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2025-2026 / GEOL1051-1

Geological imaging and remote sensing

Duration

26h Th, 26h Pr, 30h Proj.

Number of credits

 Master MSc. in Geological and Mining Engineering, professional focus in environmental and geological engineering5 crédits 
 Master MSc. in Geological and Mining Engineering, professional focus in environmental and geological engineering (Co-diplomation avec l'Université polytechnique de Madrid)5 crédits 
 Master MSc. in Geological and Mining Engineering focus in mineral resources and recycling5 crédits 
 Master MSc. in Geological and Mining Engineering focus in mineral resources and recycling (Co-diplomation avec l'Université polytechnique de Madrid)5 crédits 

Lecturer

Eric Pirard

Language(s) of instruction

English 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

  • Introduction to Image Analysis and Stereology / The importance of vision in geosciences
  • From minerals to roxels : basic principles of scientific imaging in geosciences. Image calibration From analog to digital images Digital image file formats
  • Physics of Remote Sensing : Sources of electromagnetic radiation Atmospheric corrections, calibration methods Spectral properties of minerals, rocks and soils VNIR and SWIR ranges Multispectral, superspectral and hyperspectral remote sensing
  • Technologies for Core-Scanning
  • Technology of Earth Observation: Airborne and spaceborne platforms and sensors. Available systems (Landsat TM and ETM+, SPOT 3-4-5, ASTER, IKONOS, QuickBird, Sentinel, HyMap)
  • Image Processing: Image processing operations (global vs. local) Linear filters (low-pass, hi-pass, gradients) Mathematical Morphology (erosion, dilation, opening, closing)
  • Image analysis and processing, optical VNIR SWIR and thermal domains. Preprocessing. Geometric corrections, georeferencing. Radiometric correction, calibrations, atmospheric corrections Multispectral data processing. Data fusion, image sharpening Band ratios, indexes
  • Spectral Image Classification: Data transforms: principal components analysis, spectral classification techniques
  • Quantitative mineralogical and textural analysis: Modal (phase) and porosity analysis. Blob analysis: particle size and shape analysis. Texture indices

Learning outcomes of the learning unit

This course contributes to the learning outcomes I.2, I.3, II.2, III.1, IV.3, VII.4, VII.5 of the MSc in geological and mining engineering.

Prerequisite knowledge and skills

Planned learning activities and teaching methods

Mode of delivery (face to face, distance learning, hybrid learning)

Course materials and recommended or required readings

Work placement(s)

Organisational remarks and main changes to the course

Contacts

Association of one or more MOOCs