Estimating significant wave height from SAR imagery based on an SVM regression model

doi:10.1007/s13131-018-1203-7

	Estimating significant wave height from SAR imagery based on an SVM regression model
	Gao, Dong 1,2; Liu, Yongxin 1; Meng, Junmin 2; Jia, Yongjun 3; Fan, Chenqing 2
刊名	ACTA OCEANOLOGICA SINICA
	2018-03
卷号	37 期号:3 页码:103-110
关键词	advanced synthetic aperture radar wave mode support vector machine significant wave height
ISSN号	0253-505X
DOI	10.1007/s13131-018-1203-7
英文摘要	A new method for estimating significant wave height (SWH) from advanced synthetic aperture radar (ASAR) wave mode data based on a support vector machine (SVM) regression model is presented. The model is established based on a nonlinear relationship between sigma (0), the variance of the normalized SAR image, SAR image spectrum spectral decomposition parameters and ocean wave SWH. The feature parameters of the SAR images are the input parameters of the SVM regression model, and the SWH provided by the European Centre for Medium-range Weather Forecasts (ECMWF) is the output parameter. On the basis of ASAR matching data set, a particle swarm optimization (PSO) algorithm is used to optimize the input kernel parameters of the SVM regression model and to establish the SVM model. The SWH estimation results yielded by this model are compared with the ECMWF reanalysis data and the buoy data. The RMSE values of the SWH are 0.34 and 0.48 m, and the correlation coefficient is 0.94 and 0.81, respectively. The results show that the SVM regression model is an effective method for estimating the SWH from the SAR data. The advantage of this model is that SAR data may serve as an independent data source for retrieving the SWH, which can avoid the complicated solution process associated with wave spectra.
资助项目	Natural Science Foundation of China[41406207]
WOS关键词	OCEAN ; ALGORITHM ; SPECTRA
WOS研究方向	Oceanography
语种	英语
出版者	SPRINGER
WOS记录号	WOS:000427248000013
内容类型	期刊论文
源URL	[http://ir.fio.com.cn:8080/handle/2SI8HI0U/26948]
专题	自然资源部第一海洋研究所
通讯作者	Fan, Chenqing
作者单位	1.Inner Mongolia Univ, Coll Elect & Informat Engn, Hohhot 010020, Peoples R China 2.State Ocean Adm, Inst Oceanog 1, Qingdao 266061, Peoples R China 3.State Ocean Adm, Natl Satellite Ocean Applicat Serv, Beijing 100081, Peoples R China
推荐引用方式 GB/T 7714	Gao, Dong,Liu, Yongxin,Meng, Junmin,et al. Estimating significant wave height from SAR imagery based on an SVM regression model[J]. ACTA OCEANOLOGICA SINICA,2018,37(3):103-110.
APA	Gao, Dong,Liu, Yongxin,Meng, Junmin,Jia, Yongjun,&Fan, Chenqing.(2018).Estimating significant wave height from SAR imagery based on an SVM regression model.ACTA OCEANOLOGICA SINICA,37(3),103-110.
MLA	Gao, Dong,et al."Estimating significant wave height from SAR imagery based on an SVM regression model".ACTA OCEANOLOGICA SINICA 37.3(2018):103-110.