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 (ERT) – Estimate of the surface temperature.
Description of the General Split Window Technique, using the thermal emission
for estimating the sub-surface characteristics. Exercises:. 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.