Abstract¶
How to use python, QGIS, GDAL, and other FOSS software packages to visualize geospatial data. Introduction to the book, webinar, setup and brief discussion of advantages and disadvantages of free and open source software.
Overview of FOSS software¶
A brief introduction to using free and open source tools.
Python for geospatial analysis
QGIS as a complementary tool
GDAL data processing in the terminal
Leafmap and other GISWQS tools for analysis and visualization
Advantages/Disadvantages¶
Generally the biggest plus to using FOSS tools is they’re free and flexible, you and in charge of the data and what it looks like, and your data doesn’t have to go to a cloud server to be used by whatever AI company to train their models. The biggest disadvantage is having to rely heavily on code and the terminal to run the tools. However, the latter is become less of a barrier with large language models (LLMs) such as Claude, script snippets, and other tricks we’ll show you that make life easier in the FOSS world.
| PROS | CONS |
|---|---|
| 🟢 Free | 🔴 Code and CLI to use |
| 🟢 Open-source | 🔴 Can frequently fail |
| 🟢 Learning code is fun | 🔴 Some software not updated |
| 🟢 Flexible | 🔴 Unavailable tools |
Using notebooks¶
Chapters¶
The book contains the following chapters or tutorials:
01-intro — Overview & Getting Started
Introduction to FOSS data visualization tools, advantages vs. disadvantages, and course structure. (This chapter)02-setup — Installation & Environment
Step-by-step setup guide for Python, QGIS, GDAL, and required packages. Virtual environment configuration and troubleshooting.03-viz_primer — Visualization Principles
Foundational design principles for data visualization grounded in academic research (Tufte, Bertin, Few). Learn what makes effective visualizations.04-eda — Exploratory Data Analysis
Comprehensive EDA techniques using pandas, matplotlib, seaborn, missingno, and ydata-profiling. Understand your data before visualization.05-charts — Creating Publication-Quality Charts
Tutorial on building polished charts with pandas, matplotlib, and seaborn. Covers styling, colormaps, and export formats for print.06-qgis — QGIS Essentials
Introduction to QGIS GUI for interactive map creation, visual analysis, and design. Complement your Python work with a graphical interface.07-workflows — Common Geospatial Workflows
Eight practical workflows: data loading, cleaning, vector operations, raster processing, static maps, interactive maps, multi-source integration, and automation.08-resources — Learning Resources & Data Sources
Curated directory of educational resources, developer tools, data sources (USGS, Google Earth Engine, OSM), and geospatial communities.