Go beyond the basics and unleash the full power of QGIS with practical, step-by-step examples About This Book This book is your one-stop solution to all of your GIS needs using the open source QGIS Master QGIS by learning about database integration, geoprocessing tools, Python scripts, advanced cartography, and custom plugins This example-rich, practical guide will help you create sophisticated analyses and maps Who This Book Is For If you are a GIS professional, a consultant, a student, or perhaps a fast learner who wants to go beyond the basics of QGIS, then this book is for you. It will prepare you to realize the full potential of QGIS. What You Will Learn Create and manage a spatial database Get to know advanced techniques to style GIS data Prepare both vector and raster data for processing Add heat maps, live layer effects, and labels to your maps Master LAStools and GRASS integration with the Processing Toolbox Edit and repair topological data errors Automate workflows with batch processing and the QGIS Graphical Modeler Integrate Python scripting into your data processing workflows Develop your own QGIS plugin In Detail QGIS is an open source solution to GIS. It is widely used by GIS professionals all over the world. It is the leading alternative to the proprietary GIS software. Although QGIS is described as intuitive, it is also by default complex. Knowing which tools to use and how to apply them is essential to producing valuable deliverables on time. Starting with a refresher on the QGIS basics, this book will take you all the way through to creating your first custom QGIS plugin. From the refresher, we will recap how to create, populate, and manage a spatial database. You'll also walk through styling GIS data, from creating custom symbols and color ramps to using blending modes. In the next section, you will discover how to prepare vector, heat maps, and create live layer effects, labeling, and raster data for processing. You'll also discover advanced data creation and editing techniques. The last third of the book covers the more technical aspects of QGIS such as using LAStools and GRASS GIS's integration with the Processing Toolbox, how to automate workflows with batch processing, and how to create graphical models. Finally, you will see how to create and run Python data processing scripts and write your own QGIS plugin with pyqgis. By the end of the book, you will understand how to work with all the aspects of QGIS, and will be ready to use it for any type of GIS work. Style and approach This step-by-step comprehensive guide will let you dig your teeth into working with spatial databases, creating your own QGIS plugins, and creating your own custom graphical models.
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.
Practical examples with real-world projects in GIS, Remote sensing, Geospatial data management and Analysis using the R programming language Key FeaturesUnderstand the basics of R and QGIS to work with GIS and remote sensing dataLearn to manage, manipulate, and analyze spatial data using R and QGISApply machine learning algorithms to geospatial data using R and QGISBook Description Managing spatial data has always been challenging and it's getting more complex as the size of data increases. Spatial data is actually big data and you need different tools and techniques to work your way around to model and create different workflows. R and QGIS have powerful features that can make this job easier. This book is your companion for applying machine learning algorithms on GIS and remote sensing data. You’ll start by gaining an understanding of the nature of spatial data and installing R and QGIS. Then, you’ll learn how to use different R packages to import, export, and visualize data, before doing the same in QGIS. Screenshots are included to ease your understanding. Moving on, you’ll learn about different aspects of managing and analyzing spatial data, before diving into advanced topics. You’ll create powerful data visualizations using ggplot2, ggmap, raster, and other packages of R. You’ll learn how to use QGIS 3.2.2 to visualize and manage (create, edit, and format) spatial data. Different types of spatial analysis are also covered using R. Finally, you’ll work with landslide data from Bangladesh to create a landslide susceptibility map using different machine learning algorithms. By reading this book, you’ll transition from being a beginner to an intermediate user of GIS and remote sensing data in no time. What you will learnInstall R and QGISGet familiar with the basics of R programming and QGISVisualize quantitative and qualitative data to create mapsFind out the basics of raster data and how to use them in R and QGISPerform geoprocessing tasks and automate them using the graphical modeler of QGISApply different machine learning algorithms on satellite data for landslide susceptibility mapping and predictionWho this book is for This book is great for geographers, environmental scientists, statisticians, and every professional who deals with spatial data. If you want to learn how to handle GIS and remote sensing data, then this book is for you. Basic knowledge of R and QGIS would be helpful but is not necessary.
If you are a geospatial analyst who wants to learn more about automating everyday GIS tasks or a programmer who is responsible for building GIS applications,this book is for you. The short, reusable recipes make concepts easy to understand. You can build larger applications that are easy to maintain when they are put together.
Develop analytical location-based web applications with QGIS About This Book Tame geographic information workflows with QGIS blueprints for smart web applications Create geographic web applications using QGIS and free/open source software Blueprints provide real-world applications covering many use cases Who This Book Is For This book encompasses relatively experienced GIS developers who have a strong grounding in the fundamentals of GIS development. They will have used QGIS before, but are looking to understand how to develop more complex, layered map applications that expose various data sets, utilize different visualizations, and are consumable (usable) by end users What You Will Learn Review geographic information principles and the application of these principles in the QGIS free/open source ecosystem Perform advanced analysis with site selection, hydrologic, and topological networks Build performant web applications by tile caching and generating static assets Provide collaborative editing capabilities for your team or community Develop custom and dynamic analysis and visualization capabilities Select the best components from desktop and web, for your use case Integrate it with social media and crowdsourcing In Detail QGIS, the world's most popular free/open source desktop geographic information system software, enables a wide variety of use cases involving location – previously only available through expensive specialized commercial software. However, designing and executing a multi-tiered project from scratch on this complex ecosystem remains a significant challenge. This book starts with a primer on QGIS and closely related data, software, and systems. We'll guide you through six use-case blueprints for geographic web applications. Each blueprint boils down a complex workflow into steps you can follow to reduce time lost to trial and error. By the end of this book readers should be able to build complex layered applications that visualize multiple data sets, employing different types of visualization, and give end users the ability to interact with and manipulate this data for the purpose of analysis. Style and approach This is a comprehensive guide to the application of QGIS and free/open source software in creating web applications from analysis. Step-by-step blueprints guide the reader through analytical and web development topics and designs.
This book navigates the numerous American and Canadian cartographic resources available in print, and online, offering information on how to locate and access the large variety of resources. Cartographic materials are highlighted and summarized, along with lists of map libraries and geospatial centers, and related professional associations.
Exploring the U.S. Census gives social science students and researchers alike the tools to understand, extract, process, and analyze data from the decennial census, the American Community Survey, and other data collected by the U.S. Census Bureau. Donnelly′s text provides a thorough background on the data collection methods, structures, and potential pitfalls of the census for unfamiliar researchers, collecting information previously available only in widely disparate sources into one handy guide. Hands-on, applied exercises at the end of the chapters help readers dive into the data. Along the way, the author shows how best to analyze census data with open-source software and tools. Readers can freely evaluate the data on their own computers, in keeping with the free and open data provided by the Census Bureau. By placing the census in the context of the open data movement, this text makes the history and practice of the census relevant so readers can understand what a crucial resource the census is for research and knowledge.
Using Geodata and Geolocation in the Social Sciences: Mapping our Connected World provides an engaging and accessible introduction to the Geoweb with clear, step-by-step guides for: Capturing Geodata from sources including GPS, sensor networks and Twitter Visualizing Geodata using programmes including QGIS, GRASS and R Featuring colour images, practical exercises and a companion website packed with resources, this book is the perfect guide for students and teachers looking to incorporate location-based data into their social science research.
Over the past few decades the world has been organized through the growth and integration of geographic information systems (GIS) across public and private sector industries, agencies, and organizations. This has happened in a technological context that includes the widespread deployment of multiple digital mobile technologies, digital wireless communication networks, positioning, navigation and mapping services, and cloud-based computing, spawning new ways of imagining, creating, and consuming geospatial information and analytics. GIS: An Introduction to Mapping Technologies is written with the detached voices of practitioner scholars who draw on a diverse set of experiences and education, with a shared view of GIS that is grounded in the analysis of scale-diverse contexts emphasizing cities and their social and environmental geographies. GIS is presented as a critical toolset that allows analysts to focus on urban social and environmental sustainability. The book opens with chapters that explore foundational techniques of mapping, data acquisition and field data collection using GNSS, georeferencing, spatial analysis, thematic mapping, and data models. It explores web GIS and open source GIS making geospatial technology available to many who would not be able to access it otherwise. Also, the book covers in depth the integration of remote sensing into GIS, Health GIS, Digital Humanities GIS, and the increased use of GIS in diverse types of organizations. Active learning is emphasized with ArcGIS Desktop lab activities integrated into most of the chapters. Written by experienced authors from the Department of Geography at DePaul University in Chicago, this textbook is a great introduction to GIS for a diverse range of undergraduates and graduate students, and professionals who are concerned with urbanization, economic justice, and environmental sustainability.
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.
This open access book represents a comprehensive review of available land-use cover data and techniques to validate and analyze this type of spatial information. The book provides the basic theory needed to understand the progress of LUCC mapping/modeling validation practice. It makes accessible to any interested user most of the research community's methods and techniques to validate LUC maps and models. Besides, this book is enriched with practical exercises to be applied with QGIS. The book includes a description of relevant global and supra-national LUC datasets currently available. Finally, the book provides the user with all the information required to manage and download these datasets.
"This book examines how the methods and data sources used to generate DEMs and calculate land surface parameters have changed over the past 25 years. The primary goal is to describe the state-of-the-art for a typical digital terrain modeling workflow that starts with data capture, continues with data preprocessing and DEM generation, and concludes with the calculation of one or more primary and secondary land surface parameters"--