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Fourier series for analysis of temporal sequences of satellite sensor imagery

Author

Summary, in English

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.

Publishing year

1994

Language

English

Pages

3735-3741

Publication/Series

International Journal of Remote Sensing

Volume

15

Issue

18

Document type

Journal article

Publisher

Taylor & Francis

Topic

  • Physical Geography

Keywords

  • NDVI
  • growing seasons
  • time series analysis

Status

Published

Research group

  • remote sensing

ISBN/ISSN/Other

  • ISSN: 1366-5901