Learn QGIS: Techniques for efficient spatial analysis

Gain a deep understanding of QGIS, the world's most popular free and open-source GIS tool for spatial analysis and mapping

Key Features

• Find out how to effectively use QGIS by exploring its features in depth
• Practice real-world scenarios for spatial data extraction, analysis, and mapping
• Explore cutting-edge topics in the geospatial industry, such as machine learning and artificial intelligence
• Purchase of the print or Kindle book includes a free PDF eBook

Book Description

Spatial data is everywhere, requiring professionals from various fields to capture, visualize, and analyze spatial datasets from a myriad of sources. In this fifth edition of Learn QGIS, the authors draw from their vast experience in geospatial technologies to guide you through the most essential data editing, mapping, and analysis tools available in the world’s most popular free and open-source geographic information system (GIS) software.

This updated edition incorporates the latest advancements in QGIS, comprehensively guiding you through creating, visualizing, and analyzing spatial datasets. Starting with data creation and editing, the book explores map projections, spatial data sources, and visualization techniques. You’ll develop expertise in cartographic principles, conduct spatial analysis for environmental and socioeconomic applications, and work with Earth Observation data from Copernicus and NASA.

The addition of new topics such as field data collection, data security, and ethical considerations ensures that you stay ahead of modern GIS challenges. The book also introduces AI in GIS, enabling you to leverage machine learning for geospatial data science tasks.

By the end of this QGIS book, you’ll have become proficient in geospatial analysis using QGIS and Python.

What you will learn

• Grasp the core concepts of spatial data importing, managing, and analysis
• Access geospatial data sources from public organizations
• Find out how to handle different map projections and regulations
• Get to grips with the basics of map design and common map types
• Understand spatial data analysis and problem solving through using real-world scenarios
• Capture, download, and analyze Earth Observation data
• Build mobile projects for data collection on the go
• Integrate the power of AI and ML, and learn the ethical aspects of their use in GIS

Who this book is for

This fully updated edition is for GIS professionals, developers, researchers, and students in environmental management, urban studies, transportation, and spatial planning. Educators can integrate step-by-step exercises into their technical training as this book provides a hands-on approach to spatial data collection, management, and analysis, incorporating new QGIS capabilities.

Table of Contents

1. Where Do I Start?
2. Data Creation and Editing
3. Spatial Data Sources
4. Understanding Coordinates and Map Projections
5. Visualizing Data
6. Creating Great Maps
7. Common Map Types
8. Spatial Analysis - Environmental Applications
9. Spatial Analysis - Socioeconomic Applications
10. Extending QGIS with Python
11. Earth Observation Data Analysis
12. Field Data Collection
13. Data Security and Ethical Considerations
14. AI in QGIS

Eugenia Sarafova is Associate Professor with 20 years of experience in teaching GIS & Cartography. Author of training programs, courses and books dedicated to geospatial technologies. In the last several years Eugenia has presented at hundreds of live and online events as a host, presenter and science communicator.

Ivan Ivanov is a geographer and software engineer heavily involved in developing and promoting free and open source geospatial software. Since 2019 he is actively contributing in three of the flagship fully open-source GIS applications - QGIS, QField and QFieldCloud.

Andrew Cutts holds a geography degree and a masters degree in GIS and has almost 20 years of experience in working with geospatial technology. He currently works as a freelance geospatial consultant. He has worked in local government, large multinational companies, and small and medium-sized enterprises. He has run a geospatial blog for almost 3 years and is a co-host of the #scenefromabove podcast. Andrew has spoken at events worldwide on GIS and Earth observation. He is a keen user of Python, especially for rapid prototyping for geospatial challenges. Currently, he is working with clients to maximize their investment with geospatial technology through direct consulting, training, and technical writing.

Anita Graser is a spatial data scientist, open source GIS advocate, and author with a background in geographic information science. She is currently working with the Center for Mobility Systems at the Austrian Institute of Technology in Vienna and teaching QGIS classes at UNIGIS Salzburg. She serves on the QGIS project steering committee. and has published several books about QGIS. Furthermore, she develops tools, such as the Time Manager plugin for QGIS.