
Lars Eklundh
Professor

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.
Department/s
- LUCSUS (Lund University Centre for Sustainability Studies)
- Dept of Physical Geography and Ecosystem Science
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