Duration
20h Th, 20h Pr
Number of credits
| Master of Science (MSc) in Aerospace Engineering | 5 crédits | |||
| Master in space sciences (120 ECTS) | 5 crédits |
Lecturer
Language(s) of instruction
English language
Organisation and examination
Teaching in the first semester, review in January
Schedule
Units courses prerequisite and corequisite
Prerequisite or corequisite units are presented within each program
Learning unit contents
The theoretical lessons address the following topics:
- General theoretical concepts in Earth observation
- Optical remote sensing
- Thermal infrared remote sensing
- Passive and active microwave remote sensing
- Advanced Earth observation: very high-resolution (drones, nanosatellites) and hyperspectral remote sensing
- Earth observation applications for land monitoring
- Time series extraction of optical vegetation indices (Google Earth Engine)
- Time series analysis for land monitoring (Python Notebook)
- Radar data processing for flood monitoring
- LiDAR and photogrammetric drone data processing
- Retrieval of biophysical variables from hyperspectral data (radiative transfer modelling)
Learning outcomes of the learning unit
This course provides an introduction to remote sensing, with emphasis on matter-radiation interactions that determine the observables accessible in each region of the electromagnetic spectrum.
At the end of the course, the student will be able to understand the theoretical concepts in Earth observation and apply advanced signal processing techniques.
Prerequisite knowledge and skills
The Course is accessible to any Bachelor in Sciences or Applied Sciences.
Planned learning activities and teaching methods
Theoretical and pratical lectures combined with a project.
Mode of delivery (face to face, distance learning, hybrid learning)
Face-to-face course
Additional information:
Theoretical and pratical lectures are face-to-face (every week).
A project is carried out remotely by group of typically two students.
Recommended or required readings
Slides of the theoretical and pratical lectures are available on eCampus. Links to additional material (books or papers) are also provided at the end of each set of slides.
Exam(s) in session
Any session
- In-person
oral exam
Written work / report
Additional information:
The evaluation is based on the the project (40%) and an oral exam (60%).
Each project will require to submit a report in the form of a PowerPoint presentation as well as the Python code in due time. Eeach group will be given the opportunity to present and defend his project in front of the class. The project is compulsory, students who have not realised and presented the project will not be allowed to take the exam.
The goal of the oral exam will be to assess the understanding of theoretical lectures. Students will have to present one or several parts of the course and answer questions covering the whole course material.
Work placement(s)
Organizational remarks
None
Contacts
Prof. François Jonard, francois.jonard@uliege.be