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Processing Remote Sensing Images

Code: 43384
Credits: 6
2026/2027
Degree programme Type Course
Remote Sensing and Geographical Information Systems OB 1

Contact lecturer

Name :
Xavier Pons Fernandez
Email :
xavier.pons@uab.cat

Teaching staff

Xavier Pons Fernandez

Teaching staff (external to UAB)

Jordi Joan Mallorquí Franquet
Mercè Vall-Llossera Ferran
Joan Cristian Padró Garcia
Jordi Cristóbal

Group languages

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

Prerequisites

Prerequisites are not required

Objectives

At the end of the course, the student will be able to:

  • Master different tools primary processing of aerial and satellite imagery.
  • Dominate the physical principles that govern remote image capture and transformations of the content of the image itself.
  • Distinguish the different sources of image geometric deformations and possible signal interference caused by atmospheric captured or lighting effects (topography, etc.).
  • Correctly apply the methodologies to mitigate the different error sources in order to be able to view and extract physical parameters of the received data.

Learning outcomes

  • CA03 (Propose innovative solutions to effectively solve complex problems in the primary processing of images obtained by remote sensors, making suitable decisions based on their knowledge and judgment.) Propose innovative solutions to effectively solve complex problems in the primary processing of images obtained by remote sensors, making suitable decisions based on their knowledge and judgment.
  • CA04 (Plan collaborative actions with academic institutions, public bodies and entities of the professional sector in the design and execution of R+D+I projects in Remote Sensing.) Plan collaborative actions with academic institutions, public bodies and entities of the professional sector in the design and execution of R+D+I projects in Remote Sensing.
  • KA04 (Recognise the physical principles that govern remote image capture, as well as the transformations of image content.) Recognise the physical principles that govern remote image capture, as well as the transformations of image content.
  • KA05 (Distinguish the different sources of geometric deformations in the image, as well as possible interference in the captured signal caused by atmospheric or lighting effects (topography, etc.).) Distinguish the different sources of geometric deformations in the image, as well as possible interference in the captured signal caused by atmospheric or lighting effects (topography, etc.).
  • SA05 (Process images taking into account geometric deformations, lighting conditions and different atmospheric conditions.) Process images taking into account geometric deformations, lighting conditions and different atmospheric conditions.
  • SA06 (Apply different tools and methodologies for the primary processing of images obtained by remote sensors for the subsequent extraction of geographic information.) Apply different tools and methodologies for the primary processing of images obtained by remote sensors for the subsequent extraction of geographic information.
  • SA07 (Determine a study methodology, based on the knowledge acquired, for specific use cases in the processing of Remote Sensing images.) Determine a study methodology, based on the knowledge acquired, for specific use cases in the processing of Remote Sensing images.
  • SA08 (Use various specialised GIS and Remote Sensing software, as well as other software related to the processing of Earth observation images and obtaining reliable geographic information.) Use various specialised GIS and Remote Sensing software, as well as other software related to the processing of Earth observation images and obtaining reliable geographic information.

Contents


PHYSICAL PRINCIPLES OF REMOTE SENSING

Solar spectrum

  1. Concepts: radiation and electromagnetic spectrum, polarization. Fundamental relationships between frequency, length and transported wave energy.
  2. Basic physical parameters (terminology and symbology, definitions, units): Radiant energy, energy flow, energy intensity, radiance energy excitance, irradiance, reflectance, albedo, transmittance, absorptance; absorbance. spectral magnitudes.
  3. Specular reflection, diffuse and lambertiana.
  4. Black body (Planck's law, Stefan-Boltzmann law, Wien's displacement law).
  5. Solar radiation. Exoatmospheric characteristics and the surface of the Earth; interaction with the atmosphere and atmospheric windows.
  6. Spectral signatures. Main characteristics of water, soil and rocks and vegetation in the visible and infrared non thermal.
  7. Factors that influence the spectral signature.

Thermal

  1. The thermal radiation emitted by the Earth. Remote Sensing approaches.
  2. Physical parameters of the thermal infrared region.
  3. KCL. black body, white body and gray body. selective radiators. Thermal behaviour of an object-related parameters.
  4. Thermal behavior of an object: related parameters.
  5. Spectral behaviour of the different coverages in the thermal infrared region.
  6. Factors which influence the emissivity.
  7. Emissivity measurement. Field measurements.
  8. Emissivity measurement. Measured from satellite.

Active microwave

  1. Active Microwave Remote Sensing: Imaging Radar.
  2. Wave-Matter interaction: Radar Cross Section and Backscattering Coefficient.
  3. Backscattering Coefficient.
  4. Backscattering models.
  5. SAR polarimetry.

Passive microwave

  1. Passive Sensors: Fundamentals andPhysical Principles.
  2. Applications of passive microwave E.O.
  3. Microwave Radiometers:
  4. Figures of Merit: Angular Resolution and Radiometric Resolution.
  5. Calibration: internal, external, use of multi-look information.
  6. Present and future EO Passive Microwave Mission.


GEOMETRIC CORRECTION OF AERIAL AND SATELLITE IMAGERY

  1. Geometric corrections. Deformation sources. Orthoimage, orthophoto and orthophoto of authentic orthophotomap concepts. Corrections in vectorial bases.
  2. Physical models (collinearity equations orbit models), semi-empirical (polynomial corrections, models of rational functions, Delaunay triangulation) and mixed. Model of radar images: determining the sampling step azimuth and distance. Relief role. Ground control points (GCP), test points, homologous points.
  3. Geometry of the radar image. Sampling of the image. Geometric distortion of images. Accurate geocoding images using Digital Elevation Models (DEM or DEM). Obtaining DEM and Radar Mapping. Approaches to areas of low relief. Examples.
  4. Basic correction process. Nearest neighbor, bilinear and bicubic interpolation: Chromatic, radiometric and geometric in image resampling. Considerations about output pixel size.
  5. Sources of GCP. Automatic GCP.
  6. Basics of physical models. Consideration of the relief.
  7. Basics of semi-empirical models:
  8. Polynomial models 1st an 2nd degree. Application cases.
  9. Higher polynomial model degree. Application cases.
  10. Polynomial models with consideration relay.
  11. Models of rational functions.
  12. Delaunay Triangulation.
  13. Mixed Models: Theory and examples ASTER, MODIS, SSM/I and SMOS.
  14. Errorestimate.Statistical interpretation of the RMS.
  15. Mosaics and geometry images.
  16. Practical realization of the main models.


RADIOMETRIC IMAGE CORRECTION

1. Radiometric corrections. Calibration sensors. Sources of signal distortion. DN conversion to radiances. Interest and obtaining reflectances.

2. Formulation corrections in the visible and infrared non thermal.

2.1 Sun and atmspheric roles. Exoatmospheric radiance, transmittance. Variation throughout the year. Spectral variation. Diffuse atmospheric radiation.

2.2 Relief role: incidence angle, projected shadows. Celestial sphere. Neighboring reflected radiation.

2.3 Combining sensors in the same study. Usability of pseudoinvariant areas (PIA).

2.4 Combined use of in situ sensors such as handheld spectroradiometers or sun photometers.

3. Corrections based in multispectral and large mount of images: advantages and limitations.

Learning activities and methodology

Title Hours ECTS Learning outcomes
Tutorials 4 0.16
Reading of articles / reports of interest 2 0.08
Master classes / exhibitions 27 1.08
Classroom practices 34 1.36
Resolution exercices 8 0.32
Personal study 15 0.6
Writing reports 58 2.32

Principal working language: spanish (spa), although the bibliographic materials may be in other languages, mostly English.

In this module there are 3 groups of learning activities:

  • Targeted activities consist of classes of theory and practices that will be carried out in a specialized computer room. At the beginning of each of the subjects that make up the module, the teachers will explain the structure of the theoretical-practical contents, as well as the evaluation method.
  • Supervised activities consist of classroom practices that will allow you to prepare the work and exercises of each subject, as well as tutorial sessions with the teachers in case the students request it.
  • Autonomous activities are a set of activities related to the elaboration of works, exercises and exams, such as the study of different material in the form of journal articles, reports, data, etc., defined according to the needs of autonomous work of each student
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 works 40% - 60% 0 0 CA03, CA04, KA04, KA05, SA05, SA06, SA07, SA08
Theoretical and practical exam 60% - 70% 2 0.08 CA03, KA04, KA05, SA05, SA06, SA07, SA08

This module does not incorporate single assessment.

The evaluation of this subject consists of the following system:

  • Brief theoretical and practical exams (50% of the grade), carried out during the teaching of the module, in the form of a truly continuous assessment. These exams will be face-to-face, of short duration (approximately 20'-30') and will be carried out at the beginning of some classes to check that students are understanding the course topics (prepared by themselves in many cases) as they are addressed. Then, once each exam is finished, and still in the classroom, the teacher will consolidate all the needed details, devoting some extra time to practical issues, etc. In addition, the results of these short assessments will be available almost immediately, which allows students to have a very fine control of how their course is progressing. This brings us closer to a flipped classroom teaching methodology, in which students do not need to prepare partial or final exams since they prepare the classes in advance, they continuously self-assess and thus the classroom time can be devote to solve doubts, consolidate knowledge and tackle all kinds of practical exercises (but based on a good knowledge of the theory, previously studied by themselves).
  • Theoretical exams of specific parts of the module (20 % of the grade).
  • The completion of different practical works proposed throughout the teaching of the module and delivered within the set deadline. A correct formal presentation and careful preparation will be assessed (30 % of the grade).

The exams or other evaluation procedures not reaching the minimum mark of 5 out of 10 will be considered “failed” and they must be repeated.

A student who has submitted less than 20 % of the requested assignments will be considered \"non-evaluable\". The same mark will be assigned to any student who has not taken any of the theoretical-practical tests, as it is considered that the student has not been able to provide sufficient evaluation evidence.

Aspects to take into account.

  • Regular class attendance in class is highly recommended for the correct monitoring of the subjects. Only in cases of physical impossibility of face-to-face assistance is streaming monitoring justified, since an important part of the experiences and learning are fully achieved through contact with the teaching staff and classmates.
  • If the tests cannot be taken in person, their format will be adapted (maintaining their weighting) to the possibilities offered by the UAB's online tools.
  • If practical work has to be delivered, this delivery must be done within the deadlines for them to be evaluated.
  • The review of grades for each assessment activity is done by writing an email to the responsible teacher in order to agree the date and time.
  • On carrying out each evaluation activity, Lecturers will inform about the procedures to be followed for reviewing all grades awarded, and the date on which such a review will take place.

Extraordinary exams.

  • This extraordinary exam is unique.
  • Students will have the opportunity to take an extraordinary exam the day or days scheduled by the faculty.

Cheating: Copies and plagiarisms.

  • The commission of any irregularity in an assessment activity (academic fraud, plagiarism or improper use of AI, unless such use is expressly authorised in the course guide) that may lead to a significant change in the grade will result in that assessment activity being graded with a 0. If the course guide stipulates that obtaining a minimum grade in that assessment activity is an essential requirement for passing the course, or if several irregularities occur in the assessment activities of the same course, the final grade for that course will be 0. In addition, disciplinary proceedings may be initiated against any student who incurs any of these irregularities.

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mountainous terrain" Remote Sensing of Environment, 124:756–770

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Active and passive microwave

Broquetas Ibars, A, D Casado, R Martín, M Fernández Usón, A Monti Guarnieri, A Leanza (2016) “Track compensation and calibration of continuous monitoring GEOSAR missions”, IGARSS 2016, doi: 10.1109/IGARSS.2016.7729360

Emery, W., Camps, A. (2017) "Introduction to Satellite Remote Sensing.

Atmosphere, Ocean, Land and Cryosphere Applications". Elsevier. 860 pàgs.

Shimada, M (2018) “Imaging from Spaceborne and Airborne SARs, Calibration, and Applications”, CRC Press.

Ulaby, FT, DG Long, WJ Blackwell, C Elachi, AK Fung, C Ruf, K Sarabandi, HA Zebker, J van Zyl (2014) “Microwave Radar and Radiometric Remote Sensing”, University of Michigan Press.


Physical principles of Remote Sensing

Solar spectrum

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Berger, K.; Hank, T.; Halabuk, A.; Rivera-Caicedo, J.P.; Wocher, M.; Mojses, M.; Gerhátová, K.; Tagliabue, G.; Dolz, M.M.; Venteo, A.B.P.; Verrelst, J. (2021) Assessing Non-Photosynthetic Cropland Biomass from Spaceborne Hyperspectral Imagery. Remote Sensing, 13:4711. https://doi.org/10.3390/rs13224711

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evidence and climate significance, Geophysical Research Letters, 38, L01706, doi:10.1029/2010GL045777.

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Melià, J. (1991) "Fundamentos físicos de la teledetección: leyes y principios básicos", in Gandía, S., J. Melià (eds.) "La teledetección en el seguimiento de los fenómenos naturales. Recursos renovables: Agricultura." Departament de Termodinàmica. Universitat de València. pp. 51-83.

Milton, E.J., Schaepman, M.E., Anderson, K., Kneubühler, M., Fox, N. 2009 Progress in field spectroscopy, Remote Sensing of Environment: 113 (1), S92-S109.

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Van de Griend, A. A., Owe, M. (1993) On the relationship between thermal

emissivity and the normalized difference vegetation index for natural surfaces,

International Journal of Remote Sensing, 14: 1119-1131.

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Zhao, F., W. Ma, J. Zhao, Y. Guo, M. Tariq, J. Li (2024) Global retrieval of the spectrum of terrestrial chlorophyll fluorescence: First results with TROPOMI, Remote Sensing of Environment, 300: 113903.

Active and passive microwave

Cumming, IC, Wong, FH (2005), “Digital Processing of Synthetic Aperture Radar Data: Algorithms and Implementation”, Artech House, Norwood, MA-USA.

Curlander, JC, McDonough, RN (1991) “Synthetic Aperture Radar”, John Wiley

Elachi C (1988) “Spaceborne Radar Remote Sensing: Applications and Techniques”, IEEE Press.

Elachi, C, van Zyl, JJ (2006) “Introduction to the physics and techniques of remote sensing”, John Wiley & Sons. N.Y. 584 p. 2ª edició.

Emery, W, Camps, A (2017) "Introduction to Satellite Remote Sensing.

Atmosphere, Ocean, Land and Cryosphere Applications". Elsevier. 860 pàgs.

Janssen, MA (1993) “Atmospheric Remote Sensing by Microwave Radiometry”, John Wiley

Oliver, C, Quegan S. (2004), “Understanding Synthetic Aperture Radar Images”, SciTech Publishing.

Sharkov, EA (2003) “Passive Microwave Remote Sensing of the Earth. Physical Foundations”, Springer-Praxis

Skou, N, le Vine, DM (1989) “Microwave Radiometer Systems: Design & Analysis”, Artech House

Ulaby, FT, Elachi, C (1990) Radar Polarimetry for Geoscience Application

Ulaby, FT, Long, DG (Eds.) (2014), “Microwave Radar and Radiometric Remote Sensing”, Univ. Michigan Press.


Software

MiraMon, ArcGIS, QGIS, MATLAP, ENVI, R, SNAP, Office Microsoft

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
(PAULm) Classroom practices (master) 1 Catalan/Spanish first semester afternoon