Fourier series for analysis of temporal sequences of satellite sensor imagery
(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)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/695050
- author
- Olsson, Lennart LU and Eklundh, Lars LU
- organization
- publishing date
- 1994
- 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
- 2016-04-04 07:38:25
- date last changed
- 2021-04-04 06:33:37
@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}}, keywords = {{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}}, doi = {{10.1080/01431169408954355}}, volume = {{15}}, year = {{1994}}, }