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Fourier series for analysis of temporal sequences of satellite sensor imagery

Olsson, Lennart LU and Eklundh, Lars LU (1994) In International Journal of Remote Sensing 15(18). p.3735-3741
Abstract
Fourier Series and the derivative were used in this study for analysing time series of remotely-sensed data. The technique allows fundamental characteristics of time series data to be quantified. In Fourier analysis a function in space or time is broken down into sinusoidal components, or harmonics. The first and second harmonics are a function of the mono or bi-modality of the curve, demonstrated in the study on Global Vegetation Index data classified into typical mono and bi-modal vegetation index zones. The last harmonic explains close to 100 per cent of the variance in the curve. Other important parameters of the time series, such as extreme points and rate of change, can be extracted from the derivative of the Fourier Series. Fourier... (More)
Fourier Series and the derivative were used in this study for analysing time series of remotely-sensed data. The technique allows fundamental characteristics of time series data to be quantified. In Fourier analysis a function in space or time is broken down into sinusoidal components, or harmonics. The first and second harmonics are a function of the mono or bi-modality of the curve, demonstrated in the study on Global Vegetation Index data classified into typical mono and bi-modal vegetation index zones. The last harmonic explains close to 100 per cent of the variance in the curve. Other important parameters of the time series, such as extreme points and rate of change, can be extracted from the derivative of the Fourier Series. Fourier Series may form a basis for a quantitative approach to the problem of handling temporal sequences of remotely-sensed data. (Less)
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author
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
NDVI, growing seasons, time series analysis
in
International Journal of Remote Sensing
volume
15
issue
18
pages
3735 - 3741
publisher
Taylor & Francis
external identifiers
  • scopus:0028584840
ISSN
1366-5901
DOI
10.1080/01431169408954355
language
English
LU publication?
yes
id
171f4241-59cf-4b7e-a7cc-ef7acf55ef9f (old id 695050)
date added to LUP
2007-12-17 10:31:48
date last changed
2017-04-09 04:28:47
@article{171f4241-59cf-4b7e-a7cc-ef7acf55ef9f,
  abstract     = {Fourier Series and the derivative were used in this study for analysing time series of remotely-sensed data. The technique allows fundamental characteristics of time series data to be quantified. In Fourier analysis a function in space or time is broken down into sinusoidal components, or harmonics. The first and second harmonics are a function of the mono or bi-modality of the curve, demonstrated in the study on Global Vegetation Index data classified into typical mono and bi-modal vegetation index zones. The last harmonic explains close to 100 per cent of the variance in the curve. Other important parameters of the time series, such as extreme points and rate of change, can be extracted from the derivative of the Fourier Series. Fourier Series may form a basis for a quantitative approach to the problem of handling temporal sequences of remotely-sensed data.},
  author       = {Olsson, Lennart and Eklundh, Lars},
  issn         = {1366-5901},
  keyword      = {NDVI,growing seasons,time series analysis},
  language     = {eng},
  number       = {18},
  pages        = {3735--3741},
  publisher    = {Taylor & Francis},
  series       = {International Journal of Remote Sensing},
  title        = {Fourier series for analysis of temporal sequences of satellite sensor imagery},
  url          = {http://dx.doi.org/10.1080/01431169408954355},
  volume       = {15},
  year         = {1994},
}