Remote sensing of cyanobacterial blooms in inland waters: present knowledge and future challenges

doi:10.1016/j.scib.2019.07.002

	Remote sensing of cyanobacterial blooms in inland waters: present knowledge and future challenges
	Shi, Kun 1,2,3; Zhang, Yunlin 2,3; Qin, Boqiang 2,3; Zhou, Botian 4
刊名	SCIENCE BULLETIN
	2019-10-30
卷号	64 期号:20 页码:1540-1556
关键词	Cyanobacterial blooms Inland waters Bio-optical properties Satellite MODIS
ISSN号	2095-9273
DOI	10.1016/j.scib.2019.07.002
通讯作者	Zhang, Yunlin(ylzhang@niglas.ac.cn)
英文摘要	Timely monitoring, detection and quantification of cyanobacterial blooms are especially important for controlling public health risks and understanding aquatic ecosystem dynamics. Due to the advantages of simultaneous data acquisition over large geographical areas and high temporal coverage, remote sensing strongly facilitates cyanobacterial bloom monitoring in inland waters. We provide a comprehensive review regarding cyanobacterial bloom remote sensing in inland waters including cyanobacterial optical characteristics, operational remote sensing algorithms of chlorophyll, phycocyanin and cyanobacterial bloom areas, and satellite imaging applications. We conclude that there have many significant progresses in the remote sensing algorithm of cyanobacterial pigments over the past 30 years. The band ratio algorithms in the red and near-infrared (NIR) spectral regions have great potential for the remote estimation of chlorophyll a in eutrophic and hypereutrophic inland waters, and the floating algae index (FAI) is the most widely used spectral index for detecting dense cyanobacterial blooms. Landsat, MODIS (Moderate Resolution Imaging Spectroradiometer) and MERIS (MEdium Resolution Imaging Spectrometer) are the most widely used products for monitoring the spatial and temporal dynamics of cyanobacteria in inland waters due to the appropriate temporal, spatial and spectral resolutions. Future work should primarily focus on the development of universal algorithms, remote retrievals of cyanobacterial blooms in olig-otrophic waters, and the algorithm applicability to mapping phycocyanin at a large spatial-temporal scale. The applications of satellite images will greatly improve our understanding of the driving mechanism of cyanobacterial blooms by combining numerical and ecosystem dynamics models. (C) 2019 Science China Press. Published by Elsevier B.V. and Science China Press. All rights reserved.
资助项目	National Science and Technology Major Project of China[2017ZX07203001] ; National Natural Science Foundation of China[41771472] ; National Natural Science Foundation of China[41621002] ; Youth Innovation Promotion Association of Chinese Academy of Sciences[2017365] ; Key Research Program of Frontier Sciences of Chinese Academy of Sciences[QYZDB-SSW-DQC016] ; Strategic Priority Research Program of Chinese Academy of Sciences[XDA19070301]
WOS研究方向	Science & Technology - Other Topics
语种	英语
出版者	ELSEVIER
WOS记录号	WOS:000493351100015
内容类型	期刊论文
源URL	[http://119.78.100.138/handle/2HOD01W0/10331]
专题	中国科学院重庆绿色智能技术研究院
通讯作者	Zhang, Yunlin
作者单位	1.Chinese Acad Sci, Ctr Excellence Tibetan Plateau Earth Sci, Beijing 100101, Peoples R China 2.Chinese Acad Sci, Nanjing Inst Geog & Mnol, Taihu Lab Lake Ecosyst Res, State Key Lab Lake Sci & Environm, Nanjing 210008, Jiangsu, Peoples R China 3.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 4.Chinese Acad Sci, Chongqing Inst Green & Intelligent Technol, Chongqing Key Lab Big Data & Intelligent Comp, Chongqing 400714, Peoples R China
推荐引用方式 GB/T 7714	Shi, Kun,Zhang, Yunlin,Qin, Boqiang,et al. Remote sensing of cyanobacterial blooms in inland waters: present knowledge and future challenges[J]. SCIENCE BULLETIN,2019,64(20):1540-1556.
APA	Shi, Kun,Zhang, Yunlin,Qin, Boqiang,&Zhou, Botian.(2019).Remote sensing of cyanobacterial blooms in inland waters: present knowledge and future challenges.SCIENCE BULLETIN,64(20),1540-1556.
MLA	Shi, Kun,et al."Remote sensing of cyanobacterial blooms in inland waters: present knowledge and future challenges".SCIENCE BULLETIN 64.20(2019):1540-1556.