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Practical examples with real-world projects in GIS, Remote sensing, Geospatial data management and Analysis using the R programming language Key Features Understand the basics of R and QGIS to work with GIS and remote sensing data Learn to manage, manipulate, and analyze spatial data using R and QGIS Apply machine learning algorithms to geospatial data using R and QGIS Book 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 learn Install R and QGIS Get familiar with the basics of R programming and QGIS Visualize quantitative and qualitative data to create maps Find out the basics of raster data and how to use them in R and QGIS Perform geoprocessing tasks and automate them using the graphical modeler of QGIS Apply different machine learning algorithms on satellite data for landslide susceptibility mapping and prediction Who 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.
Go beyond the basics and unleash the full power of QGIS 3.4 and 3.6 with practical, step-by-step examples Key Features One-stop solution to all of your GIS needs Master QGIS by learning about database integration, and geoprocessing tools Learn about the new and updated Processing toolbox and perform spatial analysis Book Description QGIS is an open source solution to GIS and widely used by GIS professionals all over the world. It is the leading alternative to 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 and getting you acquainted with the latest QGIS 3.6 updates, this book will take you all the way through to teaching you how to create a spatial database and a GeoPackage. Next, you will learn how to style raster and vector data by choosing and managing different colors. The book will then focus on processing raster and vector data. You will be then taught advanced applications, such as creating and editing vector data. Along with that, you will also learn about the newly updated Processing Toolbox, which will help you develop the advanced data visualizations. The book will then explain to you the graphic modeler, how to create QGIS plugins with PyQGIS, and how to integrate Python analysis scripts with QGIS. By the end of the book, you will understand how to work with all aspects of QGIS and will be ready to use it for any type of GIS work. 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 plugins 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.
Step through loading GIS data, creating GIS data, styling GIS and making maps with QGIS following a simple narrative that will allow you to build confidence as you progress. Key Features Work with GIS data, a step by step guide from creation to making a map Perform geoprocessing tasks and automate them using model builder Explore a range of features in QGIS 3.4, discover the power behind open source desktop GIS Book Description QGIS is a user friendly, open source geographic information system (GIS). The popularity of open source GIS and QGIS, in particular, has been growing rapidly over the last few years. This book is designed to help beginners learn about all the tools required to use QGIS 3.4. This book will provide you with clear, step-by-step instructions to help you apply your GIS knowledge to QGIS. You begin with an overview of QGIS 3.4 and its installation. You will learn how to load existing spatial data and create vector data from scratch. You will then be creating styles and labels for maps. The final two chapters demonstrate the Processing toolbox and include a brief investigation on how to extend QGIS. Throughout this book, we will be using the GeoPackage format, and we will also discuss how QGIS can support many different types of data. Finally, you will learn where to get help and how to become engaged with the GIS community. What you will learn Use existing data to interact with the canvas via zoom/pan/selection Create vector data and a GeoPackage and build a simple project around it Style data, both vector and raster data, using the Layer Styling Panel Design, label, save, and export maps using the data you have created Analyze spatial queries using the Processing toolbox Expand QGIS with the help of plugins, model builder, and the command line Who this book is for If you know the basic functions and processes of GIS, and want to learn to use QGIS to analyze geospatial data and create rich mapping applications, then this is the book for you.
This is a book about how ecologists can integrate remote sensing and GIS in their daily work. It will allow ecologists to get started with the application of remote sensing and to understand its potential and limitations. Using practical examples, the book covers all necessary steps from planning field campaigns to deriving ecologically relevant information through remote sensing and modelling of species distributions. All practical examples in this book rely on OpenSource software and freely available data sets. Quantum GIS (QGIS) is introduced for basic GIS data handling, and in-depth spatial analytics and statistics are conducted with the software packages R and GRASS. Readers will learn how to apply remote sensing within ecological research projects, how to approach spatial data sampling and how to interpret remote sensing derived products. The authors discuss a wide range of statistical analyses with regard to satellite data as well as specialised topics such as time-series analysis. Extended scripts on how to create professional looking maps and graphics are also provided. This book is a valuable resource for students and scientists in the fields of conservation and ecology interested in learning how to get started in applying remote sensing in ecological research and conservation planning.
Solve all big data problems by learning how to create efficient data models Key Features Create effective models that get the most out of big data Apply your knowledge to datasets from Twitter and weather data to learn big data Tackle different data modeling challenges with expert techniques presented in this book Book Description Modeling and managing data is a central focus of all big data projects. In fact, a database is considered to be effective only if you have a logical and sophisticated data model. This book will help you develop practical skills in modeling your own big data projects and improve the performance of analytical queries for your specific business requirements. To start with, you’ll get a quick introduction to big data and understand the different data modeling and data management platforms for big data. Then you’ll work with structured and semi-structured data with the help of real-life examples. Once you’ve got to grips with the basics, you’ll use the SQL Developer Data Modeler to create your own data models containing different file types such as CSV, XML, and JSON. You’ll also learn to create graph data models and explore data modeling with streaming data using real-world datasets. By the end of this book, you’ll be able to design and develop efficient data models for varying data sizes easily and efficiently. What you will learn Get insights into big data and discover various data models Explore conceptual, logical, and big data models Understand how to model data containing different file types Run through data modeling with examples of Twitter, Bitcoin, IMDB and weather data modeling Create data models such as Graph Data and Vector Space Model structured and unstructured data using Python and R Who this book is for This book is great for programmers, geologists, biologists, and every professional who deals with spatial data. If you want to learn how to handle GIS, GPS, and remote sensing data, then this book is for you. Basic knowledge of R and QGIS would be helpful.
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.

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