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Improving land cover class separation using an extended Kalman filter on MODIS NDVI time-series data
journal contribution
posted on 2023-05-17, 17:42 authored by Kleynhans, W, Jan OlivierJan Olivier, Wessels, KJ, van den Bergh, F, Brian SalmonBrian Salmon, Steenkamp, KCIt 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.
History
Publication title
IEEE Geoscience and Remote Sensing LettersVolume
7Pagination
381-385ISSN
1545-598XDepartment/School
School of EngineeringPublisher
IEEEPlace of publication
United StatesRights statement
Copyright 2009 IEEERepository Status
- Restricted