Wang, Yueqi1,2,3
; Gao, Zhiqiang1,2,3; Ning, Jicai1,2,3发表期刊REMOTE SENSING
2021-07-01
卷号13期号:14页码:14
关键词multi-year seasonal date seriesharmonic analysiscross-validationiterative piecewise fittingsea surface chlorophyll-a time series
DOI10.3390/rs13142727
通讯作者Ning, Jicai(jcning@yic.ac.cn)
英文摘要High-quality remotely sensed satellite data series are important for many ecological and environmental applications. Unfortunately, irregular spatiotemporal samples, frequent image gaps and inevitable observational biases can greatly hinder their application. As one of the most effective gap filling and noise reduction approaches, the harmonic analysis of time series (HANTS) method has been widely used to reconstruct geographical variables; however, when applied on multi-year time series over large spatial areas, the optimal harmonic formulas are generally varied in different locations or change across different years. The question of how to choose the optimal harmonic formula is still unanswered due to the deficiency of appropriate criteria. In this study, an adaptive piecewise harmonic analysis method (AP-HA) is proposed to reconstruct multi-year seasonal data series. The method introduces a cross-validation scheme to adaptively determine the optimal harmonic model and employs an iterative piecewise scheme to better track the local traits. Whenapplied to the satellite-derived sea surface chlorophyll-a time series over the Bohai and Yellow Seas of China, the AP-HA obtains reliable reconstruction results and outperforms the conventional HANTS methods, achieving improved accuracy. Due to its generic approach to filling missing observations and tracking detailed traits, the AP-HA method has a wide range of applications for other seasonal geographical variables.
资助机构National Natural Science Foundation of China; Open Fund of the CAS Key Laboratory of Marine Ecology and Environmental Sciences, Institute of Oceanology, Chinese Academy of Sciences
收录类别SCI
语种英语
关键词[WOS]OCEAN-COLOR; MISSING DATA; YELLOW SEAS; HIGH-ORDER; NDVI; SEAWIFS; PHENOLOGY; MODEL; MODIS; SEASONALITY
研究领域[WOS]Environmental Sciences & Ecology; Geology; Remote Sensing; Imaging Science & Photographic Technology
WOS记录号WOS:000677059800001
引用统计
文献类型期刊论文
条目标识符http://ir.yic.ac.cnhttp://ir.yic.ac.cn/handle/133337/29494
专题中科院海岸带环境过程与生态修复重点实验室_海岸带信息集成与战略规划研究中心
中科院海岸带环境过程与生态修复重点实验室
通讯作者Ning, Jicai作者单位1.Chinese Acad Sci, Yantai Inst Coastal Zone Res, CAS Key Lab Coastal Environm Proc & Ecol Remediat, Yantai 264003, Peoples R China
2.Chinese Acad Sci, Yantai Inst Coastal Zone Res, Shandong Key Lab Coastal Environm Proc, Yantai 264003, Peoples R China
3.Chinese Acad Sci, Ctr Ocean Megasci, Qingdao 266071, Peoples R China
推荐引用方式
GB/T 7714Wang, Yueqi,Gao, Zhiqiang,Ning, Jicai. An Adaptive Piecewise Harmonic Analysis Method for Reconstructing Multi-Year Sea Surface Chlorophyll-A Time Series[J]. REMOTE SENSING,2021,13(14):14.
APAWang, Yueqi,Gao, Zhiqiang,&Ning, Jicai.(2021).An Adaptive Piecewise Harmonic Analysis Method for Reconstructing Multi-Year Sea Surface Chlorophyll-A Time Series.REMOTE SENSING,13(14),14.
MLAWang, Yueqi,et al."An Adaptive Piecewise Harmonic Analysis Method for Reconstructing Multi-Year Sea Surface Chlorophyll-A Time Series".REMOTE SENSING 13.14(2021):14.
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