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
| Date | Lecture | Tutorial | Lab |
| September | |||
| 6 – 8 | No Lecture | GIS Data files (8 & 11) | No Lab |
| 11 – 15 | GIS Data | Text data processing (15 & 18) | Introduction to QGIS |
| 18 – 22 | Data Collection | Map Display (22 & 25) | Creating Data |
| 25 – 29 | Coordinate Systems | Creating Data | |
| October | |||
| 2 – 6 | Spatial Analysis | Map projections (2 & 6) | Vector Overlays |
| 9 – 13 | Spatial Analysis | Vector Analysis (13 & 16) | Thanksgiving |
| 16 – 20 | Midterm Exam (17th) | Raster Analysis (20 & 23) | Exploring Raster Data |
| 23 – 27 | Census Data | Attribute Management (27 & 30) | Working with Joins |
| November | |||
| 30 Oct – 3 Nov | Quantitative Methods | Descriptive Statistics (3 & 6) | Census Data |
| 6 – 10 | Geocoding | Geocoding (10 & 13) | Geocoding |
| 13-17 | Precision and Accuracy | Visualization (17 & 20) | Projects |
| 20-24 | Data Quality | Tutorial Review (24 & 27) | Projects |
| December | |||
| 27 Nov – 1 Dec | Course Review | Student Projects Due | |
| 4 – 8 | Final Exam (5th) | ||
Project Proposal
Final Project Outline
Below is the grading scheme for the course this year
COURSE GRADING – 2023
| Lab Assignments | 35% | Due weekly unless otherwise stated |
| Lecture Midterm | 15% | October 17 |
| Tutorial Exercises | 10% | Due weekly unless otherwise stated |
| Student Project | 20% | December 1 |
| Final Exam | 20% | 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