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Navigation and Earth Observation Systems

Code: 43846
Credits: 6
2026/2027
Degree programme Type Course
Geoinformation OB 1

Contact lecturer

Name :
Jordi Cristobal Rosselló
Email :
jordi.cristobal@uab.cat

Group languages

You can consult this information at the end of the document.

Prerequisites

This course has no specific requirements. Students should only have a basic knowledge of software as user level.

Objectives

Earth observation systems provide a synoptic view of the territory. This advantage, offered by a platform located at a certain altitude, has been exploited from aerial platforms for more than a century. However, the operational use of satellite systems is relatively recent, with its origin and widespread application dating back to the 1970s, with the launch of the Landsat programme. Today, spectral, spatial and temporal resolution form an equation of use and applicability that ranges from optical or thermal systems to active systems, such as radar systems, enabling a better understanding of the territory in environmental, resource management and sustainability contexts.


Navigation is the set of arts and techniques that make it possible to move from point A to point B efficiently and safely, whether by means of course and speed, the use of known references, or coordinates on paper or electronic charts. With the development of radiocommunications, first terrestrial and later satellite-based from the 1970s onwards, satellite radionavigation systems emerged, such as GPS and GALILEO, which have made positioning and navigation widely used on a global scale.


In this context, the specific objectives of the course are to provide:


- The basic knowledge required to understand and use the data provided by satellite systems for Earth observation, navigation and positioning, particularly in terms of accuracy and temporal, spectral and spatial resolution.

- The theoretical and practical knowledge needed to develop critical thinking about which technologies and approaches are most suitable for solving geoinformation projects, both in the field of Earth observation and in positioning.

- The specific practical skills required for the use and analysis of the information provided by Earth observation technologies and navigation and positioning systems, in order to exploit them effectively.


Learning outcomes

  • CA03 (Propose positioning and navigation instruments to measure biophysical parameters with different levels of precision and performance.) Propose positioning and navigation instruments to measure biophysical parameters with different levels of precision and performance.
  • CA04 (Extract information from the data provided by the different types of images obtained by Earth observation systems.) Extract information from the data provided by the different types of images obtained by Earth observation systems.
  • CA05 (Integrate optimal geospatial information technologies, services and applications into each application case.) Integrate optimal geospatial information technologies, services and applications into each application case.
  • CA06 (Explain the societal implications of the use and dissemination of geospatial information and its derivative products taking into account ethical responsibility and related legislation.) Explain the societal implications of the use and dissemination of geospatial information and its derivative products taking into account ethical responsibility and related legislation.
  • KA04 (Distinguish the main types of satellite platforms and sensors for the necessary processing of the data they provide.) Distinguish the main types of satellite platforms and sensors for the necessary processing of the data they provide.
  • KA05 (Choose the coordinate system for a given geographical area and the derived sensors and data products for each type of study and application.) Choose the coordinate system for a given geographical area and the derived sensors and data products for each type of study and application.
  • KA06 (Accurately and reliably distinguish between navigation and positioning systems and techniques for the different navigation and field data collection scenarios.) Accurately and reliably distinguish between navigation and positioning systems and techniques for the different navigation and field data collection scenarios.
  • SA04 (Use navigation and positioning techniques to establish both navigation and position reliably and accurately.) Use navigation and positioning techniques to establish both navigation and position reliably and accurately.
  • SA05 (Apply the physical foundations of Earth observation to the analysis and processing of data from remote sensors.) Apply the physical foundations of Earth observation to the analysis and processing of data from remote sensors.
  • SA06 (Review the post-processing and analysis of the data of interest provided by the navigation and global positioning systems by satellite.) Review the post-processing and analysis of the data of interest provided by the navigation and global positioning systems by satellite.

Contents

Physical principles of remote sensing, image processing, and information extraction from Earth observation data


  1. Physical principles of optical, thermal, and microwave remote sensing.
  2. Platforms and sensors.
  3. Geometric and radiometric corrections of multi/hyperspectral data.
  4. Fundamentals of digital image processing.
  5. Extraction of quantitative information from remote sensing data.


Positioning, surveying, and navigation


  1. Introduction to navigation: Global Navigation Satellite Systems (GNSS).
  2. Navigation sensors, system integration, and architecture.
  3. Geodesy, measurement, reference systems, and map projections.
  4. Geolocation, case studies, and market.


Learning activities and methodology

Title Hours ECTS Learning outcomes
Lectures on basic concepts 24 0.96 CA03, CA04, CA05, CA06, KA04, KA05, KA06, SA04, SA05, SA06
Study and exercises 40 1.6 CA03, CA04, CA05, CA06, KA04, KA05, KA06, SA04, SA05, SA06
Supervised exercises 11 0.44 CA03, CA04, CA05, CA06, KA04, KA05, KA06, SA04, SA05, SA06
Field exercises 4 0.16 CA03, CA04, CA05, CA06, KA04, KA05, KA06, SA04, SA05, SA06
Guided practical exercises at the classroom 12 0.48 CA03, CA04, CA05, CA06, KA04, KA05, KA06, SA04, SA05, SA06
Design and presentation of potential applications integrating remote sensing and navigation 29 1.16 CA03, CA04, CA05, CA06, KA04, KA05, KA06, SA04, SA05, SA06

Learning is achieved by means of three types of activities.

Directed activities: Directed activities are theoretical and practical lectures in a computer lab. They include solving case studies and practical exercises. Lectures are the common thread of the course. Lectures serve to systematize all the content, to present the state of the art of the different subjects, to provide methods and techniques for specific tasks, and to sum up the knowledge to learn. Lectures organize also the autonomous and complementary work done by the students

Supervised activities: Supervised activities are focused on the execution of a semester project, consisting of a real case study, carried out through workshop hours, autonomous work and tutorials. This semester project allows to apply together all the knowledge and technical skills learnt in all the courses of the semester. The semester project is a milestone for the students and the actual demonstration that they had achieved the learning goals of all the courses of the semester. It is also the main evidence for evaluation as students should have to submit at the end of the semester a report that summarizes the whole project and do an oral presentation.

Autonomous activities: Autonomous work of the students includes personal readings, data and documentation search, complementary exercises and the personal development of the semester project.

The activities that could not be done onsite will be adapted to an online format made available through the UAB’s virtual tools. Exercises, projects and lectures will be carried out using virtual tools such as tutorials, videos, Teams sessions, etc. Lecturers will ensure that students are able to access these virtual tools, or will offer them feasible alternatives.

Annotation: within the schedule set by the centre or degree programme, 15 minutes of one class will be reserved for students to evaluate their lecturers and their courses or modules through questionnaires.

Assessment

Continuous assessment activities

Title Weight Hours ECTS Learning outcomes
Practical exercises 35 10.5 0.42 CA03, CA04, CA05, CA06, KA04, KA05, KA06, SA04, SA05, SA06
Report submissions 45 13.5 0.54 CA03, CA04, CA05, CA06, KA04, KA05, KA06, SA04, SA05, SA06
Oral presentations 20 6 0.24 CA03, CA04, CA05, CA06, KA04, KA05, KA06, SA04, SA05, SA06

If the assessment activities cannot be carried out in person, their format will be adapted (while maintaining their weighting) to the possibilities offered by the UAB virtual tools. Assignments, activities and class participation will be carried out through forums, wikis and/or exercise discussions via Teams, etc. The lecturer will ensure that the student can access them or will offer alternative means that are within their reach.


CONTINUOUS ASSESSMENT. This course/module does not provide for the single assessment system.


a) Assessment process and activities:


The assessment of the module is mainly based on the completion of the semester project, which is assessed through two activities. On the one hand, the preparation and submission of the project summary report and, on the other, the oral defence of the project carried out. Given the highly technical content of the module, a weighting of 45% is assigned to the project report, as it is the most appropriate means of presenting the technical details in all their complexity, and a weighting of 20% is assigned to the oral defence. The assessment is complemented by 35% corresponding to the completion of practical exercises.

Unless otherwise indicated, the submission of the exercises is compulsory. In order for the exercises to be averaged with the project, they must have an average grade equal to or higher than 5.

Unless otherwise indicated, all assessment activities (semester project report, oral presentation of the semester project and practical exercises of the module) are individual.

The hours allocated to each assessment activity include the time devoted to preparing the assessment materials for each activity (report, presentation, etc.).


b) Scheduling of assessment activities:


1st semester project report: Making during all the semester. Submission at the end of semester, on January 22nd 2027.

1st semester project oral presentation: Making during all the semester. Oral presentation at the end of semester, on January 28th 2027.

Practical exercises of the module: completed and submitted weekly or fortnightly throughout the semester.


c) Assessment review procedure:


Once the grades have been published, students will have one week to request a review by arranging an appointment with the corresponding lecturer(s).


d) Resit process:


First-semester project report: may be resubmitted within a maximum period of 2 weeks after the scheduled submission date. The resit will consist of submitting the full report again in the event of a negative assessment of the first submitted report.

Oral defence of the first-semester project: may be retaken within a maximum period of 1 week after the scheduled date. The resit will consist of carrying out the oral defence again in the event of a negative assessment of the first oral defence.

Practical exercises of the module: not recoverable.

In order to take part in the resit process, the student must previously have been assessed in a set of activities whose weighting is equivalent to at least two thirds of the total assessment of the module. Therefore, the student must necessarily have been assessed on the scheduled date of the project report (45%) and the oral defence (20%) of the semester project.

Only students who have not passed the module assessment (minimum overall grade of 5.0) and who have obtained a minimum overall module grade higher than 3.5 may take part in the resit process.


e) Conditions for the grade “Not assessable”:


The student will receive the grade “Not assessable” instead of “Fail” provided that they have not submitted the first-semester project report nor completed the oral defence of the first-semester project. The student will receive the grade “Not assessable” whenever they have not submitted more than one third of the assessment activities.


f) UAB regulations on plagiarism and other irregularities in the assessment process:


If the student commits any irregularity that may lead to a significant variation in the grade of an assessment activity, that assessment activity will be graded 0, regardless of any disciplinary proceedings that may be initiated. If several irregularities occur in the assessment activities of the same course, the final grade for that course will be 0.

Assessment activities graded 0 due to irregularities committed by the student may not be reassessed.

At the time each assessment activity is carried out, the lecturer will inform students of the procedure and date for reviewing the grades.


At the time of each evaluative activity, the teacher will inform the students (Moodle) of the procedure and the date for reviewing the grades.


USE OF AI


In this course, the use of Artificial Intelligence (AI) technologies is permitted as an integral part of the development of the work, provided that the final result reflects a significant contribution by the student in terms of analysis and personal reflection. The student must clearly identify which parts have been generated using this technology, specify the tools used and include a critical reflection on how these tools have influenced the process and the final result of the activity. Lack of transparency in the use of AI will be considered a breach of academic honesty and may result in a penalty in the grade for the activity, or more severe sanctions in serious cases.


Bibliography

Campbell, J. B., Wynne, R. H., & Thomas, V. A. (2022). Introduction to remote sensing (6th ed.). Guilford Press.

Chuvieco, E. (2026). Fundamentals of satellite remote sensing: An environmental approach (4th ed.). CRC Press. https://doi.org/10.1201/9781003516149

Hofmann-Wellenhof, B., Lichtenegger, H., & Wasle, E. (2008). GNSS—Global navigation satellite systems: GPS, GLONASS, Galileo, and more. Springer. https://doi.org/10.1007/978-3-211-73017-1

Jacobson, L. (2007). GNSS markets and applications. Artech House.

Jensen, J. R. (2022). Introductory digital image processing: A remote sensing perspective (4th ed.). Pearson.

Kaplan, E. D., & Hegarty, C. J. (Eds.). (2006). Understanding GPS: Principles and applications (2nd ed.). Artech House.

Krisp, J. M., Meng, L., Pail, R., & Stilla, U. (Eds.). (2013). Earth observation of global changes (EOGC). Springer. https://doi.org/10.1007/978-3-642-32714-8

Leick, A. (2004). GPS satellite surveying (3rd ed.). John Wiley & Sons.

Lillesand, T. M., Kiefer, R. W., & Chipman, J. W. (2015). Remote sensing and image interpretation (7th ed.). Wiley.

Ormeño Villajos, S. (2006). Teledetección fundamental (3.ª ed.). Fundación General de la Universidad Politécnica de Madrid.

Rees, W. G. (2013). Physical principles of remote sensing (3rd ed.). Cambridge University Press. https://doi.org/10.1017/CBO9781139017411

Richards, J. A. (2022). Remote sensing digital image analysis (6th ed.). Springer. https://doi.org/10.1007/978-3-030-82327-6

Wolf, P. R., & DeWitt, B. A. (2000). Elements of photogrammetry: With applications in GIS (3rd ed.). McGraw-Hill.

Xu, G. (2007). GPS: Theory, algorithms and applications (2nd ed.). Springer. https://doi.org/10.1007/978-3-540-72715-6


Software

ESA SNAP

Google Earth Engine

Miramon

QGIS

Course groups and languages

The information provided is provisional until November 30. After this date, you will be able to consult the language of each group through this link. To access the information, you will need to enter the course CODE

Type of teaching Group Language Semester Shift
(TEm) Theory (master) 1 Catalan/Spanish first semester afternoon
(PLABm) Practical laboratories (master) 1 Catalan/Spanish first semester afternoon