Classification of Several Optically Complex Waters in China Using in Situ Remote Sensing Reflectance

	Classification of Several Optically Complex Waters in China Using in Situ Remote Sensing Reflectance
	Shen, Qian 1; Li, Junsheng 1; Zhang, Fangfang 1; Sun, Xu 1; Li, Jun 1; Li, Wei 1; Zhang, Bing 1
刊名	REMOTE SENSING
	2015
卷号	7 期号:11 页码:753-761
关键词	optically complex waters classification remote sensing reflectance inherent optical properties
通讯作者	Shen, Q (reprint author), Chinese Acad Sci, Inst Remote Sensing & Digital Earth, 9 Dengzhuang South Rd, Beijing 100094, Peoples R China.
英文摘要	Determining the dominant optically active substances in water bodies via classification can improve the accuracy of bio-optical and water quality parameters estimated by remote sensing. This study provides four robust centroid sets from in situ remote sensing reflectance (R-rs ()) data presenting typical optical types obtained by plugging different similarity measures into fuzzy c-means (FCM) clustering. Four typical types of waters were studied: (1) highly mixed eutrophic waters, with the proportion of absorption of colored dissolved organic matter (CDOM), phytoplankton, and non-living particulate matter at approximately 20%, 20%, and 60% respectively; (2) CDOM-dominated relatively clear waters, with approximately 45% by proportion of CDOM absorption; (3) nonliving solids-dominated waters, with approximately 88% by proportion of absorption of nonliving particulate matter; and (4) cyanobacteria-composed scum. We also simulated spectra from seven ocean color satellite sensors to assess their classification ability. POLarization and Directionality of the Earth's Reflectances (POLDER), Sentinel-2A, and MEdium Resolution Imaging Spectrometer (MERIS) were found to perform better than the rest. Further, a classification tree for MERIS, in which the characteristics of R-rs (709)/R-rs (681), R-rs (560)/R-rs (709), R-rs (560)/R-rs (620), and R-rs (709)/R-rs (761) are integrated, is also proposed in this paper. The overall accuracy and Kappa coefficient of the proposed classification tree are 76.2% and 0.632, respectively.
研究领域[WOS]	Remote Sensing
收录类别	SCI ; EI
语种	英语
WOS记录号	WOS:000366185200021
内容类型	期刊论文
源URL	[http://ir.ceode.ac.cn/handle/183411/38071]
专题	遥感与数字地球研究所_SCI/EI期刊论文_期刊论文
作者单位	1.[Shen, Qian 2.Li, Junsheng 3.Zhang, Fangfang 4.Sun, Xu 5.Zhang, Bing] Chinese Acad Sci, Inst Remote Sensing & Digital Earth, Beijing 100094, Peoples R China 6.[Li, Jun] Sun Yat Sen Univ, Sch Geog, Planning, Guangzhou 510275, Guangdong, Peoples R China 7.[Li, Wei] Beijing Univ Chem Technol, Coll Informat Sci & Technol, Beijing 100029, Peoples R China
推荐引用方式 GB/T 7714	Shen, Qian,Li, Junsheng,Zhang, Fangfang,et al. Classification of Several Optically Complex Waters in China Using in Situ Remote Sensing Reflectance[J]. REMOTE SENSING,2015,7(11):753-761.
APA	Shen, Qian.,Li, Junsheng.,Zhang, Fangfang.,Sun, Xu.,Li, Jun.,...&Zhang, Bing.(2015).Classification of Several Optically Complex Waters in China Using in Situ Remote Sensing Reflectance.REMOTE SENSING,7(11),753-761.
MLA	Shen, Qian,et al."Classification of Several Optically Complex Waters in China Using in Situ Remote Sensing Reflectance".REMOTE SENSING 7.11(2015):753-761.