ttnsy / rgeo-intro

Coursebook for Algoritma DSS: Geospatial Analysis in R.

Building Interactive Map for Geospatial Analysis in R

Overview

The following coursebook is produced for Algoritma's DSS Building Interactive Map for Geospatial Analysis in R workshop. The 4-days online workshop is intended for participants new to the world of spatial analysis and / or programming. No prior programming knowledge is assumed.

The primary objective of this course is to provide a participant a comprehensive introduction about tools and software for visualizing a geospatial data using the popular open-source tools: R

Modules

• Part 1. Brief Introduction to R:

  • Tools Introduction
    • R and R Studio
    • Open source packages
    • Using R Markdown
    • R Programming Basics
  • Data Wrangling with R's tidyverse
    • Working with tabular data in R: Tips and Techniques
    • Data Wrangling and Aggregation
    • Introduction to visualization with ggplot2

• Part 2. Geospatial Analysis in R

  • Building Indonesia Static Map
    • Retrieving Indonesia spatial vector from an open source provider
    • Using sf for R's spatial environment
    • Grammar of Graphics for geospatial data using ggplot2
    • Enhancing map plots for richer visualization
  • Creating Interactive Map
    • Using leaflet - a JavaScript API for creating interactive maps
    • Adding markers and colors in leaflet
    • Building various geospatial analysis graphics: Choropleth, Heatmap, etc.
  • Publishing your visualization
    • Create an awesome and easy-to-build dashboard using flexdashboard package
    • Present your geospatial analysis for various industries business solution

• Additional: Demo for R'ssp package

R packages

Following packages are used within the material:

packages <- c("rgdal","sf","tidyverse","glue", "plotly", "maps","leaflet","leaflet.extras", "tmap", "flexdashboard","DT")

install.packages(packages)

References

• Kristin Stock, Hans Guesgen, in Automating Open Source Intelligence, 2016
• Edzer Pebesma, Daniel Nüst, and Roger Bivand, “The R Software Environment in Reproducible Geoscientific Research,” Eos 93 (2012): 163–164.
• Edzer Pebesma, Roger Bivand, Spatial Data Science
• Robin Lovelace, Jakub Nowosad, Jannes Muenchow, "Geocomputation with R"
• Leaflet for R
• Wilkinson, Leland, and Graham Wills. 2005. The Grammar of Graphics. Springer Science+ Business Media.
• Paula Moraga, Geospatial Health Data: Modeling and Visualization with R-INLA and Shiny, 2019
• DT: An R interface to the DataTables library