@XAMTO_AI: Want to learn geospatial programming but don't know where to start? I was in the same state until I came across an open-source book called 'Introduction to GIS Programming', which is free and allows running code online. It starts from the basics of Python and smoothly progresses to advanced geospatial data analysis. The best part is that each section comes with runnable code examples…
Summary
Introduces an open-source book titled 'Introduction to GIS Programming', which is free and supports running code online. It is suitable for learning geospatial programming from scratch, covering Python basics to advanced geospatial data analysis.
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Cached at: 08/22/26, 01:21 AM
Want to learn geospatial programming but don’t know where to start? I was in the same boat until I found an open-source book called Introduction to GIS Programming. It’s free, and you can even run the code online. It starts from the very basics of Python and smoothly progresses to advanced geospatial data analysis. The best part is that every section includes runnable code examples — learning by doing is far more effective than just reading. Absolute beginners can follow along without needing extra preparation, run code directly online without environment setup hassles, and switch between 8 languages (including English, Chinese, Japanese, and Korean) for无障碍 reading. After completing the course, you can even apply for a certification to add to your resume. The documentation and code are kept in sync to avoid obsolescence, and it’s completely open-source and free with no hidden costs.
URL: http://github.com/giswqs/intro-gispro…
giswqs/intro-gispro
Source: https://github.com/giswqs/intro-gispro
Introduction to GIS Programming
Introduction
Welcome to the official repository for Introduction to GIS Programming: A Practical Python Guide to Open Source Geospatial Tools. This repository contains all the code examples featured in the book, designed to help you learn and apply Python for geospatial analysis using open-source tools.
Get the Book
Print Edition
- 🇺🇸 English Full-Color Print Edition (556 pages) is available on Amazon (link).
PDF and EPUB Editions
🇺🇸 English | 🇨🇳 Chinese | 🇨🇿 Czech | 🇳🇱 Dutch | 🇫🇷 French | 🇩🇪 German | 🇮🇳 Hindi | 🇮🇩 Indonesian | 🇮🇹 Italian | 🇯🇵 Japanese | 🇰🇷 Korean | 🇵🇹 Portuguese | 🇷🇺 Russian | 🇲🇽 Spanish | 🇹🇷 Turkish
Cite the Book
If you use this book in your research or teaching, please consider citing it as follows:
Wu, Q. (2025). Introduction to GIS Programming: A Practical Python Guide to Open Source Geospatial Tools. Independently published. ISBN 979-8286979455.
Table of Contents
To download a PDF version of the Table of Contents, please visit [link].
-
Preface
- Introduction
- Who This Book Is For
- What This Book Covers
- Getting the Most Out of This Book
- Conventions Used in This Book
- Downloading the Code Examples
- Video Tutorials
- Get in Touch
- Acknowledgments
- About the Author
- Licensing and Copyright
-
Software Setup
- Overview of Software Tools
- Introduction to Python Package Management
- Setting Up Visual Studio Code
- Version Control with Git
- Using Google Colab
- Working with JupyterLab
- Using Docker
-
Python Programming Fundamentals
- Variables and Data Types
- Python Data Structures
- String Operations
- Loops and Conditional Statements
- Functions and Classes
- Working with Files
- Data Analysis with NumPy and Pandas
-
Geospatial Programming with Python
- Introduction to Geospatial Python
- Vector Data Analysis with GeoPandas
- Working with Raster Data using Rasterio
- Multi-dimensional Data Analysis with Xarray
- Raster Analysis with Rioxarray
- Interactive Visualization with Leafmap
- Geoprocessing with WhiteboxTools
- 3D Mapping with MapLibre
- Cloud Computing with Earth Engine and Geemap
- Hyperspectral Data Visualization with HyperCoast
- High-Performance Geospatial Analytics with DuckDB
- Geospatial Data Processing with GDAL and OGR
- Building Interactive Dashboards with Voila and Solara
- Distributed Computing with Apache Sedona
How to Run Code Examples
The code examples are organized into folders, each corresponding to a chapter in the book. The code examples are written in Python and can be run using MyBinder, Google Colab, or Docker. Follow this video tutorial to learn how to run the code examples.
Using MyBinder
The code examples can be run using MyBinder.
Using Google Colab
The code examples can be run using Google Colab.
Using Docker
The code examples can be run using Docker. There are two Docker images available:
A lightweight docker image without Apache Sedona:
docker pull giswqs/pygis:book
docker run -it -p 8888:8888 -v $(pwd):/app/workspace giswqs/pygis:book
A docker image with Apache Sedona:
docker pull giswqs/pygis:sedona
docker run -it -p 8888:8888 -p 4040:4040 -p 8080:8080 -p 8081:8081 -p 7077:7077 -p 8085:8085 -v $(pwd):/app/workspace giswqs/pygis:sedona
Video Tutorials
Complementing the written content, this book is supported by a comprehensive series of video tutorials that walk through key concepts and provide additional examples:
https://tinyurl.com/intro-gispro-videos
The videos are designed to complement, not replace, the written material. They’re particularly helpful for:
- Visual learners who benefit from seeing code being written and executed
- Understanding complex concepts through multiple explanations
- Learning about the development workflow and best practices
- Seeing how to approach problems and debug issues
The playlist is organized to follow the book’s structure. You can watch them in order as you progress through the book, or jump to specific topics as needed.
The videos were created in Fall 2024 when I was teaching the Introduction to GIS Programming course at the University of Tennessee. Although the course has concluded, the videos remain relevant and can be used as a reference for the book. Additional videos will be added in the future.
Enroll for Certification
Please note that you can access the course materials and lecture videos on the course website without enrolling in the course. However, if you’re interested in submitting lab assignments, receiving grades, and earning a certificate of completion, you can enroll in the course at any time by clicking the link below. There is no deadline for enrollment, and you can complete the course at your own pace.
About the Author
Dr. Qiusheng Wu is an Associate Professor and the Director of Graduate Studies in the Department of Geography & Sustainability at the University of Tennessee, Knoxville. He also serves as an Amazon Scholar. Dr. Wu’s research focuses on geospatial data science and open-source software development, with an emphasis on leveraging big geospatial data and cloud computing to study environmental change, particularly surface water and wetland inundation dynamics. He is the creator of several widely used open-source Python packages, including geemap, leafmap, segment-geospatial, and geoai, which support advanced geospatial analysis and interactive visualization. His open-source work is available at the Open Geospatial Solutions on GitHub.
Acknowledgments
This book was written using MyST Markdown and compiled using Typst with the min-book template. Credits to developers and maintainers of the Typst and MyST Markdown projects. Special thanks to @mayconfmelo for the min-book template and their help with customizing the template for this book.
Licensing and Copyright
This book embraces the principles of open science and open education. To support transparency, learning, and reuse, the code examples in this book are released under a Creative Commons Attribution 4.0 International (CC BY 4.0) (https://creativecommons.org/licenses/by/4.0/) license. This means you are free to copy, modify, and distribute the code, even for commercial purposes, as long as appropriate credit is given. Please attribute code usage by citing the book or linking to the GitHub repository:
Wu, Q. (2025). Introduction to GIS Programming: A Practical Python Guide to Open Source Geospatial Tools. Independently published. ISBN 979-8286979455.
While the code is freely available, the text, figures, and images in this book are copyrighted by the author and may not be reproduced, redistributed, or modified without explicit permission. This includes all written content, custom diagrams, and embedded visualizations unless otherwise noted.
If you wish to reuse or adapt any non-code material from the book—for example, for teaching, presentations, or publications—please contact the author to request permission. This dual licensing approach helps balance open access to learning materials with the protection of original creative work.
Thank you for respecting these terms and supporting the open-source geospatial community.
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