? Quick Search: ? ? ? Advanced Search
FAN Chenqing,WANG Xiaochen,ZHANG Xudong,GAO Dong. 2019. A newly developed ocean significant wave height retrieval method from Envisat ASAR wave mode imagery. Acta Oceanologica Sinica, 38(9):120-127
A newly developed ocean significant wave height retrieval method from Envisat ASAR wave mode imagery
一种基于Envisat ASAR波模式数据的有效波高反演算法
Received:January 19, 2018??
DOI:10.1007/s13131-019-1480-2
Key words:significant wave height??Envisat ASAR??GA-PLS??optimal feature subset
中文关键词:??有效波高??Envisat ASAR??GA-PLS??最优特征子集
基金项目:The National Science Foundation for Young Scientists of China under contract No. 61501130; the National Key Research and Development Program of China under contract Nos 2016YFB0502504 and 2016YFB0502500; the National Natural Science Foundation of China under contract Nos 41431174, 61471358 and 41401427.
Author NameAffiliationE-mail
FAN Chenqing?First Institute of Oceanography, Ministry of Natural Resources, Qingdao 266061, China??
WANG Xiaochen?Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100190, China
Laboratory of Target Microwave Properties, Deqing Academy of Satellite Applications, Deqing 313200, China?
wangxc@aircas.ac.cn?
ZHANG Xudong?First Institute of Oceanography, Ministry of Natural Resources, Qingdao 266061, China
College of information and engineering, Ocean University of China, Qingdao 266071, China?
?
GAO Dong?First Institute of Oceanography, Ministry of Natural Resources, Qingdao 266061, China??
Hits:?20
Download times:?33
Abstract:
??????The main objective of this paper is to propose a newly developed ocean Significant Wave Height (SWH) retrieval method from Envisat Advanced Synthetic Aperture Radar (ASAR) imagery. A series of wave mode imagery from January, April and May of 2011 are collocated with ERA-Interim reanalysis SWH data. Based on the matched datasets, a simplified empirical relationship between 22 types of SAR imagery parameters and SWH products is developed with the Genetic Algorithms Partial Least-Squares (GA-PLS) model. Two major features of the backscattering coefficient σ0 and the frequency parameter S10 are chosen as the optimal training feature subset of SWH retrieval by using cross validation. In addition, we also present a comparison of the retrieval results of the simplified empirical relationship with the collocated ERA-Interim data. The results show that the assessment index of the correlation coefficient, the bias, the root-mean-square error of cross validation (RMSECV) and the scattering index (SI) are 0.78, 0.07 m, 0.76 m and 0.5, respectively. In addition, the comparison of the retrieved SWH data between our simplifying model and the Jason-2 radar altimeter data is proposed in our study. Moreover, we also make a comparison of the retrieval of SWH data between our developed model and the well-known CWAVE_ENV model. The results show that satisfying retrieval results are acquired in the low-moderate sea state, but major bias appears in the high sea state, especially for SWH>5 m.
中文摘要:
??????本文提出了一种基于的Envisat ASAR波模式数据的海浪有效波高反演算法。我们通过匹配2011年1月、4月、5月的波模式数据序列和ERA-Interim有效波高再分析数据,建立了22个图像参数和有效波高之前的经验关系。并利用基于遗传算法的最小二乘拟合模型,选取了22个图像参数中对反演结果影响较大的参数。通过交叉验证,我们发现后向散射系数σ0和频域参数S10对结果的影响最显着,因而将其作为本文海浪反演最有特征子集。进而,我们利用得到的最优特征子集建立的简化模型对海浪有效波高进行了反演,并与ERA-Interim有效波高再分析数据结果进行了比较,发现相关系数、偏差、均方根误差和散射系数分别为0.78,0.07米,0.76米和0.5。同样,我们也与高度计Jason-2和经典CWAVE_ENV结果进行了比较,结果表明:低海况下有效波高反演算法具有可靠的精度,但在高海况下并不理想。
HTML View Full Text ??View/Add Comment??Download reader
Close