Spring 2022 - GEOG 356 D100

3D GIScience (4)

Class Number: 4758

Delivery Method: In Person


  • Course Times + Location:

    Jan 10 – Apr 11, 2022: Mon, 10:30 a.m.–12:20 p.m.

  • Instructor:

    Nicholas Hedley
    1 778 782-4515
    Office: RCB 7229
  • Prerequisites:

    GEOG 255.



Introduction to 3D spatial data, 3D analysis, and 3D visualization for spatial problems. Students will gain skills in 3D aspects of GIScience concepts; data generation and use; analysis and simulation; visualization and its use for interpretation and communication.


COURSE OVERVIEW                                                                                                                                      

Calendar Description

Introduction to 3D spatial data, 3D analysis, and 3D visualization for spatial problems. Students will gain skills in 3D aspects of GIScience concepts; data generation and use; analysis and simulation; visualization and its use for interpretation and communication.

Course Description       

Emerging technologies are changing the way we generate digital representations of geographic spaces.

Modern methods of 3D data acquisition (i.e. 3D laser scanning and photogrammetry) have become industry standards, delivering powerful 3D characterizations of geographic space and revealing new opportunities to create 3D analytical geovisualizations.  3D spatial data proficiency is going to become a critical skill as industry and science adopt game engines, virtual environments and mixed reality interfaces as new spatial interface standards.

This course trains students how to design and build analytical 3D geovisualizations for applied geographic problems, using a rich and engaging repertoire of contemporary 3D data, analysis, visualization and interfaces. This course prepares students for an emerging new world of geovisual analysis and communication in GIScience. In fact many GEOG 356 students have been hired by companies in the 3D geospatial information and interface sector already!

In GEOG 356, we will explore a range of contemporary and emerging 3D visualization technologies for geovisualization and critically review their properties and potential in geospatial applications. You will learn how to capture geographic phenomena in 3D using a range of methods, including: 3D scanning; Structure-from-Motion (SfM); LiDAR and UAVs (drones). We will explore the workflows needed to build 3D GIS and 3D geographic virtual environments from these data types. I will show you how to design and build a variety of 3D geovisualizations using a range of analysis and simulation methods. You will get to experience 3D data visualizations (including building your own). We will consider all of these experiences through the perspectives of geovisualization, GIScience, spatial cognition, and spatial interface research – at a time when 3D surveying and emerging virtual and mixed reality geovisual platforms are in need of 3D GIScience specialists.

Newly reworked for 2022, GEOG 356 provides students of many backgrounds with an introduction to the rapidly emerging fields of 3D geographic visualization and 3D GIScience, gaining first-hand experience with 3D data and its use, 3D geovisual analysis and simulation. Students will be introduced to thinking about spatial problems and phenomena in three dimensions. We will explore the capabilities of 3D data capture, 3D representation, 3D spatial analysis and simulation, interaction and interpretation of 3D visualizations. We will also be using some virtual reality and mixed reality visualization systems!

We will explore questions such as: How do we design and perform 3D spatial data surveys using laser scanners, drones, and underwater sensors? What types of data do they produce? What can we do with these data? What sorts of analysis, and simulations are possible? What new forms of 3D geovisualization can we implement? How can 3D data, representation, visualization and analysis be applied to challenges in fields that span the whole spectrum of spatial phenomena? How are these emerging technologies and methods defining future 3D GIScience? I will illustrate many of these capabilities and questions, using direct examples from my own active research, and from other sources. Students are encouraged to add their own experiences and ideas to the mix!

Students will be guided through 3D geovisual GIScience skill-building activities – focused through applied problem-solving contexts tuned to students who take this course. These may include: environmental change; social science; human dynamics; urban development; archaeology and cultural heritage; Earth science; natural hazards; using data collected by rovers on Mars to build analytical simulations; and 3D surveying 2000-yr-old sites in Egypt! 

Objectives of Course Content

This class is designed as an accessible, experiential course for a wide range of students – organized in a modular format. Lectures and labs will be used flexibly to introduce and demonstrate 3D concepts, data, methods, visual analysis and interface technologies. Assignments have been newly designed to be achievable in students’ busy schedules, while delivering training and experience with 3D data, visualization and interaction.

In week 1, students will be polled, in order to tune content and activities to their interests and objectives.

Students will learn how to design and produce 3D visualizations for presentation and communication of spatial phenomena to academic and public audiences. Students will learn how to generate, process and use 3D data from laser scanning, UAVs (drones) and other platforms. Students will learn how to generate 3D representations of a variety of spatial phenomena, using a range of 3D data formats. Students will learn how to perform 3D spatial analyses and simulations.

Students in this course will be supported by assigned readings, discussion, position papers, hands-on exercises, demonstrations of 3D methods and interface technologies, and applied examples.


A weekly lecture session will introduce concepts, technology, methods, demonstrations. We will also use this time for student show-and-tell discussions of technology and applications; a weekly lab presentation at the start of each training module (live/video) - for hands-on training in methods, labs and course assignments, and demonstrations.; weekly group Q&A with a TA.  Lectures and labs will be used flexibly to introduce and demonstrate 3D concepts, data, methods, visual analysis and interface technologies.

COURSE COMPONENTS (see next page for more detail)                                                                               

Weekly live lecture: period (or video lecture episode) discussion/Q&A

Weekly Lab methods instructional presentations (live and/or video)

Weekly Lab Q&A with TA

Lab assignments

Online mini quizzes (as part of assignment grade)

Online course exam (see below)

Final project assignment (demonstrate your acquired skills with an applied case study)


Lectures as weekly Episodes

In order to maximize the ability of all students to connect with and experience lecture material as a narrative from me, my lecture materials will be made available as a mixture of weekly PDF notes and video ‘episodes’. These episodes will allow students to benefit from a narrative of 3D data, 3D GIScience and 3D Geovisualization ideas, concepts, methods and perspective. In each episode, 3D data, 3D GIScience, and 3D geovisualization concepts, methods will be introduced, explained, demonstrated, discussed and sometimes critiqued. You will also be introduced to applied 3D data/GIScience/3D geovisualization workflows, through presentation of applied projects, including discussion of project management skills.

Producing lectures as online videos, means that they will be accessible/downloadable from our online class platform (Canvas), allowing asynchronous viewing/ playback/pausing/viewing/review control for everyone, to suit each student’s personal schedule.

Note that we are also going to try some very innovative, first-of-their-kind ways to experience/deliver some of the content on 3D data, 3D GIScience and 3D geovisualization!

Weekly live discussion in Unpack the Episode

It is also essential, however, that you (my students!) can benefit from live discussion and clarification of lecture topics and questions. Therefore, we will also use some of our time to openly discuss topics/technology/issue. These meetings will be held during GEOG 356’s scheduled ‘lecture time’. Any video meetings will use Zoom.


Once a week you will have assigned lab training activities, where you will work through a sequence of exercises that introduce you to: 3D data generation and manipulation; 3D data processing and analysis; 3D simulation; 3D geovisual analysis; 3D GIS software use. Labs are intended as a technical apprenticeship in a repertoire of 3D data, analysis, simulation and visualization methods, running parallel to lectures, and informed by the ideas, concepts and perspectives discussed in lecture. Labs will begin in Week 2. In Week 1, we will poll students to check on resources (including personal/off-campus computing access) to participate in and complete labs, so that we can identify and put in place a plan for maximum student experience, and success.

Each topic/training module in lab will be kicked off with a presentation/video introduction by your TA. (This video will also serve as an instructional reference and be made accessible on Canvas). Accompanying the video, will be a set of digital notes providing instructions to follow for each training module. Some guidelines will be very step-by-step, while others will intentionally challenge you to figure out solutions to problems. All meaningful training and experience!

Each week, your TA will hold Q&A in support of lab work, lab section-by-section. Note that this will be conducted in the most efficient way possible – preferably as specific topics/questions presented to groups of students requesting support.

We reserve the right to modify the format of these instructional materials/resources if we perceive there to be more effective ways to maximize student experiences, and TA time efficiency.

Computing resources in support of GEOG 356 include: Geography computing labs (which have a range of software installed); home install of some software for you to use while working on assignments, etc; remote access to Geography computing labs using VPN.

We will tune the lab/training to students’ computing/access context, using primarily open-source software and cloud processing as much as possible. We will discuss each student’s computing situation with them in Week 1, to determine best course of action for maximum positive experience in this class.

Quizzes and exams will both be administered remotely, through Canvas. The schedule will be synchronous (i.e. typically during the respective scheduled class timeslot or within an assignment cycle).

FINAL PROJECT                                                                                                                                             

A key component of this course will be the production of a small portfolio-quality applied 3D GIScience/3D Geoviz project. The final project enables you to integrate and demonstrate the 3D data/analysis/visualization skills/methods/technology (and GIScience thinking) you have learned, focused through one of a collection of applied thematic topics (designed/tuned to the interests of students in the course). Proactive planning and time management are important to produce a great project. Deliverables will be submitted digitally.


Technological access/needs:
We will poll students in Week 1 to make sure everyone has a feasible arrangement with which to successfully access/perform lab work.

Student conduct and integrity:
We expect all students to hold themselves to the highest standards of scholarly practice and integrity. Your work should be completed by YOU and nobody else. We reserve the right to use plagiarism detection software. Do yourself a favor - thrive in this course through your own effort, a positive attitude, and with maximum integrity.

Recommended familiarity
For maximum benefit, students should be familiar and comfortable with the Windows desktop environment especially using files and folders in Windows and navigating to folders and files from within specific applications; we expect students to have a working knowledge of either ArcGIS or QGIS. You will be using a range of tools, converting data and moving them between different software packages.

Spring 2022 courses will be delivered in person based on information available at the time of publishing the outline; please note the delivery mode is subject to change following Provincial Health Officer (PHO) and/or SFU recommendations and orders.


Students completing this course, students will be:

  1. a) knowledgeable about how emerging GIS, GIScience, data acquisition, processing and geovisualization technologies raise new opportunities for representing and visualizing geographic spaces;
  2. b) experienced in the planning, design, field strategy and implications of 3D spatial data capture, using 3D laser scanning (LiDAR); UAVs (Drones); Structure-from-Motion (SfM) photogrammetry; structured light and other 3D capture technologies;
  3. c) experienced in the acquisition, processing, export and use of various interoperable 3D data assets;
  4. d) experienced in a range of 3D geovisualization technologies (incl. 3D GIS; point cloud software; photogrammetric software; 3D game engines repurposed to spatial analysis and visualization);
  5. e) trained in how to design and implement 3D geovisualizations of their own;
  6. f) able to combine 2D/3D/4D spatial analysis with interactive 3D visualization systems;
  7. g) trained in multi-platform workflow to develop analytical 3D geovisualizations;
  8. h) trained in spatial project design and management skills;
  9. i) able to integrate 3D spatial data and geovisualization methods and thinking into their future work.


  • Lab assignments (training in a repertoire of 3D data/processing/analysis/simulation/vis methods) and quizzes 50%
  • An applied ‘3D GIScience/3D Geoviz mini project’ assignment to demonstrate your acquired skills 25%
  • A cumulative course exam (locking in the ideas, concepts, methods, implications of your 3D Science training) 25%


A+ 97 or higher
A 91-96
A- 85-90
B+ 80-84
B 75-79
B- 70-74
C+ 65-69
C 60-64
C- 55-59
D 50-54
F 0-49



There is no required textbook for this course.

PDF lecture notes, curated reading assignments and support materials will be provided throughout the semester.

Registrar Notes:


SFU’s Academic Integrity web site http://www.sfu.ca/students/academicintegrity.html is filled with information on what is meant by academic dishonesty, where you can find resources to help with your studies and the consequences of cheating.  Check out the site for more information and videos that help explain the issues in plain English.

Each student is responsible for his or her conduct as it affects the University community.  Academic dishonesty, in whatever form, is ultimately destructive of the values of the University. Furthermore, it is unfair and discouraging to the majority of students who pursue their studies honestly. Scholarly integrity is required of all members of the University. http://www.sfu.ca/policies/gazette/student/s10-01.html


Teaching at SFU in spring 2022 will involve primarily in-person instruction, with safety plans in place.  Some courses will still be offered through remote methods, and if so, this will be clearly identified in the schedule of classes.  You will also know at enrollment whether remote course components will be “live” (synchronous) or at your own pace (asynchronous).

Enrolling in a course acknowledges that you are able to attend in whatever format is required.  You should not enroll in a course that is in-person if you are not able to return to campus, and should be aware that remote study may entail different modes of learning, interaction with your instructor, and ways of getting feedback on your work than may be the case for in-person classes.

Students with hidden or visible disabilities who may need class or exam accommodations, including in the context of remote learning, are advised to register with the SFU Centre for Accessible Learning (caladmin@sfu.ca or 778-782-3112) as early as possible in order to prepare for the spring 2022 term.