Geospatial Raster Data Processing in Python

This repository contains an introduction to geospatial raster data processing in Python. This is part of the course on Advanced Geospatial Analytics with Python taught since Fall 2023 at Clark University.

Requirements

You need to have pixi installed on your machine. Follow the installation instructions for your operating system, for example on macOS/Linux (if you are on Windows using WSL, use this command in your WSL terminal):

curl -fsSL https://pixi.sh/install.sh | sh

or on native Windows (PowerShell, not WSL):

powershell -ExecutionPolicy ByPass -c "irm -useb https://pixi.sh/install.ps1 | iex"

Instructions

Clone this repository to your local machine:

git clone git@github.com:HamedAlemo/raster-data-tutorial.git

Change your directory to the cloned repository:

cd raster-data-tutorial

Launch Jupyter Lab (running this for the first time will install the environment using the dependencies in pixi.toml and the exact versions pinned in pixi.lock):

pixi run lab

• Jupyter Lab will open in your browser (otherwise copy the url printed in the terminal and paste it in your browser).
• Open notebooks/raster_analysis.ipynb and notebooks/raster_processing.ipynb, and follow the instructions. Downloaded data is stored in data/ and the rasters the notebooks write are saved in output/, both in the repository root.
• The Dask dashboard will be available at the link printed by the Dask client (by default http://localhost:8787).

To add a new package to the environment, run pixi add <package-name>.