Open AccessOil pollution discrimination by an inelastic hyperspectral Scheimpflug lidar system
Author(s) -
Fei Gao,
Jingwei Li,
Hongze Lin,
Sailing He
Publication year - 2017
Publication title -
optics express
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.394
H-Index - 271
ISSN - 1094-4087
DOI - 10.1364/oe.25.025515
Subject(s) - hyperspectral imaging , lidar , oil pollution , environmental science , pollution , principal component analysis , remote sensing , optics , scheimpflug principle , laser , materials science , physics , geology , computer science , environmental engineering , ecology , artificial intelligence , cornea , biology
An inelastic hyperspectral Scheimpflug lidar system is developed for range-resolved oil pollution detection and discrimination. A theory of system parametric design is built for aquatic circumstances, and laser-induced fluorescence spectra with an excitation wavelength of 446 nm are employed to detect oil pollution. Seven kinds of typical oil samples are tested and well distinguished using the principal component analysis (PCA) and linear discriminant analysis (LDA) methods. It has been shown that blue laser diodes (LD) have great potential for oil pollution detection, and our system could be further utilized for more applications in both marine and terrestrial environments.