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Hands-On Geospatial Analysis with R and QGIS 3.4 [Video]

More Information
  • Develop a Shiny application for geospatial data processing and visualizations using R and QGIS 3.4.
  • Implement an efficient and reproducible workflow for geospatial analysis.
  • Create interactive and professional mapping products and publish them on open applications. 
  • Conduct advanced geospatial analyses that address practical issues such as land cover using machine algorithms.
  • Use modern and novel techniques to code with best practices.
  • Utilize skills to serve a wide range of groups, including governmental organizations, Academia, consulting firms, and natural-resource industries.
  • Critique a variety of geospatial data products and optimize your geospatial abilities to communicate your findings effectively

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

Style and Approach

A step-by-step guide using realistic examples and illustrative slides to help you achieve a full workflow.

  • 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
Course Length 2 hours 11 minutes
Date Of Publication 31 Jan 2019
Supervised Classification – Machine Learning Logic
Supervised Classification – Landcover Analysis
Integrating R and QGIS Workflow
Presentation-Ready Map Product
Sharing the Map on Shiny
Reactive Values – Displaying Static Plots Upon Clicking on a Polygon
Deploying the Application
Advanced Customizations in Shiny


Jane Wang

Jane Wang is a GIS Developer and has a Masters Degree in Geospatial Sciences with experiences in research, teaching, data analysis, and visualizations. She has 6 years' academic and 3 years' professional experience working with geospatial products and communicating scientific information in appealing visual outputs using R, GIS, Python, and Adobe Suite. She has been given awards for her creative and novel geospatial work in international conferences and is also an active member of the R community. She has actively communicated with and taught a wide-ranging audience.