Training Course on Web-based GIS and Mapping with R Shiny - R, Shiny

Module 1: Introduction to Web-based GIS with R and Shiny

Theory:

Overview of web GIS applications and interactive mapping.

Introduction to R Shiny architecture: server, UI, reactive programming.

Comparison with other web GIS frameworks (Leaflet, ArcGIS Online).

Applications: Online mapping for urban planning, environmental monitoring, and public dashboards.

Hands-on Exercise: Install R, RStudio, and Shiny; run a sample Shiny GIS app.

Case Study: Interactive flood risk dashboard for a city.

Module 2: Geospatial Data Handling in R

Theory:

Spatial data types: points, lines, polygons, raster.

Importing shapefiles, GeoJSON, KML, and raster data.

Coordinate Reference Systems (CRS) and projections.

Methods:

Using sf, sp, raster, and terra packages for spatial data manipulation.

Hands-on Exercise: Load and visualize shapefiles, raster layers, and census data in R.

Case Study: Preparing land-use and population layers for interactive mapping.

Module 3: Spatial Analysis in R for Web Mapping

Theory:

Overlay, buffering, spatial joins, and distance calculations.

Raster operations and extraction.

Multi-criteria spatial analysis in R.

Methods: Using sf, rgeos, raster, and spdep for analysis.

Hands-on Exercise: Conduct spatial queries and analyses on environmental datasets.

Case Study: Identify suitable locations for new public facilities using multi-criteria analysis.

Module 4: Introduction to Shiny UI and Server Concepts

Theory:

Reactive programming in Shiny.

UI layout options: fluidPage, navbarPage, sidebarLayout.

Connecting UI elements to server logic.

Hands-on Exercise: Build a basic Shiny app with input widgets and reactive outputs.

Case Study: Interactive population map responding to user-selected districts.

Module 5: Creating Interactive Maps with Shiny

Theory:

Using leaflet, tmap, and mapview packages for interactive mapping.

Adding popups, tooltips, legends, and layers control.

Integrating multiple map layers dynamically.

Hands-on Exercise: Create an interactive map showing urban infrastructure and environmental data.

Case Study: Flood monitoring map with real-time water level indicators.

Module 6: Dynamic Data Filtering and User Interaction

Theory:

Using inputs such as sliders, checkboxes, and dropdowns to filter data.

Reactive expressions and outputs for dynamic maps and tables.

Linking plots, tables, and maps in Shiny apps.

Hands-on Exercise: Create a map and table that update based on selected filters.

Case Study: Interactive dashboard showing pollution levels by neighborhood and time.

Module 7: Integrating Spatial Analytics into Shiny Apps

Theory:

Embedding spatial analysis outputs into Shiny.

Real-time computations using sf and raster.

Advanced visualizations with plotly and ggplot2.

Hands-on Exercise: Integrate distance and overlay analysis results into an interactive app.

Case Study: Identify emergency response zones dynamically in a city.

Module 8: Advanced Shiny App Features

Theory:

Custom widgets, dynamic UI generation, and modules.

Adding download buttons for data export.

Optimizing app performance for large datasets.

Hands-on Exercise: Build an advanced GIS dashboard with multiple interactive components.

Case Study: Real-time environmental monitoring app with downloadable datasets.

Module 9: Deploying and Sharing Shiny GIS Apps

Theory:

Deploying Shiny apps locally, on Shiny Server, or cloud platforms.

User authentication, permissions, and security considerations.

App maintenance and updates.

Hands-on Exercise: Deploy a Shiny GIS app to a local Shiny server or shinyapps.io.

Case Study: Public-facing dashboard for urban traffic monitoring.

Module 10: Capstone Project

Project Examples:

Urban infrastructure planning dashboard integrating population, roads, and public services.

Environmental monitoring Shiny app with interactive raster and vector layers.

Disaster response web GIS app showing hazard zones and affected areas.

Hands-on Exercise: Develop, deploy, and present a full web-based GIS Shiny application.

Presentation: Peer review, feedback, and best practices discussion.