Exercise: STAC

Exercise: STAC#

Timing

  • Time: 20 min

Goals

  • Getting familiar with Jupyter in the Puhti web interface

  • Learn to use STAC for searching for raster data

Prerequisites

Open JupyterLab in Puhti web interface#

Change the default project

  • project_2015299 is an example project name, replace with your own CSC project name.

  • CSC Docs: Jupyter

  • Open the Jupyter launch page: from front page or Apps -> Jupyter

  • Use settings:

    • (Reservation: geocomputing_day1, only during course)

    • Project: project_2015299

    • Partition: interactive (small during course)

    • Number of CPU cores: 1

    • Memory (Gb): 8

    • Local disk: 0

    • Time: 0:30:00

    • Python: geoconda

    • Module version: default

    • Working directory: /scratch/project_2015299

    • Launch

  • Wait a moment for Jupyter to start -> Connect to Jupyter

  • Open

Preparations#

  • Open new Terminal window

  • Make a folder for the exercise materials and make it your working directory

  • Change the project name.

mkdir -p /scratch/project_2015299/students/$USER
cd /scratch/project_2015299/students/$USER

  • Copy the example scripts to Puhti.

git clone https://github.com/csc-training/geocomputing.git

STAC Notebook#

  1. In the file explorer, open `students/$USER/geocomputing/python/STAC

  2. Open STAC_CSC_example_short.ipynb notebook

  3. Follow the notebook, use Shift+Enter for running cells.

End the session#

  • Close the web tab

  • Find the session in the Active sessions view and select Cancel

Key points

  • STAC is an easy option for finding and downloading raster data.

  • Jupyter is a nice tool for interactively working with Python.

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