[Intermediate] Spatial Data Analysis with R, QGIS & More from Udemy

What's inside

Learning objectives

Carry out the most common spatial data analysis and gis tasks using free software tools
Perform advanced spatial data analysis and mapping using both r and qgis
Develop robust map-making skills including harnessing the power of google earth.
Get started with using the powerful, freeware tool grass gis for some spatial data analysis tasks

Stop spending money on paid-for gis software tools
Have a solid foundation to learn advanced gis tasks
Gain experience in working with a variety of different spatial data and gain hands-on expertise

Carry out the most common spatial data analysis and gis tasks using free software tools
Perform advanced spatial data analysis and mapping using both r and qgis
Develop robust map-making skills including harnessing the power of google earth.
Get started with using the powerful, freeware tool grass gis for some spatial data analysis tasks
Stop spending money on paid-for gis software tools
Have a solid foundation to learn advanced gis tasks
Gain experience in working with a variety of different spatial data and gain hands-on expertise

Syllabus

By the end of this section, the students will have been introduced to the key spatial concepts. Further, they will know about the different free software tools such as R, QGIS , GRASS & their use

Introduction: Welcome to the Course

In this lecture students will be briefly introduced to the concepts pertaining to spatial data analysis such as coordinate reference systems and the different spatial data that will be used in the course.

Get Started with R and QGIS

This lecture will show how to configure GRASS to read in our own data. The demonstration data are in folder "Lecture_4-grass_eg1"

Conclusion to Section 1

This quiz will test the introductory concepts relating to spatial data and the software tools that we will use in this course

Students will learn the properties of shapefiles and their visualization. Students will be proficient in basic shapefile attribute visualization techniques and choropleth mapping

This lecture presents a brief overview of what shapefiles are and their attribute table is. Further I briefly demonstrate how to modify the basic properties of shapefiles to improve their appearance. The data used for the lecture demonstration are present in the folder "Lecture_6-countries_shp"

In this section we will see how shapefiles can be rendered and visualized using qualitative attributes. We will focus on the world map and display the different continents in there as a way of making the world map more intuitive. The data used for the lecture demonstration are present in the folder "Lecture_6-countries_shp"

In this section we will see how shapefiles can be rendered and visualized using quantitative attributes. We will focus on the world map and use the country areas in there as a way of making the world map more intuitive. The data used for the lecture demonstration are present in the folder "Lecture_6-countries_shp"

In this lecture the students will be exposed to basic concepts of mapping shapefile data and mapping shapefile attributes in R using spplot function. The data used for the lecture demonstration are present in the folder "Lecture_6-countries_shp"

This lecture will demonstrate how to build choropleth maps using shapefiles in R. The students will also be introduced to the R package, GISTools for choropleth mapping. The data used for the lecture demonstration are present in the folder "Lecture_6-countries_shp"

In this lecture, students will learn how to use Google Earth data and display their own spatial data on Google Earth base layers. The data for this lecture are in folder "Lecture_11-ggplot_GE_R"

Conclusion to Section 2

Spatial Data Visualization Quiz

By the end of this section, students will have an in-depth knowledge of shapefile processing operations. We will focus on shapefile statistics, clipping and intersecting different shapefiles

In this section I will demonstrate how to add data from a CSV file to a shapefile using a spatial join. Spatial joins work by combining data for common attributes in CSV and the shapefile. The data for this lecture are in folder "Lecture_13-JpnPop_joinR".

In this lecture we will see how to carry out the spatial joining demonstrated in the previous lecture in QGIS using R. The data for this lecture are in folder "Lecture_13-JpnPop_joinR".

In this lecture I will demonstrate how to compute basic descriptive statistics from a shapefile using R. The data used for the lecture demonstration are present in the folder "Lecture_6-countries_shp"

In this lecture the students will learn how to add a user defined buffer to a polygon or a polyline. The data used in this lecture are present in the folder "Lecture_16-buffer_vector_data".

In this lecture the students will learn how to add a user defined buffer to a polygon or a polyline. The data used in this lecture are present in the folder "Lecture_17-mynamar_intersecn".

This lecture demonstrates how to make an outer buffer/boundary in both R and QGIS. The data for this lecture are in folder "Lecture_18-outer_buffer".

A brief description of the data used for lectures 20--23

In this lecture the students will learn how to carry out the union between 2 shapefiles in QGIS. The data used in this lecture are present in the folder "Lecture_17-mynamar_intersecn".

In this lecture the students will learn how to clip a shapefile in QGIS. The data used in this lecture are present in the folder "Lecture_17-mynamar_intersecn".

In this lecture the students will learn how to intersect 2 shapefiles in QGIS. The data used in this lecture are present in the folder "Lecture_17-mynamar_intersecn".

In this lecture I will show how to carry out intersection between two shapefiles and clip the bigger shapefile using the smaller shapefile as a cookie-cutter in R. The data used in this lecture are present in the folder "Lecture_17-mynamar_intersecn".

Conclusion to Section 3

This quiz is designed to test the ability of the students to carry out analysis of shapefile data

Will be able to able to build basic visualizations and carry out specific analysis tasks related to point XY data such as interpolation.

In this lecture I will demonstrate how to make a heat map from point/XY data in QGIS and visually display the distribution and concentration of attributes using QGIS. The data used in this lecture are present in the folder "Lecture_25-Heatmap".

A brief introduction to the theory behind Kernel Density Estimation (KDE)

In this lecture I will demonstrate how to use geographical point data to map the distribution and clustering of an attribute using Kernel Density Estimates in R. A brief introduction to the package spatstat (used for analyzing point/XY data) has been provided. The data used in this lecture are present in the folder "Lecture_27-uk_plaque".

In this lecture, the students will learn how to plot heat maps to show the spatial distribution and concentration of point data on Google Earth in R. The data for this lecture are in "Lecture_27-uk_plaque".

Brief Introduction to the Concepts of Interpolation

In this lecture, the students will learn how to carry out interpolation of point data in QGIS. The data for this lecture are in "Lecture_30-aust_elev".

Students will be able to carry out thin spline interpolation on point data to produce a raster surface. The data for this lecture are in "Lecture_31-interpolation_r".

This lecture demonstrates how to carry out the IDW interpolation of point data in R. Students will be able to carry out thin spline interpolation on point data to produce a raster surface. The data for this lecture are in "Lecture_31-interpolation_r".

This lecture briefly demonstrates how to carry out kriging in R. Students will be able to carry out thin spline interpolation on point data to produce a raster surface. The data for this lecture are in "Lecture_31-interpolation_r".

This lecture demonstrates how to use GRASS to implement some interpolation techniques on point data. The data for this lecture are in "Lecture_32-interpolation_grass1".

Conclusion to Section 4

This quiz seeks to test the understanding of carrying out point patterns analysis of spatial data

Will be able to able to carry out basic mapping specific analysis tasks related to raster data such as improved raster display, DEM analysis.

I will demonstrate how to display raster data in QGIS and how to use Properties to enhance the rendering and visualization of these data. The data for this lecture are in "Lecture_37-digital elevation model_easia".

This lecture will demonstrate how to display raster data in R. A brief introduction the package rasterVis which is used for visualizing raster data in R will be provided. The data for this lecture are in "Lecture_37-digital elevation model_easia".

This lecture will demonstrate how to extract raster statistics for a given set of shapefile polygons. The data for this lecture are in "Lecture_38-zonal_stats".

In this lecture I will demonstrate how to merge and stitch together non-overlapping rasters in QGIS . The data for these lectures are in folder "Lecture_39-raster_merging"

This lecture demonstrates how we can merge adjacent, non-overlapping rasters in R. The data for these lectures are in folder "Lecture_39-raster_merging"

Briefly demonstrate how to clip a raster to desired boundary using a shapefile as cookie-cutter in R and QGIS. The data for this lecture are in "Lecture_37-digital elevation model_easia".

Briefly demonstrate how to clip a raster to desired boundary using a shapefile as cookie-cutter in GRASS. The data for this lecture are in "Lecture_42-clipRasters_grass".

In this lecture, I will demonstrate how to carry out basic terrain analysis calculations on DEMs using GRASS. The data for this lecture are in "Lecture_37-digital elevation model_easia".

In this lecture I will show you how to geo-reference image data using QGIS. I will show how to add coordinate information both manually and using a Google Earth base layer map. The data for this lecture are in folder "Lecture_44-georeferencing_qgis"

Conclusion to Section 5

A brief quiz pertaining to processing of raster data

Students will be able to undertake more advanced GIS tasks such suitability analysis, building automated analysis workflows

Rationale For This Section

This lecture shows how simple GIS tasks can be automated as a part of a workflow in QGIS. The data for this lecture are in "Lecture_37-digital elevation model_easia".

Multi-Criteria Decision Making/Suitability Analysis-Theory

This lecture will show how to implement the AHP process on raster data in QGIS. The data for this lecture are in "Lecture_49-suitability analysis_MCDM".

This lecture will show how to build a basic interactive webmap in QGIS. The data for this lecture are in "Lecture_50-webmap_qgis".

This lecture shows how the student can build interactive web maps using their own spatial data in R. An introduction to the leaflet package is provided. The data for this lecture are in "Lecture_50-webmap_qgis".

CONCLUSION

Additional Material

Work With R's Inbuilt Geospatial Data

Use ggplot2 to visualize geographic data

Github

Brazil Time Lapse

Assign Legends in QGIS

Posit On POSIT

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Develops skills and knowledge that are highly relevant to GIS professionals and researchers

Taught by Minerva Singh, who has several years of research experience in Quantitative Ecology and an MPhil in Geography and Environment

Builds on basic spatial data analysis tasks and teaches users how to practically implement more advanced GIS tasks such as interpolation, mapping spatial data, geo-referencing, and detailed vector processing

Introduces another powerful free GIS software, GRASS, in addition to making you proficient in R and QGIS

Covers complex GIS techniques and provides hands-on experience in working with a variety of different spatial data

Suitable for intermediate learners in spatial data analysis

Reviews summary

Engaging course with practical exercises

Learners say that this engaging course offers practical exercises that encourage application of concepts. Reviewers appreciated the hands-on approach of the course and found the quizzes helpful for reinforcement.

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in [Intermediate] Spatial Data Analysis with R, QGIS & More with these activities:

Review Geospatial Concepts

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Refresh your understanding of fundamental geospatial concepts to enhance your comprehension of the course materials

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Review online resources on coordinate reference systems
Explore different types of spatial data and their characteristics
Familiarize yourself with common spatial data formats
Practice identifying and interpreting spatial data

Explore GRASS GIS Tutorial

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Follow a guided tutorial to familiarize yourself with the capabilities and workflow of GRASS GIS

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Access the online tutorial documentation
Choose a tutorial relevant to your interests
Work through the tutorial steps
Experiment with different options and parameters
Apply the acquired knowledge to your own projects

Learn the basics of R

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This activity will help you strengthen your foundational understanding of R, which will make it easier to follow along with the course material and apply the concepts you learn.

Browse courses on R

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Take an online tutorial on R
Complete the R exercises in the course syllabus
Build a simple R script

15 other activities

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Review Introduction to Geographic Information Systems book by A. Keith Turner

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This book will be a reference and will help you prepare for the course. It will also provide additional depth and breadth.

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Read Chapter 1-3 of the book, focusing on key concepts and definitions
Summarize the main points of each chapter and create a visual overview of the material

Explore R / QGIS cheat sheets

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A cheat sheet is a quick reference of frequently used commands and their syntax. It helps improve recall of information and quickly looking up how to write various commands.

Browse courses on R

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Find R cheatsheets for a quick overview of functions and commands
Bookmark or download your favorite R cheatsheet for easy access
Locate QGIS cheatsheets for guidance on tools and features
Keep the downloaded cheatsheets accessible to use whenever you need them during the course

Complete Shapefile Processing Exercises

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Engage in hands-on exercises to strengthen your skills in manipulating and analyzing shapefile data

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Download and open a shapefile
Explore the attributes and geometry of the shapefile
Perform basic operations such as buffering and clipping
Analyze spatial relationships between different shapefiles
Export the results in a desired format

Watch video tutorials on advanced GIS techniques

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Video tutorials provide visual demonstrations and explanations, making complex concepts easier to understand and retain.

Browse courses on GIS

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Search for video tutorials on specific GIS techniques you want to improve in, such as interpolation, spatial analysis, or data visualization
Select reputable sources, such as university channels, industry experts, or online learning platforms
Take notes while watching the videos, focusing on key concepts and practical applications
Pause and rewind the videos as needed to fully understand the explanations

Review the fundamentals of R

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Refreshes the student's memory of fundamentals that will be used extensively in this course

Browse courses on R Programming

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Review the basics of R syntax
Practice creating and manipulating data frames
Work with basic R functions

Review the basics of QGIS

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Refreshes the student's memory of fundamentals that will be used extensively in this course

Browse courses on QGIS

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Review the basics of QGIS interface
Practice loading and visualizing spatial data
Work with basic QGIS tools

Complete practice exercises on RStudio

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Practice exercises provide an opportunity to apply the concepts and techniques learned in the course, reinforcing understanding and improving proficiency.

Browse courses on R

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Access practice exercises provided by the course instructor or find additional exercises online
Set aside dedicated time to work on these exercises, aiming to complete at least 1-2 exercises per week
Use RStudio to execute the code and analyze the results
Review your answers and identify areas where you need further clarification or practice

Practice spatial data analysis in R and QGIS

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This activity will help you improve your skills in using R and QGIS for spatial data analysis.

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Complete the practice exercises in the course lectures
Find a dataset and perform a spatial analysis on your own

Practice spatial data analysis tasks in QGIS

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Provides hands-on experience in performing common spatial data analysis tasks, reinforcing understanding and skills

Browse courses on Spatial Data Analysis

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Load a spatial dataset into QGIS
Perform basic spatial analysis operations (e.g., buffer, intersection)
Create thematic maps and visualizations
Export and share the results

Practice spatial data analysis tasks in R

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Provides hands-on experience in performing common spatial data analysis tasks, reinforcing understanding and skills

Browse courses on Spatial Data Analysis

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Load a spatial dataset into R
Perform basic spatial analysis operations (e.g., buffer, intersection)
Create thematic maps and visualizations
Export and share the results

Form a small study group with other enrolled students

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Collaborating with other students can provide various viewpoints on course concepts and help improve understanding.

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Reach out to classmates through the course discussion board or social media
Connect with 2-3 students who are also interested in forming a study group
Set up regular virtual or in-person meetings to discuss course materials, work on assignments together, and quiz each other
Alternatively, join an existing study group if one has been formed

Write a blog post or article on a GIS topic

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Writing about a GIS topic helps solidify understanding, improve communication skills, and share knowledge with others.

Browse courses on GIS

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Choose a specific GIS topic that you are familiar with and passionate about
Research and gather information from reputable sources
Organize your content into a logical structure, including an introduction, body, and conclusion
Write clear and concise explanations, providing examples and illustrations to support your points
Proofread your blog post or article carefully before publishing it on a platform of your choice

Create a map of your local area using QGIS

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This activity will help you apply your skills in spatial data analysis and mapping to a real-world problem.

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Find a dataset of your local area
Import the data into QGIS
Create a map of your local area

Connect with a Study Buddy

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Meet and discuss the course materials with a peer regularly to test your understanding of the concepts

Browse courses on R

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Find a classmate interested in collaborating
Schedule a regular meeting time
Review lecture notes and assignments together
Discuss challenging concepts and assist each other in understanding
Quiz each other on the material

Build an Interactive Web Map

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Create an interactive web map using the skills and techniques learned in the course to showcase your understanding of spatial data visualization

Browse courses on Web Mapping

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Gather spatial data and prepare it for use
Design the layout and functionality of the map
Implement the map using QGIS or R
Publish the map online
Share the map with others

Career center

Learners who complete [Intermediate] Spatial Data Analysis with R, QGIS & More will develop knowledge and skills that may be useful to these careers:

Geospatial Analyst

Geospatial Analysts use spatial data analysis and mapping to solve problems in a variety of fields, such as business, government, and academia. They use a variety of tools and techniques to analyze spatial data and develop solutions to problems. This course may be useful for Geospatial Analysts, as it provides a comprehensive overview of spatial data analysis and mapping techniques. The course also covers advanced topics such as interpolation, suitability analysis, and web mapping, which are all valuable skills for Geospatial Analysts.

See salaries and explore the career path for Geospatial Analyst

Spatial Data Scientist

Spatial Data Scientists use spatial data analysis and mapping to solve problems in a variety of fields, such as environmental science, public health, and business. They use statistical and computational methods to analyze spatial data and develop predictive models. This course may be useful for Spatial Data Scientists, as it provides a strong foundation in spatial data analysis and mapping. The course also covers advanced topics such as interpolation, suitability analysis, and web mapping, which are all valuable skills for Spatial Data Scientists.

See salaries and explore the career path for Spatial Data Scientist

Geographer

Geographers study the Earth's physical and human geography. They use spatial data analysis and mapping to understand the distribution and patterns of natural and human phenomena. This course may be useful for Geographers, as it provides a strong foundation in spatial data analysis and mapping. The course also covers advanced topics such as interpolation, suitability analysis, and web mapping, which are all valuable skills for Geographers.

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Spatial Statistician

Spatial Statisticians use statistical methods to analyze spatial data. They use a variety of techniques to identify patterns and trends in spatial data and develop models to predict future outcomes. This course may be useful for Spatial Statisticians, as it provides a solid foundation in spatial data analysis and mapping. The course also covers advanced topics such as interpolation, suitability analysis, and web mapping, which are all valuable skills for Spatial Statisticians.

See salaries and explore the career path for Spatial Statistician

GIS Analyst

GIS Analysts use geographic information systems (GIS) to analyze and visualize spatial data. They use GIS to create maps, charts, and other visualizations that can be used to support decision-making. This course may be useful for GIS Analysts, as it provides a comprehensive overview of spatial data analysis and mapping techniques. The course also covers advanced topics such as interpolation, suitability analysis, and web mapping, which are all valuable skills for GIS Analysts.

See salaries and explore the career path for GIS Analyst

Cartographer

Cartographers create maps and other visuals that communicate geographic information. They use a variety of tools and techniques to produce maps that are both accurate and visually appealing. This course may be useful for Cartographers, as it provides a solid foundation in spatial data analysis and mapping. The course also covers advanced topics such as interpolation, suitability analysis, and web mapping, which are all valuable skills for Cartographers.

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Remote Sensing Analyst

Remote Sensing Analysts use satellite imagery and other remotely sensed data to analyze the Earth's surface. They use this data to identify and map features such as land cover, land use, and natural resources. This course may be useful for Remote Sensing Analysts, as it provides a solid foundation in spatial data analysis and mapping. The course also covers advanced topics such as interpolation, suitability analysis, and web mapping, which are all valuable skills for Remote Sensing Analysts.

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Urban Planner

Urban Planners use spatial data analysis and mapping to plan and design urban areas. They work with stakeholders to identify needs and develop plans that are both feasible and sustainable. This course may be useful for Urban Planners, as it provides a comprehensive overview of spatial data analysis and mapping techniques. The course also covers advanced topics such as interpolation, suitability analysis, and web mapping, which are all valuable skills for Urban Planners.

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Planner

Planners use spatial data analysis and mapping to develop plans for the future development of communities and regions. They work with stakeholders to identify needs and develop plans that are both feasible and sustainable. This course may be useful for Planners, as it provides a comprehensive overview of spatial data analysis and mapping techniques. The course also covers advanced topics such as interpolation, suitability analysis, and web mapping, which are all valuable skills for Planners.

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Transportation Planner

Transportation Planners use spatial data analysis and mapping to plan and design transportation systems. They work with stakeholders to identify needs and develop plans that are both feasible and sustainable. This course may be useful for Transportation Planners, as it provides a comprehensive overview of spatial data analysis and mapping techniques. The course also covers advanced topics such as interpolation, suitability analysis, and web mapping, which are all valuable skills for Transportation Planners.

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Water Resources Manager

Water Resources Managers are responsible for managing water resources, such as rivers, lakes, and aquifers. They use spatial data analysis and mapping to assess the status of water resources, develop management plans, and communicate water resource information to stakeholders. This course may be useful for Water Resources Managers, as it provides a solid foundation in spatial data analysis and mapping. The course also covers advanced topics such as interpolation, suitability analysis, and web mapping, which are all valuable skills for Water Resources Managers.

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Natural Resource Manager

Natural Resource Managers are responsible for managing natural resources, such as forests, water, and wildlife. They use spatial data analysis and mapping to assess the status of natural resources, develop management plans, and communicate natural resource information to stakeholders. This course may be useful for Natural Resource Managers, as it provides a solid foundation in spatial data analysis and mapping. The course also covers advanced topics such as interpolation, suitability analysis, and web mapping, which are all valuable skills for Natural Resource Managers.

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Wildlife Biologist

Wildlife Biologists study the distribution and abundance of wildlife. They use spatial data analysis and mapping to identify and map wildlife habitats, assess the impact of human activities on wildlife, and develop conservation plans. This course may be useful for Wildlife Biologists, as it provides a solid foundation in spatial data analysis and mapping. The course also covers advanced topics such as interpolation, suitability analysis, and web mapping, which are all valuable skills for Wildlife Biologists.

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Surveyor

Surveyors measure and map the Earth's surface. They use a variety of tools and techniques to collect data about the shape and size of the Earth. This course may be useful for Surveyors, as it provides a solid foundation in spatial data analysis and mapping. The course also covers advanced topics such as interpolation, suitability analysis, and web mapping, which are all valuable skills for Surveyors.

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Environmental Consultant

Environmental Consultants are professionals who provide advice and guidance to organizations on environmental issues. They help organizations to comply with environmental regulations, reduce their environmental impact, and develop sustainable practices. This course may be useful for Environmental Consultants, as it provides a solid foundation in spatial data analysis and mapping. This knowledge can be used to assess the environmental impact of projects, develop remediation plans, and communicate environmental information to stakeholders.

See salaries and explore the career path for Environmental Consultant