气候变化领域集成服务门户(CCPortal): Optimizing and comparing gap-filling techniques using simulated NDVI time series from remotely sensed global data

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DOI	10.1016/j.jag.2018.11.008
	Optimizing and comparing gap-filling techniques using simulated NDVI time series from remotely sensed global data
	Julien Y.; Sobrino J.A.
发表日期	2019
ISSN	15698432
起始页码	93
结束页码	111
卷号	76
英文摘要	NDVI (Normalized Difference Vegetation Index) time series usually suffer from remaining cloud presence, even after data pre-processing. To address this issue, numerous gap-filling (or reconstruction) techniques have been developed in the literature, although their comparison has mainly been local to regional, with only two global studies to date, and has led to sometimes contradictory results. This study builds on these different comparisons, by testing different parameterizations for five NDVI temporal profile reconstruction techniques, namely HANTS (Harmonic Analysis of Time Series), IDR (iterative Interpolation for Data Reconstruction), Savitzky-Golay, Asymmetric Gaussian and Double Logistic, and then comparing them as generally parameterized, and then with the best of the tested parameterizations. These comparisons show that the HANTS reconstruction technique provides lower errors in cloud prone areas, while the IDR method works best with shorter cloud covers. However, the remaining errors in cloud prone areas are still high, and there is room for new reconstruction techniques. Although these results are only applicable to the range of the tested parameterizations, these latter have been chosen within widely used configurations, and should provide interested users with a better understanding of the different methods and the best parameterization for their needs, as well as an estimate of the expected error in the reconstruction of NDVI time series. © 2018 Elsevier B.V.
英文关键词	Benchmark; Multi-Temporal; Parameterization; Reconstruction methods; Vegetation index
语种	英语
scopus关键词	cloud cover; estimation method; NDVI; optimization; parameterization; reconstruction; remote sensing; time series
来源期刊	International Journal of Applied Earth Observation and Geoinformation
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/156520
作者单位	Global Change Unit, Image Processing Laboratory, University of Valencia, P.O. Box 22085, Valencia, E-46071, Spain
推荐引用方式 GB/T 7714	Julien Y.,Sobrino J.A.. Optimizing and comparing gap-filling techniques using simulated NDVI time series from remotely sensed global data[J],2019,76.
APA	Julien Y.,&Sobrino J.A..(2019).Optimizing and comparing gap-filling techniques using simulated NDVI time series from remotely sensed global data.International Journal of Applied Earth Observation and Geoinformation,76.
MLA	Julien Y.,et al."Optimizing and comparing gap-filling techniques using simulated NDVI time series from remotely sensed global data".International Journal of Applied Earth Observation and Geoinformation 76(2019).