Syllabus Fall 2024

Instructor:Anthony Jjumbaanthony.jjumba@unbc.ca
Lectures:Monday and Wednesday: 10:00 – 11:20 
Labs:Tuesday: 11:30 – 14:30   

Course Description

This lab-based course introduces advanced GIS concepts and technical skills related high accuracy data collection, database management systems, and the Geoweb. In addition, the students will explore advanced methods of analysing geographic data.

Leaning Objectives:

The students will learn about the various methods of collecting and analysing geographic data. Drawing on various statistical methods, they will also gain insight into the nature of the spatial patterns existing in geographic phenomena. They will also develop skills for working with spatial databases; web-based tools for storing retrieval and display of geographic data; and ArcGIS and RStudio software.

Course Schedule:

LessonLecture TopicLabs
September
2 – 6Geographic Data and Statistical Techniques  No Labs
9 – 13Geographic Data and Statistical Techniques  Introduction to R
16 – 20Sampling Methods || Landscape Structure and MetricsLab 1: Basic Analytics in R
23 – 27Exploratory Data Analysis  Lab 2: Spatial Data in R
October
30 Sep – 4Pattern AnalysisLab 3: PCA Using RStudio
7 – 11Spatial AutocorrelationLab 4: K-Means Clustering
14 – 18Regression Analysis
21 – 25Midterm (21 Oct)Lab 5: Moran’s I, Local Moran’s I
28 – 1 NovGeowebLab 6: Bivariate Analysis
November
4 – 8Database Management SystemsLab 7: Working with Leaflet
11 – 15Database Management SystemsLab 8: PostgreSQL and PostGIS
18 – 22Simulation ModellingLab 9 (NetLogo GEOG 613) 
25 – 29Course ReviewProject Assignment
December
2 – 6Final Exam (Dec 2nd) || Project Submission (Dec 3rd)
  

Literature Review Instructions (Student Paper)

GEOG-413 Grading Scheme

Lab Assignments (8)35%Due Weekly
Mid-term15%
Student Projects20%
Student Paper10% 
Final Exam20%

GEOG-613 Grading Scheme

Lab Assignments (9)40%Due Weekly
Mid-term10%
Student Projects20%
Student Paper15% 
Final Exam15%