Improved red-edge chlorophyll-a detection for Sentinel 2

Chlorophyll-a (chl-a) concentration is an indicator of algal biomass. The Sentinel 2 platform offers greatly improved spatial resolution over other satellite platforms designed for water based chl-a retrievals and includes a “red-edge” band at 704 nm not present on the Landsat 8 operational land ima...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	James Bramich, Christopher J.S. Bolch, Andrew Fischer
Formato:	article
Lenguaje:	EN
Publicado:	Elsevier 2021
Materias:	Remote sensing Chlorophyll-a Sentinel 2 MSI Red-edge Ecology QH540-549.5
Acceso en línea:	https://doaj.org/article/6e60ad27db5a4877bd2be224cd1af407
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:6e60ad27db5a4877bd2be224cd1af407
record_format	dspace
spelling	oai:doaj.org-article:6e60ad27db5a4877bd2be224cd1af4072021-12-01T04:28:09ZImproved red-edge chlorophyll-a detection for Sentinel 21470-160X10.1016/j.ecolind.2020.106876https://doaj.org/article/6e60ad27db5a4877bd2be224cd1af4072021-01-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S1470160X20308141https://doaj.org/toc/1470-160XChlorophyll-a (chl-a) concentration is an indicator of algal biomass. The Sentinel 2 platform offers greatly improved spatial resolution over other satellite platforms designed for water based chl-a retrievals and includes a “red-edge” band at 704 nm not present on the Landsat 8 operational land imager. This study provides validation of an improved version of a well known semi-analytical chl-a retrieval algorithm. The algorithm is provided with several free image processing utilities and the improved approach can be implemented with minimal technology skills. The improved performance is the result of replacing a fixed chl-a specific absorption coefficient (a) with a variable model. This method was applied to three Sentinel 2 images taken over the Lake Erie western basin correlating with an in-situ dataset of 24 samples where chl-a ranged from 1.89 mg m−3 to 70.20 mg m−3. The variable a model produced chl-a retrievals with normalised root mean squared error of prediction (NRMSEP) = 7.5%, bias = -0.47 mg m−3, coefficient of determination (R2) = 0.91 and Nash-Sutcliffe efficiency (NSE) = 0.90). This represented a 23% reduction in NRMSEP, an 85% reduction in bias and an increase in NSE of 7% over the default algorithm using a fixed a* value. Creation of chl-a retrieval algorithms that consider the variability in a* should result in algorithms that perform better against a wide range of chl-a concentrations and are less likely to require local recalibration. Obtaining accurate chl-a retrievals from a satellite platform with the spatial resolution of Sentinel 2 will allow satellite monitoring of many more inland waters than previously possible.James BramichChristopher J.S. BolchAndrew FischerElsevierarticleRemote sensingChlorophyll-aSentinel 2MSIRed-edgeEcologyQH540-549.5ENEcological Indicators, Vol 120, Iss , Pp 106876- (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Remote sensing Chlorophyll-a Sentinel 2 MSI Red-edge Ecology QH540-549.5
spellingShingle	Remote sensing Chlorophyll-a Sentinel 2 MSI Red-edge Ecology QH540-549.5 James Bramich Christopher J.S. Bolch Andrew Fischer Improved red-edge chlorophyll-a detection for Sentinel 2
description	Chlorophyll-a (chl-a) concentration is an indicator of algal biomass. The Sentinel 2 platform offers greatly improved spatial resolution over other satellite platforms designed for water based chl-a retrievals and includes a “red-edge” band at 704 nm not present on the Landsat 8 operational land imager. This study provides validation of an improved version of a well known semi-analytical chl-a retrieval algorithm. The algorithm is provided with several free image processing utilities and the improved approach can be implemented with minimal technology skills. The improved performance is the result of replacing a fixed chl-a specific absorption coefficient (a) with a variable model. This method was applied to three Sentinel 2 images taken over the Lake Erie western basin correlating with an in-situ dataset of 24 samples where chl-a ranged from 1.89 mg m−3 to 70.20 mg m−3. The variable a model produced chl-a retrievals with normalised root mean squared error of prediction (NRMSEP) = 7.5%, bias = -0.47 mg m−3, coefficient of determination (R2) = 0.91 and Nash-Sutcliffe efficiency (NSE) = 0.90). This represented a 23% reduction in NRMSEP, an 85% reduction in bias and an increase in NSE of 7% over the default algorithm using a fixed a* value. Creation of chl-a retrieval algorithms that consider the variability in a* should result in algorithms that perform better against a wide range of chl-a concentrations and are less likely to require local recalibration. Obtaining accurate chl-a retrievals from a satellite platform with the spatial resolution of Sentinel 2 will allow satellite monitoring of many more inland waters than previously possible.
format	article
author	James Bramich Christopher J.S. Bolch Andrew Fischer
author_facet	James Bramich Christopher J.S. Bolch Andrew Fischer
author_sort	James Bramich
title	Improved red-edge chlorophyll-a detection for Sentinel 2
title_short	Improved red-edge chlorophyll-a detection for Sentinel 2
title_full	Improved red-edge chlorophyll-a detection for Sentinel 2
title_fullStr	Improved red-edge chlorophyll-a detection for Sentinel 2
title_full_unstemmed	Improved red-edge chlorophyll-a detection for Sentinel 2
title_sort	improved red-edge chlorophyll-a detection for sentinel 2
publisher	Elsevier
publishDate	2021
url	https://doaj.org/article/6e60ad27db5a4877bd2be224cd1af407
work_keys_str_mv	AT jamesbramich improvedrededgechlorophylladetectionforsentinel2 AT christopherjsbolch improvedrededgechlorophylladetectionforsentinel2 AT andrewfischer improvedrededgechlorophylladetectionforsentinel2
_version_	1718405908722089984

Improved red-edge chlorophyll-a detection for Sentinel 2

Ejemplares similares