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Improving land cover class separation using an extended Kalman filter on MODIS NDVI time-series data

Citation

Kleynhans, W and Olivier, JC and Wessels, KJ and van den Bergh, F and Salmon, BP and Steenkamp, KC, Improving land cover class separation using an extended Kalman filter on MODIS NDVI time-series data, IEEE Geoscience and Remote Sensing Letters, 7, (2) pp. 381-385. ISSN 1545-598X (2010) [Refereed Article]

Copyright Statement

Copyright 2009 IEEE

DOI: doi:10.1109/LGRS.2009.2036578

Abstract

It is proposed that the normalized difference vegetation index time series derived from Moderate Resolution Imaging Spectroradiometer satellite data can be modeled as a triply (mean, phase, and amplitude) modulated cosine function. Second, a nonlinear extended Kalman filter is developed to estimate the parameters of the modulated cosine function as a function of time. It is shown that the maximum separability of the parameters for natural vegetation and settlement land cover types is better than that of methods based on the fast Fourier transform using data from two study areas in South Africa.

Item Details

Item Type:Refereed Article
Keywords:Discrete Fourier transforms, Kalman filtering
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:84577
Year Published:2010
Web of Science® Times Cited:29
Deposited By:Engineering
Deposited On:2013-05-21
Last Modified:2015-02-08
Downloads:0

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