Advanced

A simple method for reconstructing a high-quality NDVI time-series data set based on the Savitzky-Golay filter

Chen, J; Jönsson, Per LU ; Tamura, M; Gu, ZH; Matsushita, B and Eklundh, Lars LU (2004) In Remote Sensing of Environment 91(3-4). p.332-344
Abstract
Although the Normalized Difference Vegetation Index (NDVI) time-series data, derived from NOAA/AVFIRR, SPOT/VEGETATION, TERRA or AQUA/MODIS, has been successfully used in research regarding global environmental change, residual noise in the NDVI time-series data, even after applying strict pre-processing, impedes further analysis and risks generating erroneous results. Based on the assumptions that NDVI time-series follow annual cycles of growth and decline of vegetation, and that clouds or poor atmospheric conditions usually depress NDVI values, we have developed in the present study a simple but robust method based on the Savitzky-Golay filter to smooth out noise in NDVI time-series, specifically that caused primarily by cloud... (More)
Although the Normalized Difference Vegetation Index (NDVI) time-series data, derived from NOAA/AVFIRR, SPOT/VEGETATION, TERRA or AQUA/MODIS, has been successfully used in research regarding global environmental change, residual noise in the NDVI time-series data, even after applying strict pre-processing, impedes further analysis and risks generating erroneous results. Based on the assumptions that NDVI time-series follow annual cycles of growth and decline of vegetation, and that clouds or poor atmospheric conditions usually depress NDVI values, we have developed in the present study a simple but robust method based on the Savitzky-Golay filter to smooth out noise in NDVI time-series, specifically that caused primarily by cloud contamination and atmospheric variability. Our method was developed to make data approach the upper NDVI envelope and to reflect the changes in NDVI patterns via an iteration process. From the results obtained by applying the newly developed method to a 10-day MVC SPOT VGT-S product, we provide optimized parameters for the new method and compare this technique with the BISE algorithm and Fourier-based fitting method. Our results indicate that the new method is more effective in obtaining high-quality NDVI time-series. (Less)
Please use this url to cite or link to this publication:
author
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
time-series data set, Savitzky-Golay filter, NDVI, SPOT vegetation
in
Remote Sensing of Environment
volume
91
issue
3-4
pages
332 - 344
publisher
Elsevier
external identifiers
  • wos:000222438300006
  • scopus:2942739366
ISSN
0034-4257
DOI
10.1016/j.rse.2004.03.014
language
English
LU publication?
yes
id
14c0ec57-4996-4b86-ba99-2a6c6ffe4adf (old id 273331)
date added to LUP
2007-08-02 11:25:07
date last changed
2017-12-10 03:46:16
@article{14c0ec57-4996-4b86-ba99-2a6c6ffe4adf,
  abstract     = {Although the Normalized Difference Vegetation Index (NDVI) time-series data, derived from NOAA/AVFIRR, SPOT/VEGETATION, TERRA or AQUA/MODIS, has been successfully used in research regarding global environmental change, residual noise in the NDVI time-series data, even after applying strict pre-processing, impedes further analysis and risks generating erroneous results. Based on the assumptions that NDVI time-series follow annual cycles of growth and decline of vegetation, and that clouds or poor atmospheric conditions usually depress NDVI values, we have developed in the present study a simple but robust method based on the Savitzky-Golay filter to smooth out noise in NDVI time-series, specifically that caused primarily by cloud contamination and atmospheric variability. Our method was developed to make data approach the upper NDVI envelope and to reflect the changes in NDVI patterns via an iteration process. From the results obtained by applying the newly developed method to a 10-day MVC SPOT VGT-S product, we provide optimized parameters for the new method and compare this technique with the BISE algorithm and Fourier-based fitting method. Our results indicate that the new method is more effective in obtaining high-quality NDVI time-series.},
  author       = {Chen, J and Jönsson, Per and Tamura, M and Gu, ZH and Matsushita, B and Eklundh, Lars},
  issn         = {0034-4257},
  keyword      = {time-series data set,Savitzky-Golay filter,NDVI,SPOT vegetation},
  language     = {eng},
  number       = {3-4},
  pages        = {332--344},
  publisher    = {Elsevier},
  series       = {Remote Sensing of Environment},
  title        = {A simple method for reconstructing a high-quality NDVI time-series data set based on the Savitzky-Golay filter},
  url          = {http://dx.doi.org/10.1016/j.rse.2004.03.014},
  volume       = {91},
  year         = {2004},
}