ISSS624: Applied Geospatial Analytics

Welcome! In this website, I will be sharing my learning journey on applied geospatial analytics.

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Hands-On Exercises

Hands-on Exercise 1A: Geospatial Data Wrangling with R

In this hands-on exercise, I will be sharing how to import and wrangle geospatial data using appropriate R packages.

Hands-on Exercise 1B: Choropleth Mapping with R

In this hands-on exercise, I will be sharing how to plot functional and truthful choropleth maps using an R package tmap.

Hands-on Exercise 2A: Spatial Weights and Applications

In this exercise, we will learn how to compute spatial weights using R.

Hands-on Exercise 2B: Global and Local Measures of Spatial Autocorrelations

In this hands-on exercise, we will learn how to compute Global and Local Measure of Spatial Autocorrelation (GLSA) using the spdep package.

Hands-on Exercise 3: Processing and Visualising Flow Data

In this hands-on exercise, we will learn how to build an origin/destination (OD) matrix using Passenger Volume by Origin Destination Bus Stops data…

In-Class Exercises

In-Class Exercise 1: My First Date with Geospatial Data Analytics

For this task, we are required to prepare a choropleth map showing the distribution of passenger trips across the planning sub-zones.

In-Class Exercise 2A: Spatial Weights

For this task, we will be learning how to derive spatial weights using the sfdep package.

In-Class Exercise 2B: Global and Local Spatial Autocorrelations

For this task, we will be learning how to compute global and local spatial autocorrelations using the sfdep package.

In-Class Exercise 2C: Emerging Hot Spot Analysis

For this task , we will be learning how to perform Emerging Hot Spot Analysis (EHSA) using the sfdep package.

In-class Exercise 3: Calibrating Spatial Interaction Models

In-class Exercise 4: Geocoding and calibrating spatial interaction models

In this exercise, we will…

In-class Exercise 5

Use the following code chunk to install the latest version of spflow (instead from CRAN’s R library)

Take-Home Exercises

Take-Home Exercise 1: Geospatial Analytics for Public Good

As city-wide urban infrastructures such as buses, taxis, public utilities and roads become digital, data can be collected and used as a framework for tracking movement…

Take-Home Exercise 2: Applied Spatial Interaction Models

What are the driving forces behind urban dwellers to weak up early in morning to commute from their home locations to their work places? What are…