A Preliminary Assessment of a Newly-Defined Multispectral Hue Space for Retrieving River Depth with Optical Imagery and In Situ Calibration Data

Bathymetry is a key element in the modeling of river systems for flood mapping, geomorphology, or stream habitat characterization. Standard practices rely on the interpolation of in situ depth measurements obtained with differential GPS or total station surveys, while more advanced techniques involv...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Nicolas Le Moine, Mounir Mahdade
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	bathymetry depth rivers multispectral hue spectral invariant directional statistics Science Q
Acceso en línea:	https://doaj.org/article/fd6b61279cdc4b9693cc3cfeca3d3bbc
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:fd6b61279cdc4b9693cc3cfeca3d3bbc
record_format	dspace
spelling	oai:doaj.org-article:fd6b61279cdc4b9693cc3cfeca3d3bbc2021-11-11T18:56:39ZA Preliminary Assessment of a Newly-Defined Multispectral Hue Space for Retrieving River Depth with Optical Imagery and In Situ Calibration Data10.3390/rs132144352072-4292https://doaj.org/article/fd6b61279cdc4b9693cc3cfeca3d3bbc2021-11-01T00:00:00Zhttps://www.mdpi.com/2072-4292/13/21/4435https://doaj.org/toc/2072-4292Bathymetry is a key element in the modeling of river systems for flood mapping, geomorphology, or stream habitat characterization. Standard practices rely on the interpolation of in situ depth measurements obtained with differential GPS or total station surveys, while more advanced techniques involve bathymetric LiDAR or acoustic soundings. However, these high-resolution active techniques are not so easily applied over large areas. Alternative methods using passive optical imagery present an interesting trade-off: they rely on the fact that wavelengths composing solar radiation are not attenuated at the same rates in water. Under certain assumptions, the logarithm of the ratio of radiances in two spectral bands is linearly correlated with depth. In this study, we go beyond these ratio methods in defining a multispectral hue that retains all spectral information. Given <i>n</i> coregistered bands, this spectral invariant lies on the <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mo stretchy="false">(</mo><mi>n</mi><mo>−</mo><mn>2</mn><mo stretchy="false">)</mo></mrow></semantics></math></inline-formula>-sphere embedded in <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msup><mi mathvariant="double-struck">R</mi><mrow><mi>n</mi><mo>−</mo><mn>1</mn></mrow></msup></semantics></math></inline-formula>, denoted <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msup><mi mathvariant="double-struck">S</mi><mrow><mi>n</mi><mo>−</mo><mn>2</mn></mrow></msup></semantics></math></inline-formula> and tagged ‘hue hypersphere’. It can be seen as a generalization of the RGB ‘color wheel’ (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msup><mi mathvariant="double-struck">S</mi><mn>1</mn></msup></semantics></math></inline-formula>) in higher dimensions. We use this mapping to identify a hue-depth relation in a 35 km reach of the Garonne River, using high resolution (0.50 m) airborne imagery in four bands and data from 120 surveyed cross-sections. The distribution of multispectral hue over river pixels is modeled as a mixture of two components: one component represents the distribution of substrate hue, while the other represents the distribution of ‘deep water’ hue; parameters are fitted such that membership probability for the ‘deep’ component correlates with depth.Nicolas Le MoineMounir MahdadeMDPI AGarticlebathymetrydepthriversmultispectral huespectral invariantdirectional statisticsScienceQENRemote Sensing, Vol 13, Iss 4435, p 4435 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	bathymetry depth rivers multispectral hue spectral invariant directional statistics Science Q
spellingShingle	bathymetry depth rivers multispectral hue spectral invariant directional statistics Science Q Nicolas Le Moine Mounir Mahdade A Preliminary Assessment of a Newly-Defined Multispectral Hue Space for Retrieving River Depth with Optical Imagery and In Situ Calibration Data
description	Bathymetry is a key element in the modeling of river systems for flood mapping, geomorphology, or stream habitat characterization. Standard practices rely on the interpolation of in situ depth measurements obtained with differential GPS or total station surveys, while more advanced techniques involve bathymetric LiDAR or acoustic soundings. However, these high-resolution active techniques are not so easily applied over large areas. Alternative methods using passive optical imagery present an interesting trade-off: they rely on the fact that wavelengths composing solar radiation are not attenuated at the same rates in water. Under certain assumptions, the logarithm of the ratio of radiances in two spectral bands is linearly correlated with depth. In this study, we go beyond these ratio methods in defining a multispectral hue that retains all spectral information. Given <i>n</i> coregistered bands, this spectral invariant lies on the <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mo stretchy="false">(</mo><mi>n</mi><mo>−</mo><mn>2</mn><mo stretchy="false">)</mo></mrow></semantics></math></inline-formula>-sphere embedded in <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msup><mi mathvariant="double-struck">R</mi><mrow><mi>n</mi><mo>−</mo><mn>1</mn></mrow></msup></semantics></math></inline-formula>, denoted <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msup><mi mathvariant="double-struck">S</mi><mrow><mi>n</mi><mo>−</mo><mn>2</mn></mrow></msup></semantics></math></inline-formula> and tagged ‘hue hypersphere’. It can be seen as a generalization of the RGB ‘color wheel’ (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msup><mi mathvariant="double-struck">S</mi><mn>1</mn></msup></semantics></math></inline-formula>) in higher dimensions. We use this mapping to identify a hue-depth relation in a 35 km reach of the Garonne River, using high resolution (0.50 m) airborne imagery in four bands and data from 120 surveyed cross-sections. The distribution of multispectral hue over river pixels is modeled as a mixture of two components: one component represents the distribution of substrate hue, while the other represents the distribution of ‘deep water’ hue; parameters are fitted such that membership probability for the ‘deep’ component correlates with depth.
format	article
author	Nicolas Le Moine Mounir Mahdade
author_facet	Nicolas Le Moine Mounir Mahdade
author_sort	Nicolas Le Moine
title	A Preliminary Assessment of a Newly-Defined Multispectral Hue Space for Retrieving River Depth with Optical Imagery and In Situ Calibration Data
title_short	A Preliminary Assessment of a Newly-Defined Multispectral Hue Space for Retrieving River Depth with Optical Imagery and In Situ Calibration Data
title_full	A Preliminary Assessment of a Newly-Defined Multispectral Hue Space for Retrieving River Depth with Optical Imagery and In Situ Calibration Data
title_fullStr	A Preliminary Assessment of a Newly-Defined Multispectral Hue Space for Retrieving River Depth with Optical Imagery and In Situ Calibration Data
title_full_unstemmed	A Preliminary Assessment of a Newly-Defined Multispectral Hue Space for Retrieving River Depth with Optical Imagery and In Situ Calibration Data
title_sort	preliminary assessment of a newly-defined multispectral hue space for retrieving river depth with optical imagery and in situ calibration data
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/fd6b61279cdc4b9693cc3cfeca3d3bbc
work_keys_str_mv	AT nicolaslemoine apreliminaryassessmentofanewlydefinedmultispectralhuespaceforretrievingriverdepthwithopticalimageryandinsitucalibrationdata AT mounirmahdade apreliminaryassessmentofanewlydefinedmultispectralhuespaceforretrievingriverdepthwithopticalimageryandinsitucalibrationdata AT nicolaslemoine preliminaryassessmentofanewlydefinedmultispectralhuespaceforretrievingriverdepthwithopticalimageryandinsitucalibrationdata AT mounirmahdade preliminaryassessmentofanewlydefinedmultispectralhuespaceforretrievingriverdepthwithopticalimageryandinsitucalibrationdata
_version_	1718431682557640704

A Preliminary Assessment of a Newly-Defined Multispectral Hue Space for Retrieving River Depth with Optical Imagery and In Situ Calibration Data

Ejemplares similares