12 undergraduate courses in the 2026–27 Undergraduate Calendar.
Focus is on the issues and foundations of modern digital cartography. Topics covered include geographic coordinate systems, map projections, mapping quantitative data, developing online maps, and the impact of maps on society. Students will learn computer techniques to produce effective maps based on established principles of cartographic design.
A specialized introduction to fundamental concepts and emerging trends in geomatics and geospatial data science. Overview of the geospatial industry, including application in government, research, and private sector. Students are introduced to cross-discipline tools and techniques for accessing, visualizing, and analyzing geospatial data.
Students will gain knowledge about the requirements and constraints affecting recreational, commercial and research RPAS (Unmanned Aerial Vehicles [UAV], Unmanned Aircraft Systems [UAS]) flights for geomatics applications. Theory and conceptual factors affecting flight, remote sensing, and spatial analysis with very-high resolution data will be discussed. Students will gain knowledge about how to navigate regulatory requirements. They will learn how to link their science and research objectives with geomatics skills to mitigate risk and obtain regulatory approval for legal RPAS flights. Assignments provide a range of experiences to students that may include: applied aspects of flight campaign approval, setup, management; flight training; and integrating imagery with geographic information systems.
Remote sensing of the Earth's systems (atmosphere, land, and oceans) is introduced. The course covers the principles, physics, sensor technology, processing, and applications of remote sensing in the electromagnetic spectrum.
Introduction to the fundamental concepts and use of Geographic Information Systems (GIS). Students learn about the nature of geographic information and how to store, manipulate and analyze spatial data in a range of application areas. Students will learn underlying theory in lectures and gain a working knowledge of GIS software in lab sessions.
The course focuses on geospatial data acquisition and management. It provides foundational concepts related to primary data acquisition (e.g., survey data, Earth observation, geoweb), geodata cleaning, and preparation for analysis ready data. The course develops concepts of spatial database design and interrogation for geospatial analysis, demonstrating the technical requirements and processes from data collection to publication.
Students taking this course gain experience using spatial statistics to analyze spatial data and describe patterns or understand the relationship among spatial features and their attributes. Techniques related to sampling point pattern analysis, cluster detection, geostatistics, and landscape metrics, among others, will be discussed.
Advanced image processing techniques of digital remote sensing measurements (e.g. radar systems, optical and infrared systems) from ground, aircraft and satellite instrument systems. Techniques are applied to the study of physical and human environments.
Students learn theoretical and operational approaches to advanced spatial analysis using geographical information systems. Emphasis is placed on the use of automation procedures using models and programming to address a variety of topics that may include but are not limited to digital terrain modelling, suitability analysis, network analysis, and cell-based models. The domain of spatial problems explored may vary by instructor.
An in-depth study of current machine learning methods and their applications in geospatial science, with a focus on remote sensing and geographical information analysis. The differences between traditional spatial statistical analysis and modelling with artificial intelligence (AI) approaches will be emphasized and their applicability to spatial AI.
Digital image analysis for resource mapping and evaluation using remote sensing data. Topics range from initial data selection to final map production and assessment. Using commercial image analysis software, students will analyse data for a selected area and produce a portfolio of results. In addition, they will undertake a literature review on a selected topic and present highlights of the review at an end-of-term mini-conference.
The development, implementation, and presentation of a response to a set of GIS related project requirements is the focus of this course. Students work in small teams to enhance and develop their abilities to work with GIS and related spatial technologies and analytical methods in an advanced project setting. The nature of the project requirements and themes varies with faculty and student strengths and interests. Projects may emphasize development of software applications, use of programming, or advanced GIS analysis methods, and draw from theme areas such as environment studies and management, human and physical geography, or planning.