Optimal Estimate of Global Biome—Specific Parameter Settings to Reconstruct NDVI Time Series with the Harmonic ANalysis of Time Series (HANTS) Method

Terrestrial remote sensing data products retrieved from radiometric measurements in the optical and thermal infrared spectrum such as vegetation spectral indices can be heavily contaminated by atmospheric conditions, including cloud and aerosol layers. This contamination results in gaps or noisy obs...

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Autores principales:	Jie Zhou, Li Jia, Massimo Menenti, Xuan Liu
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	NDVI HANTS harmonic analysis gap-filling time series Science Q
Acceso en línea:	https://doaj.org/article/c0698d5b785d4c4fb5e434af0ddcd364
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spelling	oai:doaj.org-article:c0698d5b785d4c4fb5e434af0ddcd3642021-11-11T18:51:40ZOptimal Estimate of Global Biome—Specific Parameter Settings to Reconstruct NDVI Time Series with the Harmonic ANalysis of Time Series (HANTS) Method10.3390/rs132142512072-4292https://doaj.org/article/c0698d5b785d4c4fb5e434af0ddcd3642021-10-01T00:00:00Zhttps://www.mdpi.com/2072-4292/13/21/4251https://doaj.org/toc/2072-4292Terrestrial remote sensing data products retrieved from radiometric measurements in the optical and thermal infrared spectrum such as vegetation spectral indices can be heavily contaminated by atmospheric conditions, including cloud and aerosol layers. This contamination results in gaps or noisy observations. The harmonic analysis of time series (HANTS) has been widely used for time series reconstruction of remote sensing imagery in recent decades. To use HANTS model, a series of parameters, such as number of frequencies (NF), fitting error tolerance (FET), degree of over-determinedness (DoD), and regularization factor (Delta), need to be defined by users. These parameters provide flexibilities, but also make it difficult for non-expert users to determine appropriate settings for specific applications. This study systematically evaluated the reconstruction performance of the model under different parameter setting scenarios by simulating pixel-wise reference and noisy NDVI time series. The results of these numerical experiments were further used to identify optimal settings and improve global NDVI reconstruction performance. The results suggested optimal settings for different areas (local optimization). If a user opts to use unique settings for global reconstruction, the setting NF = 4, FET = 0.05, DoD = 5, and Delta = 0.5 can produce the best performance across all setting scenarios (global optimization). In addition, several internal improvements, such as dynamic weighting scheme, polynomial and inter-annual harmonic components, and ancillary attributes of input data can be used to further improve the performance of reconstruction. With these results, future non-expert users can easily determine appropriate settings of HANTS for specific applications in different regions.Jie ZhouLi JiaMassimo MenentiXuan LiuMDPI AGarticleNDVIHANTSharmonic analysisgap-fillingtime seriesScienceQENRemote Sensing, Vol 13, Iss 4251, p 4251 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	NDVI HANTS harmonic analysis gap-filling time series Science Q
spellingShingle	NDVI HANTS harmonic analysis gap-filling time series Science Q Jie Zhou Li Jia Massimo Menenti Xuan Liu Optimal Estimate of Global Biome—Specific Parameter Settings to Reconstruct NDVI Time Series with the Harmonic ANalysis of Time Series (HANTS) Method
description	Terrestrial remote sensing data products retrieved from radiometric measurements in the optical and thermal infrared spectrum such as vegetation spectral indices can be heavily contaminated by atmospheric conditions, including cloud and aerosol layers. This contamination results in gaps or noisy observations. The harmonic analysis of time series (HANTS) has been widely used for time series reconstruction of remote sensing imagery in recent decades. To use HANTS model, a series of parameters, such as number of frequencies (NF), fitting error tolerance (FET), degree of over-determinedness (DoD), and regularization factor (Delta), need to be defined by users. These parameters provide flexibilities, but also make it difficult for non-expert users to determine appropriate settings for specific applications. This study systematically evaluated the reconstruction performance of the model under different parameter setting scenarios by simulating pixel-wise reference and noisy NDVI time series. The results of these numerical experiments were further used to identify optimal settings and improve global NDVI reconstruction performance. The results suggested optimal settings for different areas (local optimization). If a user opts to use unique settings for global reconstruction, the setting NF = 4, FET = 0.05, DoD = 5, and Delta = 0.5 can produce the best performance across all setting scenarios (global optimization). In addition, several internal improvements, such as dynamic weighting scheme, polynomial and inter-annual harmonic components, and ancillary attributes of input data can be used to further improve the performance of reconstruction. With these results, future non-expert users can easily determine appropriate settings of HANTS for specific applications in different regions.
format	article
author	Jie Zhou Li Jia Massimo Menenti Xuan Liu
author_facet	Jie Zhou Li Jia Massimo Menenti Xuan Liu
author_sort	Jie Zhou
title	Optimal Estimate of Global Biome—Specific Parameter Settings to Reconstruct NDVI Time Series with the Harmonic ANalysis of Time Series (HANTS) Method
title_short	Optimal Estimate of Global Biome—Specific Parameter Settings to Reconstruct NDVI Time Series with the Harmonic ANalysis of Time Series (HANTS) Method
title_full	Optimal Estimate of Global Biome—Specific Parameter Settings to Reconstruct NDVI Time Series with the Harmonic ANalysis of Time Series (HANTS) Method
title_fullStr	Optimal Estimate of Global Biome—Specific Parameter Settings to Reconstruct NDVI Time Series with the Harmonic ANalysis of Time Series (HANTS) Method
title_full_unstemmed	Optimal Estimate of Global Biome—Specific Parameter Settings to Reconstruct NDVI Time Series with the Harmonic ANalysis of Time Series (HANTS) Method
title_sort	optimal estimate of global biome—specific parameter settings to reconstruct ndvi time series with the harmonic analysis of time series (hants) method
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/c0698d5b785d4c4fb5e434af0ddcd364
work_keys_str_mv	AT jiezhou optimalestimateofglobalbiomespecificparametersettingstoreconstructndvitimeserieswiththeharmonicanalysisoftimeserieshantsmethod AT lijia optimalestimateofglobalbiomespecificparametersettingstoreconstructndvitimeserieswiththeharmonicanalysisoftimeserieshantsmethod AT massimomenenti optimalestimateofglobalbiomespecificparametersettingstoreconstructndvitimeserieswiththeharmonicanalysisoftimeserieshantsmethod AT xuanliu optimalestimateofglobalbiomespecificparametersettingstoreconstructndvitimeserieswiththeharmonicanalysisoftimeserieshantsmethod
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Optimal Estimate of Global Biome—Specific Parameter Settings to Reconstruct NDVI Time Series with the Harmonic ANalysis of Time Series (HANTS) Method

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