Hyperspectral characterization of marine particles based on MIE-LORENTZ and T-matrix codes and a genetic algorithm

A. M. Sánchez; E. Zafra; J. Piera

doi:10.1109/WHISPERS.2014.8077610

Hyperspectral characterization of marine particles based on MIE-LORENTZ and T-matrix codes and a genetic algorithm

A. M. Sánchez
, E. Zafra
, J. Piera

Producció científica: Capítol de llibre › Contribució a congrés/conferència › Avaluat per experts

3 Cites (Scopus)

Resum

Particle modeling is usually exploited, along with measured data, to infer the water content. However, the particle properties must be accurately known. In this paper, a methodology to estimate the hyperspectral complex-refractive-index signatures of marine particles is presented. It is is based on the Mie-Lorentz and T-matrix characterizations to obtain the particle inherent optical properties and uses a genetic algorithm for search optimization. This methodology is tested by accurately estimating the hyperspectral complex refractive indexes on two different examples, including monodisperse and polydisperse particle size distributions of spherical and non-spherical particles.

Idioma original	Anglès
Títol de la publicació	2014 6th Workshop on Hyperspectral Image and Signal Processing
Subtítol de la publicació	Evolution in Remote Sensing, WHISPERS 2014
Editor	IEEE Computer Society
ISBN (electrònic)	9781467390125
DOIs	https://doi.org/10.1109/WHISPERS.2014.8077610
Estat de la publicació	Publicada - 28 de juny 2014
Publicat externament	Sí
Esdeveniment	6th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, WHISPERS 2014 - Lausanne, Switzerland Durada: 24 de juny 2014 → 27 de juny 2014

Sèrie de publicacions

Nom	Workshop on Hyperspectral Image and Signal Processing, Evolution in Remote Sensing
Volum	2014-June
ISSN (imprès)	2158-6276

Conferència

Conferència	6th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, WHISPERS 2014
País/Territori	Switzerland
Ciutat	Lausanne
Període	24/06/14 → 27/06/14

SDG de les Nacions Unides

Aquest resultat contribueix als següents objectius de desenvolupament sostenible.

ODS 14 Vida submarina

Accés al document

10.1109/WHISPERS.2014.8077610

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Sánchez, A. M., Zafra, E., & Piera, J. (2014). Hyperspectral characterization of marine particles based on MIE-LORENTZ and T-matrix codes and a genetic algorithm. In 2014 6th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, WHISPERS 2014 Article 8077610 (Workshop on Hyperspectral Image and Signal Processing, Evolution in Remote Sensing; Vol. 2014-June). IEEE Computer Society. https://doi.org/10.1109/WHISPERS.2014.8077610

Sánchez, A. M. ; Zafra, E. ; Piera, J. / Hyperspectral characterization of marine particles based on MIE-LORENTZ and T-matrix codes and a genetic algorithm. 2014 6th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, WHISPERS 2014. IEEE Computer Society, 2014. (Workshop on Hyperspectral Image and Signal Processing, Evolution in Remote Sensing).

@inproceedings{d697c33715f7405d97ee60dc0691f26b,

title = "Hyperspectral characterization of marine particles based on MIE-LORENTZ and T-matrix codes and a genetic algorithm",

abstract = "Particle modeling is usually exploited, along with measured data, to infer the water content. However, the particle properties must be accurately known. In this paper, a methodology to estimate the hyperspectral complex-refractive-index signatures of marine particles is presented. It is is based on the Mie-Lorentz and T-matrix characterizations to obtain the particle inherent optical properties and uses a genetic algorithm for search optimization. This methodology is tested by accurately estimating the hyperspectral complex refractive indexes on two different examples, including monodisperse and polydisperse particle size distributions of spherical and non-spherical particles.",

keywords = "Genetic algorithm, microplastics, Mie-Lorentz, particle modeling, phytoplankton, T-matrix",

author = "S{\'a}nchez, \{A. M.\} and E. Zafra and J. Piera",

note = "Publisher Copyright: {\textcopyright} 2014 IEEE.; 6th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, WHISPERS 2014 ; Conference date: 24-06-2014 Through 27-06-2014",

year = "2014",

month = jun,

day = "28",

doi = "10.1109/WHISPERS.2014.8077610",

language = "English",

series = "Workshop on Hyperspectral Image and Signal Processing, Evolution in Remote Sensing",

publisher = "IEEE Computer Society",

booktitle = "2014 6th Workshop on Hyperspectral Image and Signal Processing",

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}

Sánchez, AM, Zafra, E & Piera, J 2014, Hyperspectral characterization of marine particles based on MIE-LORENTZ and T-matrix codes and a genetic algorithm. in 2014 6th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, WHISPERS 2014., 8077610, Workshop on Hyperspectral Image and Signal Processing, Evolution in Remote Sensing, vol. 2014-June, IEEE Computer Society, 6th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, WHISPERS 2014, Lausanne, Switzerland, 24/06/14. https://doi.org/10.1109/WHISPERS.2014.8077610

Hyperspectral characterization of marine particles based on MIE-LORENTZ and T-matrix codes and a genetic algorithm. / Sánchez, A. M.; Zafra, E.; Piera, J.
2014 6th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, WHISPERS 2014. IEEE Computer Society, 2014. 8077610 (Workshop on Hyperspectral Image and Signal Processing, Evolution in Remote Sensing; Vol. 2014-June).

Producció científica: Capítol de llibre › Contribució a congrés/conferència › Avaluat per experts

TY - GEN

T1 - Hyperspectral characterization of marine particles based on MIE-LORENTZ and T-matrix codes and a genetic algorithm

AU - Sánchez, A. M.

AU - Zafra, E.

AU - Piera, J.

PY - 2014/6/28

Y1 - 2014/6/28

N2 - Particle modeling is usually exploited, along with measured data, to infer the water content. However, the particle properties must be accurately known. In this paper, a methodology to estimate the hyperspectral complex-refractive-index signatures of marine particles is presented. It is is based on the Mie-Lorentz and T-matrix characterizations to obtain the particle inherent optical properties and uses a genetic algorithm for search optimization. This methodology is tested by accurately estimating the hyperspectral complex refractive indexes on two different examples, including monodisperse and polydisperse particle size distributions of spherical and non-spherical particles.

AB - Particle modeling is usually exploited, along with measured data, to infer the water content. However, the particle properties must be accurately known. In this paper, a methodology to estimate the hyperspectral complex-refractive-index signatures of marine particles is presented. It is is based on the Mie-Lorentz and T-matrix characterizations to obtain the particle inherent optical properties and uses a genetic algorithm for search optimization. This methodology is tested by accurately estimating the hyperspectral complex refractive indexes on two different examples, including monodisperse and polydisperse particle size distributions of spherical and non-spherical particles.

KW - Genetic algorithm

KW - microplastics

KW - Mie-Lorentz

KW - particle modeling

KW - phytoplankton

KW - T-matrix

UR - https://www.scopus.com/pages/publications/85038600093

U2 - 10.1109/WHISPERS.2014.8077610

DO - 10.1109/WHISPERS.2014.8077610

M3 - Conference contribution

AN - SCOPUS:85038600093

T3 - Workshop on Hyperspectral Image and Signal Processing, Evolution in Remote Sensing

BT - 2014 6th Workshop on Hyperspectral Image and Signal Processing

PB - IEEE Computer Society

T2 - 6th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, WHISPERS 2014

Y2 - 24 June 2014 through 27 June 2014

ER -

Sánchez AM, Zafra E, Piera J. Hyperspectral characterization of marine particles based on MIE-LORENTZ and T-matrix codes and a genetic algorithm. In 2014 6th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, WHISPERS 2014. IEEE Computer Society. 2014. 8077610. (Workshop on Hyperspectral Image and Signal Processing, Evolution in Remote Sensing). doi: 10.1109/WHISPERS.2014.8077610

Hyperspectral characterization of marine particles based on MIE-LORENTZ and T-matrix codes and a genetic algorithm

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