
Lars Eklundh
Professor

A simple method for reconstructing a high-quality NDVI time-series data set based on the Savitzky-Golay filter
Author
Summary, in English
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.
Department/s
- Atomic Physics
- Dept of Physical Geography and Ecosystem Science
Publishing year
2004
Language
English
Pages
332-344
Publication/Series
Remote Sensing of Environment
Volume
91
Issue
3-4
Full text
Document type
Journal article
Publisher
Elsevier
Topic
- Atom and Molecular Physics and Optics
- Physical Geography
Keywords
- time-series data set
- Savitzky-Golay filter
- NDVI
- SPOT vegetation
Status
Published
ISBN/ISSN/Other
- ISSN: 0034-4257