Checking date: 21/05/2019

Course: 2019/2020

Earth Observation Data Processing
Study: Master in Space Engineering (360)

Coordinating teacher: SOTO SANTIAGO, LUCIA

Department assigned to the subject: Department of Signal and Communications Theory

Type: Electives
ECTS Credits: 3.0 ECTS


Students are expected to have completed
There are no specific requirements, besides those needed for admission to the Programme.
Competences and skills that will be acquired and learning results.
Basic skills: CB6 - To possess and understand knowledge that provides a basis or opportunity to be original in the development and / or application of ideas, often in a research context. CB9 - Students must know how to communicate their conclusions and the knowledge and ultimate reasons that sustain them to specialised and non- specialised audiences in a clear and unambiguous way. General skills: CG5 - Ability to handle the English, technical and colloquial language. Specific skills: - Ability to understand, visualise, process and analyse data generated by Earth observation satellites.
Description of contents: programme
1. Earth observation missions 2. Remote sensing 3. Data types & collection 4. Data processing tools 5. Project
Learning activities and methodology
Two teaching activities are proposed: lectures and practical sessions. LECTURES AND EXAMPLES (2 ECTS) Lectures will be delivered using the blackboard, with slides or by any other means to illustrate the concepts to be learnt. In these classes the explanation will be completed with examples. In these sessions the student will acquire the basic concepts of the course. It is important to highlight that these classes require the initiative and the personal and group involvement of the students (there will be concepts that the student himself should develop). PRACTICAL SESSIONS (1 ECTS) The practical classes will solve practical cases as well as laboratory sessions in which real and synthetic data sets will be analysed. Basic concepts learnt during the course are applied in the laboratory and by means of simulation. The student should participate actively the exercise implementation; the level of the student involvement in this work grows from the first exercise to the last one where the student will be encouraged to propose and solve the problem.
Assessment System
  • % end-of-term-examination 0
  • % of continuous assessment (assigments, laboratory, practicals...) 100
Basic Bibliography
  • C. Solomon, T. Breckon. Fundamentals of digital image processing: a practical approach with examples in Matlab. John Wiley & Sons. 2011
  • R. J. Doviak, D. S. Zrnic. Doppler radar and weather observations. Academic Press. 1993
  • W. L. Wolfe. Introduction to spectrometers. Bellingham. 1997
Recursos electrónicosElectronic Resources *
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The course syllabus and the academic weekly planning may change due academic events or other reasons.