A Meta-Analysis on Harmful Algal Bloom (HAB) Detection and Monitoring: A Remote Sensing Perspective

Algae serves as a food source for a wide range of aquatic species; however, a high concentration of inorganic nutrients under favorable conditions can result in the development of harmful algal blooms (HABs). Many studies have addressed HAB detection and monitoring; however, no global scale meta-ana...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Rabia Munsaf Khan, Bahram Salehi, Masoud Mahdianpari, Fariba Mohammadimanesh, Giorgos Mountrakis, Lindi J. Quackenbush
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	harmful algal blooms (HABs) meta-analysis phytoplankton remote sensing water quality Science Q
Acceso en línea:	https://doaj.org/article/db4bac565d084150926fcdb1fe2d315f
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:db4bac565d084150926fcdb1fe2d315f
record_format	dspace
spelling	oai:doaj.org-article:db4bac565d084150926fcdb1fe2d315f2021-11-11T18:54:26ZA Meta-Analysis on Harmful Algal Bloom (HAB) Detection and Monitoring: A Remote Sensing Perspective10.3390/rs132143472072-4292https://doaj.org/article/db4bac565d084150926fcdb1fe2d315f2021-10-01T00:00:00Zhttps://www.mdpi.com/2072-4292/13/21/4347https://doaj.org/toc/2072-4292Algae serves as a food source for a wide range of aquatic species; however, a high concentration of inorganic nutrients under favorable conditions can result in the development of harmful algal blooms (HABs). Many studies have addressed HAB detection and monitoring; however, no global scale meta-analysis has specifically explored remote sensing-based HAB monitoring. Therefore, this manuscript elucidates and visualizes spatiotemporal trends in HAB detection and monitoring using remote sensing methods and discusses future insights through a meta-analysis of 420 journal articles. The results indicate an increase in the quantity of published articles which have facilitated the analysis of sensors, software, and HAB proxy estimation methods. The comparison across multiple studies highlighted the need for a standardized reporting method for HAB proxy estimation. Research gaps include: (1) atmospheric correction methods, particularly for turbid waters, (2) the use of analytical-based models, (3) the application of machine learning algorithms, (4) the generation of harmonized virtual constellation and data fusion for increased spatial and temporal resolutions, and (5) the use of cloud-computing platforms for large scale HAB detection and monitoring. The planned hyperspectral satellites will aid in filling these gaps to some extent. Overall, this review provides a snapshot of spatiotemporal trends in HAB monitoring to assist in decision making for future studies.Rabia Munsaf KhanBahram SalehiMasoud MahdianpariFariba MohammadimaneshGiorgos MountrakisLindi J. QuackenbushMDPI AGarticleharmful algal blooms (HABs)meta-analysisphytoplanktonremote sensingwater qualityScienceQENRemote Sensing, Vol 13, Iss 4347, p 4347 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	harmful algal blooms (HABs) meta-analysis phytoplankton remote sensing water quality Science Q
spellingShingle	harmful algal blooms (HABs) meta-analysis phytoplankton remote sensing water quality Science Q Rabia Munsaf Khan Bahram Salehi Masoud Mahdianpari Fariba Mohammadimanesh Giorgos Mountrakis Lindi J. Quackenbush A Meta-Analysis on Harmful Algal Bloom (HAB) Detection and Monitoring: A Remote Sensing Perspective
description	Algae serves as a food source for a wide range of aquatic species; however, a high concentration of inorganic nutrients under favorable conditions can result in the development of harmful algal blooms (HABs). Many studies have addressed HAB detection and monitoring; however, no global scale meta-analysis has specifically explored remote sensing-based HAB monitoring. Therefore, this manuscript elucidates and visualizes spatiotemporal trends in HAB detection and monitoring using remote sensing methods and discusses future insights through a meta-analysis of 420 journal articles. The results indicate an increase in the quantity of published articles which have facilitated the analysis of sensors, software, and HAB proxy estimation methods. The comparison across multiple studies highlighted the need for a standardized reporting method for HAB proxy estimation. Research gaps include: (1) atmospheric correction methods, particularly for turbid waters, (2) the use of analytical-based models, (3) the application of machine learning algorithms, (4) the generation of harmonized virtual constellation and data fusion for increased spatial and temporal resolutions, and (5) the use of cloud-computing platforms for large scale HAB detection and monitoring. The planned hyperspectral satellites will aid in filling these gaps to some extent. Overall, this review provides a snapshot of spatiotemporal trends in HAB monitoring to assist in decision making for future studies.
format	article
author	Rabia Munsaf Khan Bahram Salehi Masoud Mahdianpari Fariba Mohammadimanesh Giorgos Mountrakis Lindi J. Quackenbush
author_facet	Rabia Munsaf Khan Bahram Salehi Masoud Mahdianpari Fariba Mohammadimanesh Giorgos Mountrakis Lindi J. Quackenbush
author_sort	Rabia Munsaf Khan
title	A Meta-Analysis on Harmful Algal Bloom (HAB) Detection and Monitoring: A Remote Sensing Perspective
title_short	A Meta-Analysis on Harmful Algal Bloom (HAB) Detection and Monitoring: A Remote Sensing Perspective
title_full	A Meta-Analysis on Harmful Algal Bloom (HAB) Detection and Monitoring: A Remote Sensing Perspective
title_fullStr	A Meta-Analysis on Harmful Algal Bloom (HAB) Detection and Monitoring: A Remote Sensing Perspective
title_full_unstemmed	A Meta-Analysis on Harmful Algal Bloom (HAB) Detection and Monitoring: A Remote Sensing Perspective
title_sort	meta-analysis on harmful algal bloom (hab) detection and monitoring: a remote sensing perspective
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/db4bac565d084150926fcdb1fe2d315f
work_keys_str_mv	AT rabiamunsafkhan ametaanalysisonharmfulalgalbloomhabdetectionandmonitoringaremotesensingperspective AT bahramsalehi ametaanalysisonharmfulalgalbloomhabdetectionandmonitoringaremotesensingperspective AT masoudmahdianpari ametaanalysisonharmfulalgalbloomhabdetectionandmonitoringaremotesensingperspective AT faribamohammadimanesh ametaanalysisonharmfulalgalbloomhabdetectionandmonitoringaremotesensingperspective AT giorgosmountrakis ametaanalysisonharmfulalgalbloomhabdetectionandmonitoringaremotesensingperspective AT lindijquackenbush ametaanalysisonharmfulalgalbloomhabdetectionandmonitoringaremotesensingperspective AT rabiamunsafkhan metaanalysisonharmfulalgalbloomhabdetectionandmonitoringaremotesensingperspective AT bahramsalehi metaanalysisonharmfulalgalbloomhabdetectionandmonitoringaremotesensingperspective AT masoudmahdianpari metaanalysisonharmfulalgalbloomhabdetectionandmonitoringaremotesensingperspective AT faribamohammadimanesh metaanalysisonharmfulalgalbloomhabdetectionandmonitoringaremotesensingperspective AT giorgosmountrakis metaanalysisonharmfulalgalbloomhabdetectionandmonitoringaremotesensingperspective AT lindijquackenbush metaanalysisonharmfulalgalbloomhabdetectionandmonitoringaremotesensingperspective
_version_	1718431674857947136

A Meta-Analysis on Harmful Algal Bloom (HAB) Detection and Monitoring: A Remote Sensing Perspective

Ejemplares similares