QGIS is a leading user-friendly, cross-platform, open source, desktop geographic information system (GIS). It provides many useful capabilities and features and their number is continuously growing. More and more private users and companies choose QGIS as their primary GIS software because it is very easy to use, feature-rich, extensible, and has a big and constantly growing community. This book guides you from QGIS installation through data loading, and preparation to performing most common GIS analyses. You will perform different types of GIS analyses including density, visibility, and suitability analysis on practical, real-world data. Finally, you will learn how to become more productive and automate your everyday work with the help of the QGIS Processing framework and by developing your own Python plugins. By the end of this book, you will have all the necessary knowledge about handling and analyzing spatial data.
Learn how to use QGIS 3 to take your cartographic products to the highest level. QGIS 3.4 opens up exciting new possibilities for creating beautiful and compelling maps! Building on the first edition, the authors take you step-by-step through the process of using the latest map design tools and techniques in QGIS 3. With numerous new map designs and completely overhauled workflows, this second edition brings you up to speed with current cartographic technology and trends. See how QGIS continues to surpass the cartographic capabilities of other geoware available today with its data-driven overrides, flexible expression functions, multitudinous color tools, blend modes, and atlasing capabilities. A prior familiarity with basic QGIS capabilities is assumed. All example data and project files are included. Written by two of the leading experts in the realm of open source mapping, Anita and Gretchen are experienced authors who pour their wealth of knowledge into the book. Get ready to launch into the next generation of map design!
The latest guide to using QGIS 2.14 to create great maps and perform geoprocessing tasks with ease About This Book Learn how to work with various data and create beautiful maps using this easy-to-follow guide. Give a touch of professionalism to your maps both for functionality and look and feel with the help of this practical guide. A progressive hands-on guide that builds on a geo-spatial data and adds more reactive maps by using geometry tools. Who This Book Is For This book is great for users, developers, and consultants who know the basic functions and processes of GIS and want to learn to use QGIS to analyze geospatial data and create rich mapping applications. If you want to take advantage of the wide range of functionalities that QGIS offers, then this is the book for you. What You Will Learn Install QGIS and get familiar with the user interface Load vector and raster data from files, databases, and web services Create, visualize, and edit spatial data Perform geoprocessing tasks and automate them Create advanced cartographic outputs Design great print maps Expand QGIS using Python In Detail QGIS is a user-friendly open source geographic information system (GIS) that runs on Linux, Unix, Mac OS X, and Windows. The popularity of open source geographic information systems and QGIS in particular has been growing rapidly over the last few years. Learning QGIS Third Edition is a practical, hands-on guide updated for QGIS 2.14 that provides you with clear, step-by-step exercises to help you apply your GIS knowledge to QGIS. Through clear, practical exercises, this book will introduce you to working with QGIS quickly and painlessly. This book takes you from installing and configuring QGIS to handling spatial data to creating great maps. You will learn how to load and visualize existing spatial data and create data from scratch. You will get to know important plugins, perform common geoprocessing and spatial analysis tasks and automate them with Processing. We will cover how to achieve great cartographic output and print maps. Finally, you will learn how to extend QGIS using Python and even create your own plugin. Style and approach A step by step approach to explain concepts of Geospatial map with the help of real life examples
Master over 170 recipes that will help you turn QGIS from a desktop GIS tool into a powerful automated geospatial framework About This Book Delve into the undocumented features of the QGIS API Get a set of user-friendly recipes that can automate entire geospatial workflows by connecting Python GIS building blocks into comprehensive processes This book has a complete code upgrade to QGIS 2.18 and 30 new, valuable recipes Who This Book Is For This book is for geospatial analysts who want to learn more about automating everyday GIS tasks as well as programmers responsible for building GIS applications. The short, reusable recipes make concepts easy to understand and combine so you can build larger applications that are easy to maintain. What You Will Learn Use Python and QGIS to produce captivating GIS visualizations and build complex map layouts Find out how to effectively use the poorly-documented and undocumented features of the QGIS Python API Automate entire geospatial workflows by connecting Python GIS building blocks into comprehensive processes Create, import, and edit geospatial data on disk or in-memory Change QGIS settings programmatically to control default behavior Automatically generate PDF map books Build dynamic forms for field input In Detail QGIS is a desktop geographic information system that facilitates data viewing, editing, and analysis. Paired with the most efficient scripting language—Python, we can write effective scripts that extend the core functionality of QGIS. Based on version QGIS 2.18, this book will teach you how to write Python code that works with spatial data to automate geoprocessing tasks in QGIS. It will cover topics such as querying and editing vector data and using raster data. You will also learn to create, edit, and optimize a vector layer for faster queries, reproject a vector layer, reduce the number of vertices in a vector layer without losing critical data, and convert a raster to a vector. Following this, you will work through recipes that will help you compose static maps, create heavily customized maps, and add specialized labels and annotations. As well as this, we'll also share a few tips and tricks based on different aspects of QGIS. Style and approach This book follows a recipe-based problem-solution approach to address and dispel challenges faced when implementing and using QGIS on a regular basis.
Since the first edition of Open Source GIS: A GRASS GIS Approach was published in 2002, GRASS has undergone major improvements. This second edition includes numerous updates related to the new development; its text is based on the GRASS 5.3 version from December 2003. Besides changes related to GRASS 5.3 enhancements, the introductory chapters have been re-organized, providing more extensive information on import of external data. Most of the improvements in technical accuracy and clarity were based on valuable feedback from readers. Open Source GIS: A GRASS GIS Approach, Second Edition, provides updated information about the use of GRASS, including geospatial modeling with raster, vector, and site data, image processing, visualization, and coupling with other open source tools for geostatistical analysis and web applications. A brief introduction to programming within GRASS encourages new development. The sample data set used throughout the book has been updated and is available on the GRASS web site. This book also includes links to sites where the GRASS software and on-line reference manuals can be downloaded and additional applications can be viewed.
"Desktop GIS" explores the world of Open Source GIS software and provides a guide to navigate the many options available. Strategies for choosing a platform, selecting the right tools, integration, managing change, and getting support are presented.
Learn to view, edit and analyse geospatial data using QGIS and Python 3 Key FeaturesLeverage the power of QGIS to add professionalism to your mapsExplore and work with the newly released features like Python 3, GeoPackage, 3D views, Print layouts in QGIS 3.4Build your own plugins and customize maps using QT designerBook Description QGIS 3.4 is the first LTR (long term release) of QGIS version 3. This is a giant leap forward for the project with tons of new features and impactful changes. Learn QGIS is fully updated for QGIS 3.4, covering its processing engine update, Python 3 de-facto coding environment, and the GeoPackage format. This book will help you get started on your QGIS journey, guiding you to develop your own processing pathway. You will explore the user interface, loading your data, editing, and then creating data. QGIS often surprises new users with its mapping capabilities; you will discover how easily you can style and create your first map. But that’s not all! In the final part of the book, you’ll learn about spatial analysis and the powerful tools in QGIS, and conclude by looking at Python processing options. By the end of the book, you will have become proficient in geospatial analysis using QGIS and Python. What you will learnExplore various ways to load data into QGISUnderstand how to style data and present it in a mapCreate maps and explore ways to expand themGet acquainted with the new processing toolbox in QGIS 3.4Manipulate your geospatial data and gain quality insightsUnderstand how to customize QGIS 3.4Work with QGIS 3.4 in 3DWho this book is for If you are a developer or consultant familiar with the basic functions and processes of GIS and want to learn how to use QGIS to analyze geospatial data and create rich mapping applications, this book is for you. You’ll also find this book useful if you’re new to QGIS and wish to grasp its fundamentals
Geocomputation with R is for people who want to analyze, visualize and model geographic data with open source software. It is based on R, a statistical programming language that has powerful data processing, visualization, and geospatial capabilities. The book equips you with the knowledge and skills to tackle a wide range of issues manifested in geographic data, including those with scientific, societal, and environmental implications. This book will interest people from many backgrounds, especially Geographic Information Systems (GIS) users interested in applying their domain-specific knowledge in a powerful open source language for data science, and R users interested in extending their skills to handle spatial data. The book is divided into three parts: (I) Foundations, aimed at getting you up-to-speed with geographic data in R, (II) extensions, which covers advanced techniques, and (III) applications to real-world problems. The chapters cover progressively more advanced topics, with early chapters providing strong foundations on which the later chapters build. Part I describes the nature of spatial datasets in R and methods for manipulating them. It also covers geographic data import/export and transforming coordinate reference systems. Part II represents methods that build on these foundations. It covers advanced map making (including web mapping), "bridges" to GIS, sharing reproducible code, and how to do cross-validation in the presence of spatial autocorrelation. Part III applies the knowledge gained to tackle real-world problems, including representing and modeling transport systems, finding optimal locations for stores or services, and ecological modeling. Exercises at the end of each chapter give you the skills needed to tackle a range of geospatial problems. Solutions for each chapter and supplementary materials providing extended examples are available at https://geocompr.github.io/geocompkg/articles/. Dr. Robin Lovelace is a University Academic Fellow at the University of Leeds, where he has taught R for geographic research over many years, with a focus on transport systems. Dr. Jakub Nowosad is an Assistant Professor in the Department of Geoinformation at the Adam Mickiewicz University in Poznan, where his focus is on the analysis of large datasets to understand environmental processes. Dr. Jannes Muenchow is a Postdoctoral Researcher in the GIScience Department at the University of Jena, where he develops and teaches a range of geographic methods, with a focus on ecological modeling, statistical geocomputing, and predictive mapping. All three are active developers and work on a number of R packages, including stplanr, sabre, and RQGIS.
If you are an experienced Python developer who wants to create your own geospatial applications with minimum fuss, this is the book for you. While some familiarity with mapping applications would be an advantage, no prior knowledge of geospatial concepts is required. Even if you've never used QGIS before, this book will quickly get you up to speed.
A short book with a lot of hands-on examples to help you learn in a practical way.This book is great for users, developers, and consultants who know the basic functions and processes of a GIS but want to know how to use QGIS to achieve the results they are used to a full-fledged GIS.
