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Please use this identifier to cite or link to this item: http://hdl.handle.net/10204/3980

Title: Improving NDVI time series class separation using an extended Kalman filter
Authors: Kleynhans, W
Olivier, JC
Salmon, BP
Wessels, KJ
Van den Bergh, F
Keywords: NDVI
Kalman Filter
Fast fourier transform
MODIS data
Remote sensing
Geosciences
Issue Date: Jul-2009
Publisher: IEEE
Citation: Kleynhans W, Olivier JC, Salmon, BP, Wessels, KJ and Van den Berg, F. 2009. Improving NDVI time series class separation using an extended Kalman filter. IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Cape Town, South Africa, 12-17 July 2009, pp 1-4
Abstract: It is proposed that the NDVI time series derived from MODIS multitemporal remote sensing data can be modelled as a triply (mean, phase and amplitude) modulated cosine function. A non-linear Extended Kalman Filter was developed to estimate the parameters of the modulated cosine function as a function of time. It was shown that the maximum separability of the parameters for different vegetation land cover was better than that of a spectral method based on the Fast Fourier Transform (FFT). Thus it is theorized that the cosine function parameters estimated using the EKF is superior for both classifying land cover and detecting change over time when compared to methods based on the FFT. Results from two study areas in Southern Africa are provided to show the improved separability using MODIS data.
Description: IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Cape Town, South Africa, 12-17 July 2009
URI: http://hdl.handle.net/10204/3980
ISBN: 9781424433940
Appears in Collections:Radar and electronic warfare systems
Earth observation
General science, engineering & technology
Earth observation technologies

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