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

• CSC user account and project with access to Puhti.

Open JupyterLab in Puhti web interface

• Open Puhti web interface and log in

Change the default project and username

• project_200xxxx is an example project name, replace with your own CSC project name.

• cscusername is an example username, replace with your username.

• CSC Docs: Jupyter

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

• Use settings:

  • (Reservation: geocomputing_wed, only during course)

  • Project: project_2011224

  • Partition: interactive (small during course)

  • Number of CPU cores: 1

  • Memory (Gb): 8

  • Local disk: 0

  • Time: 0:15:00

  • Python: geoconda

  • Module version: default

  • Working directory: /scratch/project_2011224

  • 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 and username.

mkdir -p /scratch/project_2011224/students/cscusername
cd /scratch/project_2011224/students/cscusername

• Copy the example scripts to Puhti.

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

STAC Notebook

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

2. Open STAC_CSC_example.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.