It is proposed that the NDVI time-series derived from MODIS satellite data can be modelled as a triply (mean, phase and amplitude) modulated cosine function. Secondly, a non-linear 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 (FFT) using data from two study areas in South Africa.
Reference:
Kleynhans, W, Olivier, JC et al 2009. Improving land cover class separation using an extended Kalman filter on MODIS NDVI time series data. IEEE Geoscience and Remote Sensing Letters, vol. 6 (4), pp 1-5
Kleynhans, W., Olivier JC, Wessels, K. J., Van Den Bergh F, Salmon BP, & Steenkamp Karen C (2009). Improving land cover class separation using an extended Kalman filter on MODIS NDVI time series data. http://hdl.handle.net/10204/4028
Kleynhans, W, Olivier JC, Konrad J Wessels, Van Den Bergh F, Salmon BP, and Steenkamp Karen C "Improving land cover class separation using an extended Kalman filter on MODIS NDVI time series data." (2009) http://hdl.handle.net/10204/4028
Kleynhans W, Olivier JC, Wessels KJ, Van Den Bergh F, Salmon BP, Steenkamp Karen C. Improving land cover class separation using an extended Kalman filter on MODIS NDVI time series data. 2009; http://hdl.handle.net/10204/4028.
Copyright: 2009 IEEE. This is the author's post print version of the work. It is posted here by permission of IEEE for your personal use. Not for redistribution. The definitive version has been published in IEEE, Geoscience and Remote Sensing Letters
ResearchSpace
