Draft Syllabus
MON, WED 2-3:15, Student Success Center
Spring 2025, 3 Credit Hours
Summary
Introduction to computing with spatial datasets, including lessons on geographic information fundamentals, projections, spatial operations, raster and imagery data analysis, and cartographic design principles that are used to digitally model social and environmental processes.
Instructor and Teaching Assistants
Dr. Clio Andris, Email: clio@gatech.edu.
TA: Andrew Dowdy
Possible Threads (Note, this is a special topics course and not officially approved under any threads!)
https://www.cc.gatech.edu/academics/threads/modeling-simulation
https://www.cc.gatech.edu/academics/threads/media
https://www.cc.gatech.edu/academics/threads/intelligence
There are no prerequisites for this course, although knowledge of Python is recommended. Students cannot get credit for this course and CP 4510 (Fundamentals of GIS). Students cannot get credit for this course and CP 6514 (Introduction to Geographic Information Systems). CP 4510 use the ArcGIS Software Suite (ArcPro), whereas this class focuses on scripting and open-source tools.
Introduction
The primary objective for this course is to expose computer science students to maps, data analysis and methods in Geographic Information Systems and Science (GIS). The course will help students learn the fundamentals of spatial data representation, formats, map projections, GIS operations and computing, cartography, and multi-criteria decision-making. Students are welcome to use a technology of their choice (such as Python), but labs will be primarily taught in the open source Quantum GIS (QGIS) computing environment.
This course teaches students how to make maps using geodata visualization strategies and cartographic standards. It also teaches geoprocessing using the programming using Python in QGIS. Students will learn how to write scripts and amend scripts for reading in, processing, and analyzing spatial datasets.
Course Objectives
- Learn about how spatial data is collected, stored, retrieved and used
- Describe the characteristics of different map projections and transformations
- Explain data and table structures, including levels of measurements, normalization, and table joins
- Retrieve, inspect and use GIS data sources such as hydrological, demographic, land use, elevation, roads, health statistics, etc.
- Use spatial joins to combine spatial data layers
- Analyze vector data using spatial interpolation, error, and estimation techniques
- Orthorectify imagery and graphics into a GISystem using control points
- Detect features in aerial imagery
- Analyze terrain of a digital elevation model including calculating slope, aspect and viewsheds
- Describe and use principles of cartography, geovisualization and interaction with data
Materials: Laptop computer is recommended. Students will be required to download QGIS.
Texts: Bolstad, P. and Mason, S. (2023) GIS Fundamentals. This book/online resource can be purchased online at https://www.gisfundamentals.org/. Reading the book will help you prepare for lectures and exams.
Course Evaluation
Students are expected to attend all lectures, read readings, and complete all assignments. There will be no official final exam. Late submissions will be graded down by 10% for each day of delay past the due time. All assignments should be handed in on Canvas. We follow the Georgia Tech grading scale.
| Content | Number of Assignments | Total Points |
| GIS labs | 10 (mostly 6 pts each) | 60 |
| GIS project | 1 | 10 |
| Exams | 2 (15% and 15%) | 30 |
| We also have a few bonus assignments that are given in class. | ||
Course Format + Infrastructure
This is an in-person class. Lectures will be in person and will include hands-on lab times to give students more experience with geographic information systems and science. All lectures, readings, assignments are to be accessed through Canvas. Canvas is for general messaging, discussions, and file retrieval. Piazza is for students to help one another. Lectures will not be recorded, but we plan to record lab instruction and post the videos on Canvas under the Media Gallery soon after class.
Exams
Exams will be administered in person, and they are closed-book. Any accommodations through ODS will be granted, whether that is testing in the testing center, extra time, etc.
How to be Successful
Please engage in class. This means showing your fellow students that you are paying attention and that class time and instruction is important to you. Be present in the lectures and do the readings (Information about information visualization comes in sentence form!). While slides give key points and high-level topics discussed, much of the content of the course comes through the discussion, and other in-class activities. If you want to do well, attending class is important.
All official due dates will be the due dates posted on Canvas.
DRAFT CALENDAR (TO BE TRANSFERRED TO M-W SCHEDULE; IT IS T-TH RIGHT NOW)
| Week | Date | Topic | Reading (GIS Fundamentals Book) |
| 1 | Tu 1/7 | Introduction to Course, GIS | |
| 1 | Th 1/9 | Lab 0: Cartography & Introduction to QGIS | Introduction to Map Design (ESRI, 1996) |
| 2 | Tu 1/14 | Vector Data + Attributes | CH 1: Introduction |
| 2 | Th 1/16 | Lab 1: Thematic mapping | |
| 3 | Tu 1/21 | Projections + Transformations | CH 3: Geodesy, Datums, Map Projections and Coordinate Systems |
| 3 | Th 1/23 | Lab 2: Projecting data | |
| 4 | Tu 1/28 | Tables, Databases, Queries/SQL | CH 8: Attribute Data and Tables |
| 4 | Th 1/30 | Lab 3: GIS operations and analysis I | |
| 5 | Tu 2/4 | GIS Operations for Vector Data | CH 9: Basic Spatial Analysis |
| 5 | Th 2/6 | Lab 4:GIS operations and analysis II | |
| 6 | Tu 2/11 | Editing and Creating Data | CH 4: Maps, Data Entry, Editing, Output |
| 6 | Th 2/13 | Lab 5: Geocoding, creating data, editing | (spatial joins, clips, intersection, buffer) |
| 7 | Tu 2/18 | Exam Review | |
| 7 | Th 2/20 | Exam 1 | |
| 8 | Tu 2/25 | Raster Data + Imagery + Digitizing | CH 6: Aerial and Satellite Images |
| 8 | Th 2/27 | Lab 6: Orthorectification, digitizing + feature detection | |
| 9 | Tu 3/4 | Raster Algebra + Raster Operations | CH 10: Topics in Raster Analysis |
| 9 | Th 3/6 | Lab 7: Raster algebra | |
| 10 | Tu 3/11 | Spring Break | |
| 10 | Th 3/13 | Spring Break | |
| 11 | Tu 3/18 | Terrain Analysis | CH 11: Terrain Analysis |
| 11 | Th 3/20 | Lab 8: Terrain analysis | |
| 12 | Tu 3/25 | No In Person Class – AAG | |
| 12 | Th 3/27 | No In Person Class – AAG | |
| 13 | Tu 4/1 | Point Patterns/Encapsulation & Project Introduction | CH 12: Spatial Estimation: Interpolation, Predication, and Core Area Delineation |
| 13 | Th 4/3 | Spatial Statistics | |
| 14 | Tu 4/10 | Lab 9: Point Patterns/Encapsulation | |
| 14 | Th 4/12 | Exam Review | |
| 15 | Tu 4/17 | Exam 2 (not cumulative) | |
| 15 | Th 4/19 | Project Help & Data Search | GIS-T Body of Knowledge Cartography |
| 16 | Tu 4/24 | Project Help | |
| 16 | Th 4/26 | READING DAY: NO CLASS | Project due date to be announced. No final exam. |