pangeo in relation to CMR

CMR is the NASA Common Metadata Repository

Introduction

This repo asks (answers) some pangeo-centric questions...

NASA intends the pangeo project will support access to earth remote sensing data (and related) via the public cloud and technologies built thereupon. This involves organized/automated computing horsepower and infrastructure. In turn this begs a number of questions, foremost 'What is the learning process that enables a scientist to take advantage of both pangeo and CMR?' Jointly 'What does this pantheon of data look like?' and 'Are there other comparable resources (type, style, scope) to be aware of?'

We begin in the notebooks with basic tactics; basically How to access metadata from the NASA CMR from a Jupyter notebook? However this repo is really a higher-level effort to get our collective arms around the learning and adoption process, by example. We have links to outreach efforts such as Damien Irving's excellent software carpentry sequence on Python for Ocean and Atmospheric Sciences. We provide Python notebooks that demonstrate a set of useful tools applied to various data resources.

Links

Education and Outreach

• Damien Irving oceanography data carpentry blog
  • ...and Damien's related AOS tutorials
• EarthML
• Research Computing in Earth Sciences course by Ryan Abernathy
• pangeo cmr repo
  • ...including GOLIVE ice velocity notebooks
• Jupyter notebook editing shortcuts
• Giovanni data discover application from Goddard

Organizations

• pangeo

• Ocean pangeo

• Atmos pangeo

• EOSDIS the NASA Earth Observing System Data Information System

• CMR

• GIBS for browsing NASA imagery

• NASA Distributed Active Archive Centers

• MEaSUREshttps://earthdata.nasa.gov/community/community-data-system-programs/measures-projects)

• EarthML

Tech and Tactics

• Python-CMR
• NEP NASA Earth Observations WMS resource page
• STAC catalog program

External resources

• NASA-external platforms for working with NASA-generated data like LANDSAT
  • Google Earth Engine (GEE)
  • AWS hosting of LANDSAT
  • Jupyter Hubs
  • GOLIVE / ITSLIVE Land Ice Velocity and Elevation derived data products
• NASA-external data sources
  • Planet
  • Polarhub is Wenwen Li's cryo crawler
• Web Mapping Services
  • Includes map controls like ipyleaflet
  • Search 'NASA WMS' to find NASA (often Goddard) Web Mapping Services.
    • Add to ipyleaflet Map; GetCapabilities and layer qualifiers help needed

More Tactics

As I am running into debugging issues I'm recording some installation steps on an EC2 instance with the idea of using an AMI to grab horsepower/RAM/disk space as needed.

wget https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh
bash Miniconda3-latest-Linux-x86_64.sh
rm Miniconda3-latest-Linux-x86_64.sh

This install miniconda. Then we have an environment config/activate:

conda create -n golive python=3.6
conda activate golive

...and requirements.txt...

boto3==1.9.78
obspy==1.1.0
Pillow==5.4.1

...and some package installations not in the requirements...

conda install pandas
conda install netcdf4
conda install xarray
conda install ipywidgets