Duration
18h Th, 36h Pr
Number of credits
| Master in forests and natural areas engineering (120 ECTS) | 6 crédits |
Lecturer
Language(s) of instruction
French 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 course aims to introduce the techniques of acquisition, processing and analysis of very high resolution remote sensing data, with a specific focus on the monitoring of agricultural, forest and semi-naturals ecosystems.
This optional course follows the course ENVT0045 "Applied Geomatics and Remote Sensing".
The course is structured in 4 main parts:
- introduction to UAV imaging acquisition techniques;
- initiation to the processing and analysis of very high resolution aerial imagery (photogrammetric processing, segmentation and classification);
- introduction to LiDAR (aerial and terrestrial) data processing and analysis ;
- introduction to SAR time series processing and analysis (Sentinel-1).
Learning outcomes of the learning unit
At the end of this course, the student must be able to:
- Select a UAV equipment (platform and sensor) for a given objective;
- Prepare and execute a data acquisition campaign with a UAV;
- Process and analyze an image dataset produces with UAV (photogrammetric processing, analysis of the 3D model, classification);
- Process ans analyze an Aerial LiDAR dataset (process of the point cloud and the raster layers derived from it)
- Preprocess and analyze time series of Sentinel-1 SAR data.
Prerequisite knowledge and skills
ENVT0045 "Applied Geomatics and Remote Sensing"
Planned learning activities and teaching methods
Table of Contents
1. Introduction and Reminders
2. UAV
2.1. Theoretical concepts (operation, piloting, regulation, sensors)
2.2 Implementation (flight planning and execution, image acquisition)
3. LiDAR
3.1 Theoretical concepts
3.2 Data acquisition
4. Image and data processing
4.1. Theoretical concepts of photogrammetry
4.2 Photogrammetric processing of UAV imaging (Photoscan software)
4.3. Aerial image processing (introduction to Python, GDAL and OTB tools)
4.4. LiDAR data processing (lidR package)
4.5. SAR Sentinel1 image processing (with GDAL and OTB)
5. Seminar: presentation of case studies and specific equipment
6. Projects: typical projects carried out by students (alone or in groups depending on the number of students enrolled in the course)
Translated with www.DeepL.com/Translator
Mode of delivery (face-to-face ; distance-learning)
The course is organized as follows:
- a series of theoretical sessions
- a seminar (presentation of specific projects or equipment)
- tutorial sessions
- sessions dedicated to the realization of mini-projects based on the valorization of existing datasets
Recommended or required readings
The teaching materials will be available on eCAMPUS page of the course and on a dedicated server for the datasets.
Assessment methods and criteria
Evaluation of the project report
Work placement(s)
Organizational remarks
Contacts
p.lejeune@ulg.ac.be