Fourier series for analysis of temporal sequences of satellite sensor imagery

Research output: Contribution to journalArticlepeer-review


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.
Original languageEnglish
Pages (from-to)3735-3741
JournalInternational Journal of Remote Sensing
Issue number18
Publication statusPublished - 1994

Subject classification (UKÄ)

  • Physical Geography

Free keywords

  • NDVI
  • growing seasons
  • time series analysis


Dive into the research topics of 'Fourier series for analysis of temporal sequences of satellite sensor imagery'. Together they form a unique fingerprint.

Cite this