Syllabus - NR 218 - Introduction to GIS - Spring 2026, Section 03
Class Details
Room 180-230 (Baker)
Monday: 5:10 - 9:00
Wednesday: 6:10 - 9:00
Instructor Details
Michael Huggins
✉ mthuggin@calpoly.edu
Office Hours: Mondays 2:00 - 4:00
Building 72-107 (Plant Conservatory)
TA: Jillian Ong
Learning Goals
- How to formulate and answer problems using spatial data
- How to create quality maps and graphics
- Apply skills in remote sensing, GIS, and data science to solve a problem
- Understand basic principles of GIS
Labs
Not every lab requires you turn in your results. The calendar lists due dates for the labs that need to be turned in.
Quizzes
There will be five quizzes. For each quiz, if you get 75% of the poionts, you get full credit. Beyond 75% correct will allow you to earn up to 25% of the quiz value ni extra credit.
Assignment Weight
| Assignment | Percentage of Grade | Description |
|---|---|---|
| Lab exercises | 50 | 9 have assignments that need to be turned in |
| Quizzes | 10 | Quizzes can happen any time! |
| Project | 20 | Will use skills learned throughout the quarter |
| Final Exam | 20 | Oral exam, in which you will explain what you did in project 4 |
Grading
A: ≥ 90%
B: ≥ 80%
C: ≥ 70%
D: ≥ 60%
F: < 60%
Note: Grading is not curved.
Assignment Submission Policy
Assignments will be submitted on Canvas. Late assignments will be penalized by 5% for every day they are late.
Academic Integrity
All students should be familiar with and adhere to the university’s academic integrity policy, which can be found here: https://osrr.calpoly.edu/academic-integrity
Use of AI
AI generated text may not be used for any writing.
Students can seek AI assistance for project work, but it is important to consider that AI will make you stupid (See this study for example) and waste your time!
- Depending on AI prevents development of critical thinking, writing, and problem-solving skills
- AI will often lead you down a terrible, deep rabbit hole of confusion
- Getting quick answers without working through problems will leave gaps in foundational knowledge needed for advanced coursework
- The struggle of working through difficult concepts is often where the most valuable learning occurs
- AI uses heaps of electricity
That is not to say LLMs are never useful or appropriate to use, but you need to know their limitations. I suggest reading this critical AI literacy guide from Rutgers University.
Textbook
You will read excerpts from Essentials of Geographic Information Systems during this course. A free and online version of the textbook can be found here.
Tutorials
We will refer to a number of tutorial videos which describe QGIS processing. These will come primarily from two sources:
Ujaval Gandhi’s QGIS Tutorials and Tips
QGIS Training Manual
There are many other helpful sources of information on GIS Software, here area couple:
Spatial Thoughts introduction-to-qgis.html
A Gentle Introduction to GIS gentle_gis_introduction/index.html
Spring Term Calendar 2026
| Date | Week | Lecture | Lab | Reading | Due Dates |
|---|---|---|---|---|---|
| March 30 | 1 | Introduction, Computers | Lab 1 | ch. 1 and 2 as well as this page about computers | |
| April 1 | 1 | Basic GIS Concepts, Scale, Coordinate systems, and Map Projections | Lab 2 | Lab 1 | |
| April 6 | 2 | Spatial Data Models and File Formats | Lab 3 | ch. 3 and 4 | |
| April 8 | 2 | Lab 4 | |||
| April 13 | 3 | Review: Coordinate Systems, Map Projections, Datums; Reprojection; GeoProcessing and Vector Operations | Lab 5 | ch. 5 and 6 | Lab 2 |
| April 15 | 3 | GeoProcessing and Vector Operations | Lab 6 | ||
| April 20 | 4 | Data Creation, Editing, Topology Basics | Lab 7 | ch. 7 and 8 | |
| April 22 | 4 | Rasters and Elevation Data | Lab 8 | ||
| April 27 | 5 | Raster Analysis: Map Algebra, Resampling, Reprojecting Rasters | Lab 9 | ch. 9 and 10 | Lab 7 |
| April 29 | 5 | Remote Sensing and Spectral Indices | Lab 10 | Lab 8 | |
| May 4 | 6 | Segmentation | Lab 11 | ||
| May 6 | 6 | Raster \(\times\) Vector Operations, Zonal Statistics, Point Sampling | Lab 12 | Lab 10 | |
| May 11 | 7 | Lab 13 | Lab 11 | ||
| May 13 | 7 | Workflow Design and Geoprocessing Models | Lab 14 | Lab 12 | |
| May 18 | 8 | Georeferencing | Lab 15 | ||
| May 20 | 8 | Advanced Topics (tbd) | Lab 16 | Lab 14 | |
| May 25 | 9 | NO CLASS (Memorial Day) | |||
| May 27 | 9 | Modern Map Making | Lab 17 | Lab 15 | |
| May 31 (Sunday) | 10 | Project | |||
| June 1 | 10 | Oral Exams | Lab 17 | ||
| June 3 | 10 | Oral Exams | Lab 19 |