEDI L4A footprints: subset downloaded GEDI L4A granules to an area of interest
  3. Explore GEDI L4A data structure: explore data structure, variables, and quality flags of the GEDI L4A dataset.

Related Resources

More resources related to ORNL DAAC data and web services can be found at the ORNL DAAC Learning page.