Remote sensing, profound notions

Duration

15h Th, 20h Pr

Number of credits

Lecturer

Yves Cornet

Language(s) of instruction

French language

Organisation and examination

Teaching in the second semester

Schedule

Schedule online

Units courses prerequisite and corequisite

Prerequisite or corequisite units are presented within each program

Learning unit contents

Theory
I. Processing of monogenic images
1. Advanced classifications of a single spectral band (Maximun Enthropy Thresholding)
2. Geometric corrections (polynomial transformations, direct georeferencing, orthorectification, digit number interpolation)
3. Advanced radiometric corrections (solar zenital angle computation and its radiometric effects correction, relative radiometric normalization, topographic normalization)
4. Advanced focal processing (Haralick texture analysis, mathematical morphology)
 
II. Processing of polygenic images
5. Polygenic transformations
6. Classification of images
7. Multi-source analysis
 
III. Some applications
8. Observation of emerged land (NDVI, LST, analysis of temporal series, teleconnections, LCC ...)
9. Satellite oceanography (SST, LSWT, Ocean Color, analysis of temporal series, teleconnections, bathymetry, classification of sea beds, radar imagery ...)
 
IV Access to the image archives
10. Selection and download of free images from the USGS server
Practical lessons
During the supervised work sessions, we will practically illustrate the theoretical concepts using several software writing scripts in MatLab and Octave.

Learning outcomes of the learning unit

Students will gain
* An understanding the acquisition process and nature of remote sensing imagery used in the different fields of Earth, Living and Sea Sciences
* A knowledge of the main types of processing applied to remote sensing imagery.
* A grasp the functions of image processing using specific software tools.
This course of advanced remote sensing should enable the student to design original solutions making it possible to answer new questions in the different application fields of remote sensing.
By also using the skills and mindset acquired during previous Bachelor courses (mathematics, statistics, physics, cartography, error propagation, digital methods applied to geography, programming ...), the student should then demonstrate the crucial scientific rigor necessary for the analysis of technical solutions, in their reliable formulation, in their implementation and analysis of their results.
Using basic knowledge learned on the course, the student should have acquired specific skills allowing him to attend several Master courses: complements of remote sensing, photogrammetry and complements of photogrammetry.

Prerequisite knowledge and skills

The course is a continuation of the introductory course on remote sensing of the second year Bachelor degree. The last is thus a prerequisite.
It involves an intense use of mono and multivariate statistical processing and principles of spatial analysis. In addition, it frequently refers to notions of analysis, matrix calculus and analytic geometry studied in mathematics. Several concepts physical science (electromagnetic spectrum, light radiation, Planck's equation, units and dimensions ...) are also important for a good understanding of this course.
It also calls upon a certain number of concepts of digital and mathematical cartography. Software tools applied during practical sessions for different courses given by members of the Geomatics Unit are also used.
These concepts and the use of these tools are briefly recalled along the year during theoretical and practical lessons.
In addition, the mindset trained during the different courses of physics, mathematics, programming, cartography and spatial analysis will be essential.

Planned learning activities and teaching methods

The theory lessons are of the ex-cathedra type. Many complementary reminders to the digital supports made available to the students are done on the blackboard during the lessons. At the beginning of each lesson a fifteen minute period is devoted to student's questions on the subject matter covered in the previous lesson. In addition, we also suggest that the students use an exercise book. This contains numerical examples illustrating the different methods explained during the theoretical lessons. Their aim is to enable the student to understand those methods I have identified over the years as being the most complicated. Typical answers are supplied. These exercises can be carried out with calculation or programming tools known to the students (Excel, Calc OpenOffice, programming languages learned during computer courses, scientific calculators ...) and don't need any image processing software.
The practical lessons are split into two parts, the supervised work and the practical work.
The supervised works are carried out mainly using Idrisi software but also under Grass, SAGA, Seadas, Matlab and Octave. They illustrate almost all the methods explained during the theoretical lessons. Supervised works lessons alternate with theoretical lessons. Typical exercises and data sets comparable to those explained and used during supervised work lessons as well as their solutions are provided to students to enable them to autonomously test their capacity for using software before the exam. Some exercises of practical exam of former years are also provided whit typical solutions.
The practical works deals with the application of classification methods to novel data sets. An account of the processing steps and graphic, cartographic and numerical results will be sent to the professor by the student who will be questioned orally on the contents of this report.
The students have free access to the Idrisi license and other software programmes through the VPN of ULg. For more information on access to these software, they can consult the following web address : http://www.gitan.ulg.ac.be/cms.
This site also contains the schedule for use of the classrooms of building B5a. If students wish to use thos rooms to complete their projects or to help them in their practical work, they can contact the staff of the Geomatics Unit.

Mode of delivery (face-to-face ; distance-learning)

The method of teaching is face-to-face. Presence is thus mandatory. Any absence must be justified by a medical certificate e.g. The lessons take place in room B5a/4/18 or B5a/2/35 according to the schedule distributed besides (http://www.facsc.ulg.ac.be/cms/c_253095/fr/horaires).
The ex cathedra theoretical lessons alternate with supervised works or tutorial lessons. The sessions of practical works take place after the theoretical and tutorials lessons.

Recommended or required readings

BONN F., 1996. Précis de télédétection. 3 volumes. Presses de l'Université du Québec.
MATHER P.M., 1999. Computer Processing of Remotely-Sensed Images. 2e édition. Wiley, Chichester, 292 p.
RUSSELL G. CONGALTON & KASS GREEN, 2008. Assessing the Accuracy of Remotely Sensed Data: Principles and Practices. CRC Pres, Second Edition.
Platform of Earth Observation (BELSO) : http://eo.belspo.be/ (consulté le 14/8/2014)
Landsat 7 handbook : http://landsathandbook.gsfc.nasa.gov/ (consulté le 14/8/2014)
Landsat 8 documentation: http://landsat.usgs.gov/landsat8.php (consulté le 14/8/2014)
Landsat Science : http://landsat.gsfc.nasa.gov/?page_id=11 (consulté le 14/8/2014)
NOAA documentation: http://www.ncdc.noaa.gov/oa/pod-guide/ncdc/docs/intro.htm (consulté le 14/8/2014)
Other references are provided via the eCampus platform.

Assessment methods and criteria

A permanent non-certificational self-evaluation is provided during exercise sessions by a strong interaction between students and teachers. It is also favoured by the exercises notebook with solutions and typical exercises with solutions of the practical exams of the former years.
The certificational evaluation will comprise three parts.
The first part of the exam consists of a written answer to a questionnaire on the theoretical lessons. This exam lasts two hours. It accounts for 50% of the overall mark if the obtained rating is 10/20 at least. In the opposite case, the rating obtained for this theoretical exam will be the rating of the overall evaluation.
The second one is the evaluation of the skill acquired during supervised works lessons. It is written open book exam on the use the Idrisi software to solve an exercise comparable to those carried out during supervised works lessons. The students have two hours to complete this exercise. This part of the exam accounts for 25% of the final mark if the obtained rating for the theoretical part is 10/20 at least.
The third part is an oral interrogation which deals with the report of the practical works lessons. This part of the evaluation takes place for 25% of the final mark, if the score obtained on the theoretical examination is at least 10/20.
The weighting mentioned above will thus be applied if the theoretical exam is passed (10/20 minimum). In the opposite case, the student will have to re-take the theory exam, in the second session.
This standard evaluation procedure can be changed by agreement with the students who will be informed.
The assessment criteria are as follows: clarity, coherence, logic, meticulousness, precision, completeness, brevity, relevance, cross-cutting nature (within the course and between courses), quality of mathematical interpretation (mathematical meaning of the different coefficients of the equation, e.g.), physical interpretation (dimensions and units, order of magnitude - scaling, e.g.) and geographical interpretations (single and multivariate spatial and temporal interaction - type - and meaning of the variables e.g.).
Critical thinking with respect to the data used (qualification, nature, meaning, representativeness, normalization ...) and methodological choices (justification of choice of methods, adopted thresholds ...) will also be taken into consideration when evaluation. Furthermore, answers will also be evaluated based on the quality and the originality of the graphic illustration since graphic expression is the scientist's specificity. It further allows demonstrating a good understanding of the phenomenon. Finally, enriching an answer with a rich personal scientific culture will also be considered a factor of excellence in the assessment.

Work placement(s)

Nil

Organizational remarks

Nil

Contacts

Yves CORNET, Professor
Geomatics Unit, 17 (B5a), Allée du 6 Août, 4000 Liège
Tel. 04 3665371
Mail : ycornet@ulg.ac.be
Web: http://139.165.44.35/cms/index.php

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