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With the rapid advancements in satellite technology, earth remote sensing has become an indispensable tool for a wide range of applications, from environmental monitoring to disaster management. However, the vast amount of data generated by these satellites can be overwhelming for many researchers and practitioners who lack the necessary skills and tools to process and analyze it. This is where QGIS comes in. QGIS is a powerful, open-source Geographic Information System (GIS) software that has been extensively used in the field of earth remote sensing. It provides a user-friendly platform for processing, analyzing, and visualizing satellite imagery, enabling users to unlock the full potential of earth remote sensing data. The purpose of this book is to help researchers and practitioners who lack the necessary skills and tools to process and analyze satellite imagery using QGIS. There are several books that cover the use of QGIS for earth remote sensing, but most of them are either too technical or too general. This book fills this gap by providing a comprehensive and user-friendly guide to using QGIS for earth remote sensing applications. It includes a range of real-world case studies that demonstrate the power and versatility of QGIS for solving complex problems in earth remote sensing. This will provide readers with practical examples of how to use QGIS for earth remote sensing and inspire them to explore new applications and possibilities. The book is intended for GIS professionals, students (undergraduate and graduate), and researchers who are interested in using QGIS for earth remote sensing applications. It will be particularly useful for those who are new to QGIS or who want to expand their knowledge of the software for remote sensing purposes.
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.
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
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
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.
Become a QGIS power user and master QGIS data management, visualization, and spatial analysis techniques About This Book Explore and create time-based visualizations and build interactive maps Maximize your use of the QGIS features, plugins and toolbox automation Packed with lots of sample datasets to enable a better understanding of the code Who This Book Is For If you are an intermediate GIS user, with either previous experience in QGIS or any other GIS application, this is the book for you. The recipes can be used to learn more advanced techniques in QGIS or to replicate the functionalities equivalent to other GIS platforms. This book assumes that you already have a working QGIS system in place. What You Will Learn Import and export common tricky spatial data formats Perform classic vector and raster analysis with QGIS Utilize spatial databases and data management tools Use and create geographic web services and maps Explore and create time-based visualizations Perform network building and routing analysis Extend QGIS capabilities with popular plugins and toolbox automation Make beautiful and unique maps with customized cartography In Detail QGIS is a user-friendly, cross-platform desktop geographic information system used to make maps and analyze spatial data. QGIS allows users to understand, question, interpret, and visualize spatial data in many ways that reveal relationships, patterns, and trends in the form of maps. This book is a collection of simple to advanced techniques that are needed in everyday geospatial work, and shows how to accomplish them with QGIS. You will begin by understanding the different types of data management techniques, as well as how data exploration works. You will then learn how to perform classic vector and raster analysis with QGIS, apart from creating time-based visualizations. Finally, you will learn how to create interactive and visually appealing maps with custom cartography. By the end of this book, you will have all the necessary knowledge to handle spatial data management, exploration, and visualization tasks in QGIS. Style and approach This book covers practical examples, with step-by-step instructions on how to use real world data covering common GIS operations and the different analysis techniques. It provides detailed explanations and applications of QGIS concepts that will allow the user to effectively analyze spatial data.
"Abernathy provides a truly accessible and interdisciplinary introduction to geodata and geolocation covering both the conceptual and the practical. It is a must read for students or researchers looking to make the most of the spatial elements of their data" - Luke Sloan, Senior Lecturer in Quantitative Methods, Cardiff University 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 walking you through using data sources, 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.
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.