Geospatial Vector Data Processing in Python

This repository contains an introduction to geospatial vector 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 Docker installed on your machine.

Instructions

It's recommended to pull the Docker image from Dockerhub. Otherwise, if you prefer, you can build your own image using the instructions in the following section.

docker pull hamedalemo/vector-tutorial:1.1

You will download files from s3 bucket in this tutorial, so it is best to mount a local directory to your container to keep the data accessible outside the container and after you terminate it:

docker run -it -p 8888:8888 -p 8787:8787 -v $(pwd):/home/gisuser/data hamedalemo/vector-tutorial:1.1

• Copy the Jupyter Lab url and paste it in your browser.
• Open vector_analysis.ipynb, dask_geopandas_intro.ipynb, and scalable_vector_analysis.ipynb and follow the instructions.

Build Your Docker image:

docker build -t vector-tutorial .

Run the container as following after switching to the repository's directory locally:

docker run -it -p 8888:8888 -p 8787:8787 -v $(pwd):/home/gisuser/data vector-tutorial

• Copy the Jupyter Lab url and paste it in your browser.
• Open vector_analysis.ipynb, dask_geopandas_intro.ipynb, and scalable_vector_analysis.ipynb and follow the instructions.