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Hands-On Geospatial Analysis with R and QGIS 3.4

Video Description

Integrate the best of both worlds: GIS and R programming

About This Video

  • Gain multi-disciplinary geospatial and application-development skills that are applicable to research, GIS consultants, data analysts, environmental services, and cartography companies.
  • Bridge the gap between GIS and programming languages to maximize the capacities of your geospatial workflow.
  • Use the most up-to-date and popular suite of software/packages for modern programming and best coding practices

In Detail

Integrating geospatial data science and traditional cartographic methods is in demand for modern geospatial analysts. In an age of flourishing data products, having a working proficiency with QGIS and R is an added advantage to every analyst.

This course introduces you to the full workflow, ranging from acquiring data, data wrangling, and analysis to outputting and publishing visualization products. We touch on a variety of datasets (including remote-sensing data and techniques) and incorporate machine learning in QGIS analytical steps. We further investigate geospatial analysis using the most up-to-date R packages, such as ggplot2, raster, sf, Leaflet, and Shiny.

By the end of the course, you will be able to produce interactive maps and professional cartographic products, deploy them as a Shiny application, and critique a variety of end-results.

The code bundle for this video course is available at - https://github.com/PacktPublishing/Hands-On-Geospatial-Analysis-with-R-and-QGIS-3.4

Downloading the example code for this course: You can download the example code files for all Packt video courses you have purchased from your account at http://www.PacktPub.com. If you purchased this course elsewhere, you can visit http://www.PacktPub.com/support and register to have the files e-mailed directly to you.

Table of Contents

  1. Chapter 1 : Introduction to Spatial Data and Operating Environment
    1. Course Overview 00:03:56
    2. Introduction to Spatial Data and GIS 00:02:59
    3. Geospatial Data Science and the Need for Reproducible Workflow 00:04:30
    4. Software Download and Setup 00:03:40
  2. Chapter 2 : Data Preparation and Basic Plotting
    1. Importing Data into QGIS 00:03:10
    2. Importing Data into R 00:06:07
    3. Turning Tables into Spatial Data 00:03:54
    4. Basic Plotting and Visualization 00:04:19
    5. Exporting Data 00:03:56
  3. Chapter 3 : Geospatial Processing with Tidyverse and sf Package
    1. Data Query and Acquisition from an API 00:04:44
    2. Tidy Data and Analysis with Tidyverse Library 00:06:13
    3. Statistical Summaries and Graphic Outputs 00:05:57
    4. Making an Interactive Map with Leaflet Library 00:05:58
    5. Map Specifics, Markers, Legends, and Scales 00:04:38
  4. Chapter 4 : Geospatial Processing with Raster Package and Machine Learning
    1. Landsat Data Query and Processing in QGIS 00:05:41
    2. Supervised Classification – Machine Learning Logic 00:04:01
    3. Supervised Classification – Landcover Analysis 00:05:22
    4. Integrating R and QGIS Workflow 00:06:09
    5. Presentation-Ready Map Product 00:05:49
  5. Chapter 5 : Visualization and Application Deployment
    1. Shiny Server – The Basics 00:02:57
    2. Sharing the Map on Shiny 00:02:51
    3. Reactive Values – Displaying Static Plots Upon Clicking on a Polygon 00:04:35
    4. Deploying the Application 00:03:19
    5. Advanced Customizations in Shiny 00:05:11
  6. Chapter 6 : Extending Beyond the Map
    1. Modern Cartographic Products 00:04:20
    2. Novel Ways of Map Making – Creating a Dot Map 00:03:41
    3. Data Types and Color Choices 00:05:01
    4. Where to Find Spatial Data? 00:03:12
    5. OpenStreetMaps and Further Resources 00:04:53