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Thesis / ROMDOC-THESIS-2016-597

Teledetecţia laser pentru caracterizarea mediilor acvatice

Vasilescu, Georgeta-Jeni
2010-02-04

Abstract: LASER REMOTE SENSING FOR WATER INVESTIGATION The ability of active remote sensing systems to sound ocean depths and aerosols at high altitudes in the atmosphere has opened an important domain of applied optics. Lidar (LIght Detection And Ranging) technique is an active remote sensing method, based on laser short pulses emission through the medium. The goal of this thesis is to reveal measurement/ processing procedures of fluorescence Lidar signals meant to sense organic compounds and pollutants inside aquatic ecosystem. Marine waters pollution investigation consists in evaluation of the state of main marine components (phytoplankton and dissolved organic matter) and early identification of pollutants presence, such as oil products. The physical phenomenon useful in this type of investigations is the induced fluorescence at the interaction between the laser beam and fluorescent water organic compounds. Laser induced fluorescence is an in situ non-contact method for assessing the composition, level of pollution or purity of the sample. The spectra of each pollutant compound leads to its isolation, identification and characterization, due to its fingerprint. This method was tested on this thesis in lab and in situ using fluorescence Lidar. The thesis contributes to implementation of laser remote sensing method for pollution level investigation on Romanian Black Sea coastal zone. The properties of river, marine and polluted waters, as well as rapid processing methods for fluorescence signals are discussed. The novelty of the thesis include: laser induced fluorescence and time resolved fluorescence measurements for water sample characterization for the first time in Romania and fluorescence Lidar technique used for in situ measurements of dissolved organic matter, pollutants and chlorophyll distributions along Romanian Black Sea coastal zone and harbors. The results reveal significant quantities of dissolved organic matter especially on coastal areas and different surfaces of hydrocarbon films. Artificial neural network, linear regression and channels relationship methods are evaluated in order to identify the best option for oil spills detection and characterization. It was found that linear regression or channels relationship are suitable to use in order to reveal the distribution of oils on a sea path while ANN is suitable for identifying the type of oils. The capabilities of Lidar system to detect highly polluted areas and to sense organic compounds relative distribution were demonstrated in connection with data processing method used.

Keyword(s): Teledetecţie laser -- Teză de doctorat ; Sisteme LIDAR (Teledetecţie) -- Teză de doctorat ; Mediu acvatic -- Teză de doctorat ; Poluarea apei -- Marea Neagră -- Teză de doctorat
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Record created 2016-11-07, last modified 2016-11-07

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