Kleynhans, WOlivier, JCSalmon, BPWessels, Konrad JVan den Bergh, F2010-03-082010-03-082009-07Kleynhans 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 1-49781424433940http://hdl.handle.net/10204/3980IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Cape Town, South Africa, 12-17 July 2009It 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.enNDVIKalman FilterFast fourier transformMODIS dataRemote sensingGeosciencesConference PresentationKleynhans, W., Olivier, J., Salmon, B., Wessels, K. J., & Van den Bergh, F. (2009). Improving NDVI time series class separation using an extended Kalman filter. IEEE. http://hdl.handle.net/10204/3980Kleynhans, W, JC Olivier, BP Salmon, Konrad J Wessels, and F Van den Bergh. "Improving NDVI time series class separation using an extended Kalman filter." (2009): http://hdl.handle.net/10204/3980Kleynhans W, Olivier J, Salmon B, Wessels KJ, Van den Bergh F, Improving NDVI time series class separation using an extended Kalman filter; IEEE; 2009. http://hdl.handle.net/10204/3980 .TY - Conference Presentation AU - Kleynhans, W AU - Olivier, JC AU - Salmon, BP AU - Wessels, Konrad J AU - Van den Bergh, F AB - 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. DA - 2009-07 DB - ResearchSpace DP - CSIR KW - NDVI KW - Kalman Filter KW - Fast fourier transform KW - MODIS data KW - Remote sensing KW - Geosciences LK - https://researchspace.csir.co.za PY - 2009 SM - 9781424433940 T1 - Improving NDVI time series class separation using an extended Kalman filter TI - Improving NDVI time series class separation using an extended Kalman filter UR - http://hdl.handle.net/10204/3980 ER -