About

• Responsible staff
• Contact hours
• Education methods
• Material used
• Marking
• Exams
• Questions related to the content of the course?
• Plagiarism, external help, and LLMs
• How to best follow this course
• Expected prior knowledge
• Course content
• Study goals

Responsible staff

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Contact hours

During the Q2:

• Wednesdays 8:45–10:30 (contact hours, demo, questions, discussions)
• Wednesday 13:45–15:30 (help with coding/assignments, with student assistant Ming-Chieh Hu)
• Fridays 8:45–10:30 (contact hours, demo, questions, discussions)

Education methods

This is a blended-learning course. The contact hours are there to explain topics that are more difficult, to give context to the lesson, to demonstrate software that are linked to the lesson, to tell funny facts about the lessons, to help with the assignments, to give feedback on the assignments.

The contact hours are not mandatory (except on 2025-12-01@08:45-09:30 when there is a quiz (10% of final mark)) but they certainly will help in understanding the concepts.

The “typical” lectures are replaced by videos and reading that you need to do individually at home before the contact hours.

Material used

You do not need to buy anything, all the material is freely available. We use the book Computational modelling of terrains (please ensure you use v2025.0!). You should download its PDF and print it (since you can bring it to both exams).

Marking

type	weight
final exam	50%
mid-term quiz	10%
2 individual assignments	20%
1 group assignment	20%

• a total of 57.5% or above is necessary to successfully pass the course
• there are 2 exams: one mid-term quiz and one final exam
• a minimum of 50% for the combined exams (quiz + final) is necessary (weighted-average of the two)
• there is one resit for the combined exams (thus one exam worth 60% during the resit period (Q3))
• there is one “retake” for the 3 assignments, but it is one individual project (made available during Q3)
• you can choose which of the resits you want to do:
  • (option 1) only the resit exam (60% of final mark);
  • (option 2) only the resit for the assignments (40% of final marks; individual task);
  • (option 3) both option 1 and option 2.
• if you still fail after the resits (<57.5% or <50% for exam part), then you have to redo the whole course the following year.

Exams

1. quiz (10%) on 2025-12-10@8:45–9:30
2. final exam (50%) on 2026-01-30@9:00-11:30

Both are open-book: you can bring any (paper) books and/or paper notes you want, but electronic devices are not allowed (except a simple calculator, which you need!).

All exams from previous years are available for download.

Questions related to the content of the course?

Please do not email me for questions, I want everyone to benefit from the answers provided, and I encourage students to also answer questions.

For all questions related to the content, please use discord (Geomatics server, #geo1015). If you prefer to ask a question with DM or email and I believe the question/answer can benefit others, I will copy-and-paste it to the general group (and remove your name).

Only use email for personal issues.

Plagiarism, external help, and LLMs

In short, you are welcome to use external help (eg a knowledgeable friend) or AI assistants (LLMs, eg ChatGPT, Claude, DeepSeek, or Gemini) as long as:

1. all significant parts of the work that you submit are done by you, and
2. if you reuse code “suggested” by an external source, you have to understand how it works;
3. how you use form of external help is documented and acknowledged in the submission.

With code, this policy means that all major parts submitted must be written mostly by you, and you must be able to explain how they work. However, you are welcome to use a chatbot to answer general questions, including for math (how do I compute a normal vector?) or programming (how do I write to a file in C++?). Getting short excerpts of code is also okay (how do I use this function?), as is getting debugging help (how do I fix this error?).

As for reports, all significant ideas in the final report should come from you. However, you are welcome to use AI for brainstorming (what are some interesting plots I can include?) or helping with structure (what should the sections of my report be?), grammar, or clarity (rephrase this paragraph).

If in doubt, please ask us if something is allowed. Violations of this policy will be considered plagiarism and will result in disciplinary action.

How to best follow this course

Every week:

1. Go the course homepage and check the week’s schedule.
2. In your own time, study the lessons of the week by watching the videos and reading the materials. The course works best if you at least skim it in advance, but we know that this is not always possible.
3. If you have any doubts about the contents of the lessons, ask questions on Discord. Asking on the geo1015-2025 text channel is best, but a DM is okay if you are uncomfortable with that. If you ask during the contact hours, we will answer quickly. If not, we will still answer, but it might take longer.
4. Try to answer the questions included at the end of the book chapter for a lesson. If you are not sure if your answers are correct, ask on Discord.
5. Optionally, have a look at some of the other materials (eg papers and videos) listed at the end of the chapter.
6. After studying the lessons of the week, work on the assignment(s) listed for that week.
7. As you work on an assignment, discuss it with your classmates and with us. High-level collaboration (eg general strategies to tackle a problem) is encouraged. Using others’ code is not and will be considered plagiarism.
8. If you get stuck in part of an assignment or want to run your strategy by us, tell us on Discord. We will not give you the solution to an assignment, but we will help you get on a good track to complete it.

All deadlines and rules are posted in this website, but we can in certain cases be flexible if needed (serious sickness, death in the family, etc.). This should be done before the deadline. We will also be widely available to help you on Discord and in person too, so don’t hesitate to ask questions. General software or programming questions are also okay, so please ask ahead. No one is born an expert, so there are no dumb questions.

Expected prior knowledge

The course is designed for students from the MSc Geomatics, and the following courses are required prerequisites:

1. GEO1000, or knowledge of a programming language, eg Matlab, Java or Python
2. GEO1001
3. GEO1002

Course content

Digital terrain models (terrains) are computer representations of the elevation of a given area, and they play an important role in understanding and analysing our built environment. They are the necessary input for several applications (eg flood modelling, visibility, effects of climate change on the north poles, etc.), and they are also relevant for studying the seabed and other planets.

The course provides an overview of the fundamentals of digital terrain modelling (DTM):

• different representations of terrains: TINs, rasters, point clouds, contour lines
• reconstruction of terrains from different sources (LiDAR, photogrammetry, InSAR)
• spatial interpolation methods
• conversion between different DTM representations
• processing of DTM: outlier detection, filtering, segmentation, and identification and classification of objects
• applications, eg runoff modelling, watersheds computations, visibility
• techniques to handle and process massive datasets

The course has both a theoretical part and a practical part where students reconstruct, manipulate, process, and extract information from terrains.

All the labs are programming tasks (to be done with the Python or C++ programming languages), and other open-source libraries and software are used.

Study goals

At the end of the course, students will be able to:

• describe the characteristics of elevations datasets from different sources (LiDAR, photogrammetry, InSAR)
• describe the pros and cons of different representations of terrains, and compare them for different applications
• explain how elevation datasets can be automatically converted to terrains
• reconstruct and manipulate terrains using open-source libraries
• explain, analyse, and discuss how terrains can be useful in different applications related to built environment
• given a specific problem where elevation plays a role (eg visibility or flood modelling), analyse and identify which data and algorithms are needed to solve the problem, and assess the consequences of these choices;