A curated list of open technology projects to sustain a stable climate, energy supply, biodiversity and natural resources.

Gedi Tutorials

Tutorials on producing high resolution laser ranging observations based on data of the Global Ecosystem Dynamics Investigation.
https://github.com/ornldaac/gedi_tutorials

Category: Sustainable Development
Sub Category: Education

Keywords

aboveground-biomass altimetry canopy-metrics gedi lidar nasa-data

Keywords from Contributors

atl08 modis viirs

Last synced: about 6 hours ago
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Repository metadata

GEDI L3 and L4 Tutorials

README.md

GEDI Science Data Tutorials

Overview

These tutorials demonstrate how to discover, access, and use GEDI science data products archived at the ORNL DAAC. GEDI L3, L4A, L4B, and L4C data products are available in various data tools and services.

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.
  4. Direct S3 Access GEDI L4A from the NASA EarthData Cloud: retrieve the GEDI L4A dataset from NASA Earthdata Cloud using direct S3 access. Open in SageMaker Studio Lab
  5. Access GEDI L4A dataset with NASA OPeNDAP in the Cloud: access selected variables for the GEDI L4A dataset within an area of interest using OPeNDAP Hyrax
  6. Access GEDI L4A dataset with NASA Harmony API: direct access and subset the GEDI L4A variables using NASA Harmony API
  7. Reproduce L4A AGBD estimates from GEDI L2A RH metrics: reconstruct L4A AGBD estimates using L2A relative height (RH) metrics
  8. Apply correction to AGBD estimates for selected L4A shots, Version 2: apply AGBD correction to Version 1 (V001) GEDI L4A shots affected with the algorithm setting group 10 issue
  9. On-Cloud Data Retrieval and Analysis: Aboveground biomass from GEDI, ICESat-2 and Field Data: directly access and retrieve the GEDI dataset, ICESat-2 and Field Data in the cloud

Python Scripts

  1. Search and download GEDI L4A dataset: downloads GEDI L4A granules to a local directory based on GeoJSON polygon
  2. Subset GEDI L4A footprints: subsets the downloaded GEDI L4A granules by a GeoJSON polygon file
  3. Subset GEDI L4A with NASA OPeNDAP in the Cloud: accesses the GEDI L4A dataset using NASA's OPeNDAP Hyrax

GEDI L4B Gridded Aboveground Biomass Density

Jupyter Notebooks

  1. Access GEDI L4B Dataset with OGC Web Services: visualize and access the GEDI L4B dataset using the OGC WMS and WCS services

Citation (citation.md)

# Cite Tutorial

To cite the tutorial in your publications, please use the following Zenodo reference:

```{only} html
[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.xxx.svg)](https://doi.org/10.5281/zenodo.xxx)
```

A full list of contributors is available [here](https://github.com/ornldaac/gedi_tutorials/graphs/contributors).

Owner metadata


GitHub Events

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Committers metadata

Last synced: 7 days ago

Total Commits: 81
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Avg Commits per committer: 27.0
Development Distribution Score (DDS): 0.025

Commits in past year: 5
Committers in past year: 1
Avg Commits per committer in past year: 5.0
Development Distribution Score (DDS) in past year: 0.0

Name Email Commits
Shrestha, Rupesh s****r@o****v 79
Bruce Wilson u****a@g****m 1
Shrestha r****s@m****v 1

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Merged pull request: 0
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Dependencies

requirements.txt pypi
  • IPython *
  • contextily *
  • folium *
  • geopandas *
  • h5py *
  • harmony-py *
  • matplotlib *
  • matplotlib_scalebar *
  • netCDF4 *
  • numpy *
  • owslib *
  • pandas *
  • pydap *
  • rasterio *
  • rasterstats *
  • requests *
  • s3fs *
  • scipy *
  • seaborn *
  • shapely *
  • tabulate *

Score: 5.910796644040527