Release of Getting Started with GEDI L1B, L2A, and L2B Data in Python Tutorial Series

May 14, 2020
By: LP DAAC

On January 21, 2020, the LP DAAC released Level 1B – Level 2 GEDI data products to the public, including Level 1B Geolocated Waveform Data (GEDI01_B), Level 2A Elevation and Height Metrics Data (GEDI02_A), and Level 2B Canopy Cover and Vertical Profile Metrics Data (GEDI02_B). GEDI granules are stored as HDF5 files encompassing an entire International Space Station (ISS) orbit, which are currently available through the LP DAAC Data Pool and NASA’s Earthdata Search. On February 10, 2020, the LP DAAC released the GEDI Finder web service, enabling spatial querying of GEDI files. On April 16, 2020 the LP DAAC released the GEDI Spatial and Band/Layer Subsetting and Export to GeoJSON (GEDI Subsetter) data prep script, providing users with spatial and layer subsetting of GEDI full orbits, as well as exporting subsets into geoJSON output format. Now that users are able to find and subset the GEDI data that they need--how about visualizing GEDI L1B waveforms? Or L2A Canopy height? PAVD?

The LP DAAC is pleased to announce the availability of a series of Jupyter Notebook Tutorials called “Getting Started with GEDI L1B, L2A, and L2B Data in Python”. The tutorials are available as Jupyter Notebooks or HTML outputs that allow users to get familiar with opening, subsetting, and visualizing GEDI L1B-L2 data in Python. The tutorials follow a use case centered on observing the towering Redwood forests of Redwood National Park in California, United States.

Tutorials:

  • The Getting Started with GEDI L1B Data in Python Jupyter Notebook shows how to use Python to open GEDI L1B files, visualize the full orbit of GEDI points (shots), subset to a region of interest, visualize GEDI full waveforms, and export subsets of GEDI science dataset (SDS) layers as GeoJSON files that can be loaded into GIS and/or Remote Sensing software programs.
  • The Getting Started with GEDI L2A Data in Python Jupyter Notebook shows how to use Python to open GEDI L2A files, visualize the full orbit of GEDI points (shots), subset to a region of interest, visualize GEDI canopy height, and export subsets of GEDI science dataset (SDS) layers as GeoJSON files that can be loaded into GIS and/or Remote Sensing software programs.
  • The Getting Started with GEDI L2B Data in Python Jupyter Notebook shows how to use Python to open GEDI L2B files, visualize the full orbit of GEDI points (shots), subset to a region of interest, visualize GEDI canopy height and vertical profile metrics, and export subsets of GEDI science dataset (SDS) layers as GeoJSON files that can be loaded into GIS and/or Remote Sensing software programs.

Access the tutorial series repository directly at: https://git.earthdata.nasa.gov/projects/LPDUR/repos/gedi-tutorials/browse.