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Repository

Basic Info
  • Host: GitHub
  • Owner: PaulEunKim
  • License: apache-2.0
  • Language: HTML
  • Default Branch: main
  • Size: 103 MB
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Created about 1 year ago · Last pushed about 1 year ago
Metadata Files
Readme Changelog Contributing License Code of conduct Citation

README.md

EMIT-Data-Resources

Welcome to the EMIT-Data-Resources repository. This repository provides guides, short how-tos, and tutorials to help users access and work with data from the Earth Surface Mineral Dust Source Investigation (EMIT) mission. In the interest of open science this repository has been made public but is still under active development. All notebooks and scripts should be functional, however, changes or additions may be made. Make sure to consult the CHANGE_LOG.md for the most recent changes to the repository. Contributions from all parties are welcome.


EMIT Background

The EMIT Project delivers space-based measurements of surface mineralogy of the Earths arid dust source regions. These measurements are used to initialize the compositional makeup of dust sources in Earth System Models (ESMs). The dust cycle, which describe the generation, lofting, transport, and deposition of mineral dust, plays an important role in ESMs. Dust composition is presently the largest uncertainty factor in quantifying the magnitude of aerosol direct radiative forcing. By understanding the composition of mineral dust sources, EMIT aims to constrain the sign and magnitude of dust-related radiative forcing at regional and global scales. During its one-year mission on the International Space Station (ISS), EMIT will make measurements over the sunlit Earths dust source regions that fall within 52 latitude. EMIT will schedule up to five visits (three on average) of each arid target region and only acquisitions not dominated by cloud cover will be downlinked. EMIT-based maps of the relative abundance of source minerals will advance the understanding of the current and future impacts of mineral dust in the Earth system.

EMIT Data Products are distributed by the LP DAAC. Learn more about EMIT data products from EMIT Product Pages and search for and download EMIT data products using NASA EarthData Search


Prerequisites/Setup Instructions

This repository requires that users set up a compatible Python environment and download the EMIT granules used. See the setup_instuctions.md file in the ./setup/ folder.

Repository Contents

Below are the resources available for EMIT Data.

|Name|Type|Summary| |:---|:---|:---| |Getting EMIT Data using EarthData Search|Markdown Guide|A thorough walkthrough for using EarthData Search to find and download EMIT data| |Streaming NASA Earthdata Cloud-Optimized GeoTIFFs using QGIS|Markdown Guide|A walkthrough to set up QGIS to stream cloud-optimized geotiff files from NASA Earthdata| |Exploring EMIT L2A Reflectance|Jupyter Notebook|Explore EMIT L2A Reflectance data using interactive plots| |Visualizing Methane Plume Timeseries|Jupyter Notebook|Find EMIT L2B CH4 Plume Data and build a timeseries of CH4 plume complexes| |GeneratingMethaneSpectral_Fingerprint|Jupyter Notebook|Extract Radiance Spectra and build an in-plume/out-of-plume ratio to compare with CH4 absorption coefficient| |FindingEMITL2B_Data|Jupyter Notebook|Use the earthaccess Python library to find EMIT L2B Mineral Identification Band Depth and Uncertainty data| |Working with EMIT L2B Mineralogy|Jupyter Notebook|Work with the EMIT L2B Mineral Identification Band Depth and Uncertainty Data and aggregate individual spectral library constituents into the EMIT-10 minerals and estimate abundance| |How to find and access EMIT data|Jupyter Notebook|Use the earthaccess Python library to find and download or stream EMIT data| |How to Convert to ENVI Format|Jupyter Notebook|Convert from downloaded netCDF4 (.nc) format to .envi format| |How to Orthorectify|Jupyter Notebook|Use the geometry lookup table (GLT) included with the EMIT netCDF4 file to project on a geospatial grid (EPSG:4326)| |How to Extract Point Data|Jupyter Notebook|Extract spectra using lat/lon coordinates from a .csv and build a dataframe/.csv output| |How to Extract Area Data|Jupyter Notebook|Extract an area defined by a .geojson or shapefile| |How to use EMIT Quality Data|Jupyter Notebook|Build a mask using an EMIT L2A Mask file and apply it to an L2A Reflectance file| |How to use Direct S3 Access with EMIT|Jupyter Notebook|Use S3 from inside AWS us-west2 to access EMIT Data| |How to find EMIT Data using NASA's CMR API|Jupyter Notebook|Use NASA's CMR API to programmatically find EMIT Data|


Helpful Links


Contact Info

Email: LPDAAC@usgs.gov
Voice: +1-866-573-3222
Organization: Land Processes Distributed Active Archive Center (LP DAAC)
Website: https://lpdaac.usgs.gov/
Date last modified: 08-01-2024

Work performed under USGS contract G15PD00467 for NASA contract NNG14HH33I.

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Dependencies

Dockerfile docker
  • docker.io/pytorch/pytorch 2.2.0-cuda12.1-cudnn8-runtime build
poetry.lock pypi
  • 177 dependencies
pyproject.toml pypi
  • black ^23.1 develop
  • ipykernel ^6.0 develop
  • isort ^5.12 develop
  • jupyter ^1.0 develop
  • pytest ^7.0 develop
  • earthaccess *
  • fiona 1.9.5
  • fsspec ^2024.1
  • gdal 3.10.3
  • geopandas 0.13.2
  • holoviews ^1.20.2
  • netCDF4 ^1.6
  • numpy ^1.25
  • pandas ^2.0
  • pyproj 3.5
  • python ^3.10
  • rasterio ^1.4
  • rioxarray ^0.15
  • s3fs ^2024.1
  • scikit-image ^0.20
  • shapely 2.0.1
  • spectral ^0.23
  • xarray ^2024.1