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Tesi etd-04112018-180705


Tipo di tesi
Tesi di laurea magistrale
Autore
ROSSI, FLAVIO
URN
etd-04112018-180705
Titolo
Hyperspectral Infrared Remote Sensing of gas plumes: modelling and simulation analysis
Dipartimento
INGEGNERIA DELL'INFORMAZIONE
Corso di studi
INGEGNERIA DELLE TELECOMUNICAZIONI
Relatori
relatore Prof. Diani, Marco
relatore Prof. Corsini, Giovanni
relatore Prof. Acito, Nicola
Parole chiave
  • Gas Plumes
  • hyperspectral sensors
  • LWIR
  • Remote Sensing
Data inizio appello
27/04/2018
Consultabilità
Non consultabile
Data di rilascio
27/04/2088
Riassunto
Gas plumes detection, identification and concentration estimation by using hyperspectral sensors in the long wave infrared spectral window, is an important task for many applications such as environmental monitoring and chemical warfare threat mitigation. Passive hyperspectral sensors based on radiance measure are well suited for gas recognition since they offer high-resolution data in the spectral region wherein each type of gas presents unique spectral features. The aim of this work is to study first a physical model, highlighting the analytical relationship among the radiometric quantities characterising the atmosphere, the gas plume and the at-sensor radiance. Two different applicative scenarios have been modelled: ground-to-ground slant observation and airborne vertical observation path. A software simulator has been developed. It can handle different radiometric parameters in order to recreate likely scenarios. Such parameters include a radiative transfer code to model the atmosphere, two databases of the gas spectral features and the background object emissivity, and a list of sensor peculiar parameters necessary to simulate the effect of a real sensor. All the radiometric quantities of interest are used together at the same time to obtain the simulated at-sensor radiance. The simulation methodology allows one to evaluate the performance of gas detection algorithm in terms of PD and PFA. In this work, an algorithm which assumes known the wavelength of the gas features is used to exemplify the method, but the methodology would remain valid also with other algorithms. In ground-to-ground scenario, the methodology includes the simulator, which implements the physical model using the peculiar gas and atmosphere parameters, followed by the algorithm by which the computation of performance indexes is achieved. The probability of detecting plume, for a given false alarm probability, has been obtained as a function of gas plume concentration. The analysis determines the minimum concentration of different gases necessary to reach a certain probability of detection. In airborne vertical path scenario, the procedure allows the inclusion of a simulated gas plume, with a certain structure, into an existing LWIR scene. The gas plume contribution has been shown in the spectral contrast image using HyTES sensor data.
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