Sarafova / Ivanov / Cutts Learn QGIS

Techniques for efficient spatial analysis
1. Auflage 2026
ISBN: 978-1-83620-330-8
Verlag: Packt Publishing
Format: EPUB
Kopierschutz: 0 - No protection

E-Book, Englisch, 432 Seiten

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.

Autoren/Hrsg.

Sarafova, Eugenia

Ivanov, Ivan

Cutts, Andrew

Graser, Anita

Leseproben

Preface

QGIS has become one of the most popular platforms for working with spatial data. It is widely used in environmental studies, urban planning, education, business, and satellite data analysis. This book is written for those who want to get hands-on with QGIS, whether you’re just beginning your GIS journey or looking to build a stronger foundation through practical, real-world examples and data. We begin with the basics: how to install QGIS, load various types of vector and raster data, and understand the structure of spatial layers. From there, we move through map styling and visualization techniques, exploring symbology, labeling, and map layout design. A full chapter is dedicated to commonly-used map types, where we introduce the cartographic principles behind thematic maps, such as choropleths, dot density maps, and proportional symbol maps.

Once the fundamentals are in place, we go deeper into spatial analysis. First, you can explore environmental applications (for example, land cover, buffering protected areas, and overlaying biodiversity zones), then dive into socioeconomic contexts, such as analyzing accessibility or population density per neighborhood. We explore how to use commonly-used tools such as count points in polygon, sum line lengths, isochrones, and others by using openly available datasets.

The book also introduces Earth observation data in an accessible way, covering how to access and work with satellite imagery from programs such as Copernicus and Landsat, and how to apply basic classification or spectral analysis inside QGIS using plugins such as the Semi-Automatic Classification Plugin (SCP). Because working with data comes with responsibilities, we dedicate an entire chapter to data security and ethical considerations, helping you learn how to handle sensitive information and understand licensing, metadata, and good data practices.

At the end, we take a look at the emerging role of artificial intelligence in GIS. Here, we introduce how AI can assist with spatial workflows, generate code, and help users explore GIS concepts through conversation—offering a glimpse into the future of geospatial technologies.

This book is based on the latest QGIS Long-Term Release (LTR) version at the time of writing. The content has been designed to support both classroom instruction and self-paced learning. While we focus on core functionality and open data, the principles are transferable to more advanced GIS work and scalable projects.

Whether you’re a student, educator, environmental analyst, urban planner, or simply a map enthusiast, this book will help you gain practical skills and confidence in using one of the most powerful free and open source GIS tools available today.

Who this book is for

This book is for GIS beginners of all kinds: students, educators and professionals from fields such as geography, environmental science, urban studies, planning, civil engineering or landscape architecture. It is also suitable for government workers, nonprofit staff, and consultants who use spatial data in their work.

Whether you’re entering GIS for the first time or need a practical refresher, this book will help you gain confidence working with real data in QGIS.

What this book covers

, , helps you take your first steps in QGIS. You’ll learn how to download and install the software on your machine, explore the user interface, and set up your first GIS project. We will walk through project settings and basic navigation tools to help you feel comfortable before moving on to more advanced topics.

, , introduces the different types of geospatial data you’ll be working with—vector and raster layers—and how they behave inside QGIS. You’ll learn how to load data from a variety of sources, including shapefiles, GeoPackages, spreadsheets, and web services.

, , focuses on where to find free and open geospatial data online. We explore major data providers, international portals, national geoportals, and examples from OpenStreetMap. You’ll also learn how to evaluate whether a dataset is appropriate for your project based on factors such as resolution, scale, and licensing.

, , dives into the world of geographic data, which is tied to the Earth’s surface, and so this chapter explains how QGIS handles coordinate systems and map projections. You’ll learn the difference between geographic and projected CRS, how to reproject layers, and how to avoid common mistakes related to mismatched coordinate systems in your maps.

, , explores symbology and styling tools. You’ll learn how to use colors, shapes, and size to represent your data meaningfully, whether it’s a simple categorical map or a complex quantitative visualization. Topics include graduated styling, rule-based symbology, and customizing legends.

, , focuses on preparing your map for presentation. You’ll learn how to create a layout, add elements such as map frames, titles, legends, and north arrows, and control the design and composition.

, , walks you through all the widely used types of thematic maps and how to create them in QGIS. You’ll learn when and how to use choropleth maps, proportional symbol maps, dot maps, heatmaps, and more. Each example includes real data and practical tips to make your maps both informative and visually effective.

, , shows how to apply spatial tools to real-world environmental scenarios. You’ll work with buffers, overlays, terrain models, and raster calculations to answer questions related to land cover, conservation zones, protected areas, and environmental impact. The focus is on using spatial analysis to support decision-making in ecological and landscape contexts.

, , takes the same tools and applies them to data about people, infrastructure, and services. You’ll calculate accessibility, identify underserved areas, measure infrastructure length, and analyze patterns in urban and rural contexts.

, , explores the fundamentals of using the PyQGIS API and associated libraries, and walks you through building a custom QGIS plugin.

, , shows you how to access and use satellite imagery in QGIS – from downloading free data from Copernicus and Landsat programs to performing simple classification and spectral analysis. We also introduce tools such as the Semi-Automatic Classification Plugin (SCP) to make remote sensing more approachable for beginners.

, , teaches you how to bring real-world data into QGIS using mobile apps and digital surveys. You’ll learn how to prepare a project with advanced form for data collection with QField, use GNSS on mobile, and collect features with geometry and attributes on mobile. This is ideal for field mapping, citizen science, and environmental monitoring projects.

, , explores the handling of geospatial data, which comes with responsibility. This chapter explains how to manage sensitive information, understand data licenses, and apply metadata standards. We also discuss anonymization, ethical map design, and how to avoid reinforcing bias or misrepresentation through spatial visualizations.

, , introduces how artificial intelligence is entering the world of GIS. We show how tools such as QChatGPT can be used inside QGIS to support your work—whether you need help writing expressions, generating code, or asking spatial questions in natural language. This chapter gives a glimpse into future directions of GIS technology.

To get the most out of this book

You will need to have access to QGIS. Everything else is covered in the book!

Download the example code files

This book includes a complete downloadable code bundle containing all the example projects and files used throughout the chapters. We recommend downloading the bundle so you can follow along smoothly and experiment with the examples.

Use the bundle as a practical starting point. Modify it, extend it, and apply what you learn by creating your own variations as you progress through the chapters.

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