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.