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Improving NDVI time series class separation using an Extended Kalman Filter
Citation
Kleynhans, W and Olivier, JC and Salmon, BP and Wessels, KJ and van den Bergh, F, Improving NDVI time series class separation using an Extended Kalman Filter, Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 12-17 July 2009, Cape Town, South Africa, pp. 256-259. ISBN 978-1-4244-3395-7 (2009) [Refereed Conference Paper]
Copyright Statement
Copyright 2012 IEEE
DOI: doi:10.1109/IGARSS.2009.5417323
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.
Item Details
| Item Type: | Refereed Conference Paper |
|---|---|
| Keywords: | Extended Kalman Filter, Normalized Difference Vegetation Index, modulated cosine function |
| Research Division: | Engineering |
| Research Group: | Geomatic Engineering |
| Research Field: | Photogrammetry and Remote Sensing |
| Objective Division: | Expanding Knowledge |
| Objective Group: | Expanding Knowledge |
| Objective Field: | Expanding Knowledge in Engineering |
| Author: | Olivier, JC (Professor JC Olivier) |
| Author: | Salmon, BP (Dr Brian Salmon) |
| ID Code: | 84575 |
| Year Published: | 2009 |
| Deposited By: | Engineering |
| Deposited On: | 2013-05-21 |
| Last Modified: | 2014-12-11 |
| Downloads: | 0 |
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