Contact hours

  • Tuesdays 13:45-16:30 (check the timetable for the room, it’s changing often)
  • (bring your laptop)

Education methods

This is a blended-learning course. There is formally no lectures, the contact hours (3h on Tuesdays) are there to answer questions and help you with the assignments. We will not give any lectures, and thus these sessions are not mandatory (except the one during week 2.5 when there is a quiz (5% final mark)).

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

Marking

final exam 35% 2019-02-01
mid-term quiz 5% 2018-12-11
4 assignments (all programming with Python) 60% (15% each)  
  • a total of 6.0 or above is necessary to successfully pass the course;
  • minimum 5.5 for the final exam required;
  • there is one resit for each assignment (only at the end of the course if the whole course is failed; can’t just redo an assignment to aim at higher score);
  • there is one resit for the final exam;
  • there is no resit for the quiz;
  • if the overall 6.0 is not obtained after the resits, then the student has to redo the whole course the following year.

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 scripting/programming in at least one language, eg Matlab, Java or Python; using Python is mandatory for the assignments)
  2. GEO1001
  3. GEO1002

Course Content

Digital terrain models (DTMs) 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 for seabed and other planets.

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

  • different representations of DTMs: TINs, rasters, point clouds, contour lines
  • reconstruction of DTMs 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 DTMs.

All the labs are programming tasks (to be done with the Python 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 DTMs, and compare them for different applications
  • explain how elevation datasets can be automatically converted to DTMs
  • reconstruct and manipulate DTMs using with open-source libraries (in Python)
  • explain, analyse, and discuss how DTMs 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;