Cap. 1 - Generalities on the remote sensing and physics principles. Introduction, remote sensing system, Properties of
the electromagnetic radiations, source of the electromagnetic radiation, Interaction with matter, remote sensing
indicators, Interaction of the electromagnetic radiation and the terrestrial atmosphere – – Equation of the radiative
transport (RTE) – Estimate of the surface temperature. Description of the General Split Window Technique, using the
thermal emission for estimating the sub-surface characteristics. Appendices: A – Beer law, scattering, absorption bands,
refraction, surface backscattering, B – Description of the General Split Window Technique, C – Using the thermal
emission for estimating the sub-surface characteristics. Exercises: Software PclnWin e PCModWin.
Cap. 2 - Remote sensing sensors. Photographic & electro-optical sensors. Micro-wave systems (active and passive),
Lidar. Calibration techniques.
Cap. 3 – The remote sensing and the space environment. The terrestrial upper-atmosphere – the San Marco satellites
data. The Space Debris – Techniques for the observation and monitoring. The atmosphere of the outer planets (Mercury,
Venus, Mars, the giant planets).
Cap. 4 – Principle of remote sensing of the terrestrial atmosphere. Atmosphere sounding. Satellite based measurement
of the atmospheric ozone. Occultation techniques with active systems.
Cap. 5 – Remote sensing orbits. Orbit properties. Orbit perturbations. The requirements of the orbits for remote sensing.
Ground tracks. Remote sensing satellite constellations. Exercises: Software STK, Matlab Orbital Mechanics.
Remote sensing systems (Landsat, SPOT, NOAA, Sentinel, MSG). Appendices: A – Drift of the orbit operational
parameters, B – Computation of the acquisition times at the ground station, C – Design of an orbit crossing a given
station at a given crossing time. Tutorial: Software STK, Matlab Orbital Mechanics.
Cap. 6 – Acquisition systems and satellite images pre-processing. Ground receiving station, Image re-construction,
enhancement and information extraction. Image registration. Map projection. Appendices: A - pixel Geo-location, B –
Statistical analysis and enhancement of the images (Discrete Fourier Transform applied to the images, Wavelet,
Principal Components, Maximum auto-correlation factors, MAF). Tutorial: Software ENVI, MATLAB Image
Processing tool.
Cap. 7 – Theory and practices of image processing. Selection of the classification algorithms (Unsupervised and
Supervised classification). Topographic models. Image registration (Ground Control Points, Mutual Information,
invariant moments, contour matching). Change detection (algebraic methods, Multivariational Alteration Detection,
MAD). Introduction to the processing of hyperspectral images (Modeling the measurements, linear un-mixing, pure
pixels). Object recognition (Mathematic Morphology, Hough Transform). Tutorial: Software ENVI, Arcview, Image
Processing tool di MATLAB.
Cap. 8 – Project of a Remote Sensing Sensor.
