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

Producción científica: Capítulo del libro › Contribución a congreso/conferencia › revisión exhaustiva

3 Citas (Scopus)

Resumen

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	Inglés
Título de la publicación alojada	2014 6th Workshop on Hyperspectral Image and Signal Processing
Subtítulo de la publicación alojada	Evolution in Remote Sensing, WHISPERS 2014
Editorial	IEEE Computer Society
ISBN (versión digital)	9781467390125
DOI	https://doi.org/10.1109/WHISPERS.2014.8077610
Estado	Publicada - 28 jun 2014
Publicado de forma externa	Sí
Evento	6th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, WHISPERS 2014 - Lausanne, Suiza Duración: 24 jun 2014 → 27 jun 2014

Serie de la publicación

Nombre	Workshop on Hyperspectral Image and Signal Processing, Evolution in Remote Sensing
Volumen	2014-June
ISSN (versión impresa)	2158-6276

Conferencia

Conferencia	6th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, WHISPERS 2014
País/Territorio	Suiza
Ciudad	Lausanne
Período	24/06/14 → 27/06/14

ODS de las Naciones Unidas

Este resultado contribuye a los siguientes Objetivos de Desarrollo Sostenible

ODS 14: Vida submarina

Acceder al documento

10.1109/WHISPERS.2014.8077610

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Enlace a la publicación en Scopus

Cómo citar

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. En 2014 6th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, WHISPERS 2014 Artículo 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,

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doi = "10.1109/WHISPERS.2014.8077610",

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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. En 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, Suiza, 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).

Producción científica: Capítulo del libro › Contribución a congreso/conferencia › revisión exhaustiva

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. En 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

Resumen

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