|Course code module||MBIO20451|
|Study load (hours)||112|
|Language of instruction:||English|
|Semester exam information:||exam in the 2nd semester|
|Contract restriction information:|
2. Objectives (expected learning outcomes)
At the end of this course:
1) you know the basic principles of remote sensing, and you can explain them;
2) you know the different sensor techniques and types, and you know the advantages and disadvantages of these sensors, and you know which sensors are suited for a certain application;
3) you know the different satelite platforms, and you know the principles of air borne observation, the differences between both, and you can explain these differences;
4) you know the different image analysis techniques, you know what they can be use for;
5) you are familiar with image interpretation and post-treatment of these images;
6) you are familiar with the remote sensing production chain (from satelite to user); and
7) you can apply these remote sensing techniques for a broad range of remote sensing data covering a wide range of ecosystems, and a wide range of applications.
3. Course content
I. Basic principles remote sensing:
(Electromagnetic spectrum, atmospheric windows, interaction of radiation with vegetation)
II. Sensor techniques and types, satellite platforms, airborne observation:
(Overview of sensors, platforms and spatial resolution)
III. Satellite image treatment: geometric correction and map projections,
atmospheric correction, modelling radiaton transfer and bi-directional reflectance
IV. Image interpretation and post-treatment: spectral information, geometric resolution,
radiometry, reduction of image information (histograms, classification))
V. The remote sensing production chain:
(Excursion: visit to an image treatment centre)
Remote sensing applications
Casus 1: Field techniques and product validation: Field sensors,
determination of biophysical variabels (LAI, fAPAR, degree of vegetation coverage, ...)
Casus 2: Remote sensing applications in relation to climate change
(estimation of carbon fluxes and balances)
Casus 3: Hydrological applications
(evapotranspiration and soil water estimates)
Casus 4: Estimating biodiversity by means of hyperspectrale remote sensing
(Classification of coastal vegetation)
Casus 5: Application of remote sensing in marine environments (radiation transfer
in water, chlorophyll concentration, total suspended matter,...)
4. Teaching method
Direct contact: LecturesExercise sessions
Personal work: Assignments - individual
5. Assessment method
Exam: Oral, with written preparationClosed bookPractical exam
Continuous assessment: Exercises
6. Compulsory reading – study material
The slides that will be used during the lectures will be made available on Blackboard.
7. Recommended reading - study material
During the first lecture you will be tested on your a priori knowledge of remote sensing, and you will be asked for your expectations in relation to this course. The way of teaching in both theoretical lectures and practical exercises will be explained.
Also during this first lecture you will receive the slides of that lecture, and it will be explained how you can obtain the slides for the following lectures from Blackboard.
In the lectures the slides will be explained as they only contain the main information which might be difficult to interpret without additional information. Although it is not obliged to follow the theoretical lectures, it is strongly recommended to follow these lectures because of the beforementioned reasons. If you can not follow the lectures you should ask your colleagues for more information on the slides.
Practical exercises should be followed. If the exercises cannot be finished within the foreseen time, you should finish the exercise outside the regular time schedule. You can ask for additional information, and for practical arrangements so that you can practice with the software outside the regular time schedule. During the practical exercise you can discuss with your colleagues to solve the exercise and share experience. In contrast the report you should deliver for each exercise is an individual work. You will receive feedback on this report.
During the last lecture it will be explained in detail how the exam will be organised, what you should know, how you should know, what the evaluation criteria are,...
If you should redo the exam, it is strongly recommend to meet so that I can give you some feedback on what went wrong, and what and how your performance can be improved.