Introduction to GIS

This lab-based course provides an introduction to the data management and analysis capabilities of Geographic Information Systems (GIS) and provides a foundation in GIS. Topics include geospatial data sources; attribute management; quantitative analysis; map projections and coordinate systems; and raster and vector analysis. This course combines data and common practices from natural resource management and social sciences.

There will be no Lecture or Labs in the first week, 6 – 8 September.

Syllabus

DateLectureTutorialLab
September
6 – 8No LectureGIS Data files (8 & 11)No Lab
11 – 15GIS DataText data processing (15 & 18)Introduction to QGIS
18 – 22Data CollectionMap Display (22 & 25)Creating Data
25 – 29Coordinate SystemsCreating Data
October
2 – 6Spatial AnalysisMap projections (2 & 6)Vector Overlays
9 – 13Spatial AnalysisVector Analysis (13 & 16)Thanksgiving
16 – 20Midterm Exam (17th)Raster Analysis (20 & 23)Exploring Raster Data
23 – 27Census DataAttribute Management (27 & 30)Working with Joins
November
30 Oct – 3 NovQuantitative MethodsDescriptive Statistics (3 & 6)Census Data
6 – 10GeocodingGeocoding (13 & 17)Geocoding
13-17Precision and AccuracyVisualization (20 & 24)Projects
20-24Data QualityTutorial Review (27 & 1 Dec)Projects
December
27 Nov – 1 DecCourse ReviewStudent Projects Due
4 – 8Final Exam (5th)

Project Proposal

Final Project Outline

Below is the grading scheme for the course this year

COURSE GRADING – 2023

Lab Assignments35%Due weekly unless otherwise stated
Lecture Midterm15%October 17
Tutorial Exercises10%Due weekly unless otherwise stated
Student Project20%December 1
Final Exam20%December 5

CONTACTS:

Anthony Jjumba (Lectures): jjumba@unbc.ca

Office Hours – Room 8-142
Tues: 11:30 – 12:30
Monday: 10:30 – 11:30

Ping Bai (SLI): ping.bai@unbc.ca Monday Lab

Guowei Li (TA): guwoei.li@unbc.ca Tuesday Lab

Aurora Padilla Martinez (TA): apadilla@unbc.ca Thursday Lab