dsir_2021.04.1

First release of the data_science_im_rs branch in April of 2021. This release will be used for the final computations associated with the USDA ARS RRSRU vegetation mapping at the LTAR CPER using NEON AOP hyperspectral data.

0.2.4

Check if .github workflow adds "v" on release tag

0.2.3

Updated workflows to sync "latest" and "tag" images.

0.2.2

Testing release process with GH workflow

0.2.1

Update workflow for tags

0.2.0

• Refactor of the repository to split containers by branch (rather than folders in Master)
• Copied Master into Main --> Switched Main branch to the default/head branch
• Update environments in data_science_im_rs branch
• Added github actions to build and push containers to dockerhub (rather than use dockerhubs auto-build tool)

SCINetGeoWS_2020

SCINetGeoWS_2020 is the container used in the SCINet 2020 Geospatial Workshop. The container can be found on DockerHub at https://hub.docker.com/r/rowangaffney/data_science_im_rs/tags, and includes, but is not limited to:

• JupyterLab IDE, with a proxies to:
  • RStudio IDE
  • VSCode IDE (https://github.com/cdr/code-server)
• 3 conda environments
  1. Base - the standard conda environment
  2. py_geo - python environment with many distributed computing and geospatial packages
  3. r_geo - R environment with many geospatial packages

More details about this container can be found at https://microbadger.com/images/rowangaffney/data_science_im_rs

0.1.0

Changes mostly to the data_science_im_rs folder. Update of the py_geo environment, added Rstudio server, VSCode server, and Panel proxy. Added the metadata hooks and webhook in dockerhub to microbadger page

0.0.6

Changed base file from jupyter/scipy to jupyter/minimal-notebook.

0.0.5

Update README.md