Detecting land cover change by evaluating the internal covariance matrix of the extended Kalman filter

Salmon, BPKleynhans, WVan den Bergh, FOlivier, JCWessels, Konrad J2013-02-252013-02-252012-07Salmon, BP, Kleynhans, W, Van den Bergh, F, Olivier, JC and Wessels, KJ. 2012. Detecting land cover change by evaluating the internal covariance matrix of the extended Kalman filter. In: IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Munich, Germany, 22-27 July 2012http://ieeexplore.ieee.org/xpl/articleDetails.jsp?reload=true&arnumber=6352676&contentType=Conference+Publicationshttp://hdl.handle.net/10204/6569IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Munich, Germany, 22-27 July 2012In this paper, the internal operations of an Extended Kalman Filter is investigated to see if any useful information can be derived to detect land cover change in a MODIS time series. The Extended Kalman Filter expands its internal covariance if a significant change in reflectance value is observed, followed by adapting the state parameters to compensate for this change. The analysis shows a change detection accuracy above 90% can be attained when evaluating the elements within the internal covariance matrix to detect new human settlements, with a corresponding false alarm rate below 11%.enChange detection algorithmsCovariance matrixKalman FilterSpatial informationTime series analysisDetecting land cover change by evaluating the internal covariance matrix of the extended Kalman filterConference PresentationSalmon, B., Kleynhans, W., Van den Bergh, F., Olivier, J., & Wessels, K. J. (2012). Detecting land cover change by evaluating the internal covariance matrix of the extended Kalman filter. IEEE Xplore. http://hdl.handle.net/10204/6569Salmon, BP, W Kleynhans, F Van den Bergh, JC Olivier, and Konrad J Wessels. "Detecting land cover change by evaluating the internal covariance matrix of the extended Kalman filter." (2012): http://hdl.handle.net/10204/6569Salmon B, Kleynhans W, Van den Bergh F, Olivier J, Wessels KJ, Detecting land cover change by evaluating the internal covariance matrix of the extended Kalman filter; IEEE Xplore; 2012. http://hdl.handle.net/10204/6569 .TY - Conference Presentation AU - Salmon, BP AU - Kleynhans, W AU - Van den Bergh, F AU - Olivier, JC AU - Wessels, Konrad J AB - In this paper, the internal operations of an Extended Kalman Filter is investigated to see if any useful information can be derived to detect land cover change in a MODIS time series. The Extended Kalman Filter expands its internal covariance if a significant change in reflectance value is observed, followed by adapting the state parameters to compensate for this change. The analysis shows a change detection accuracy above 90% can be attained when evaluating the elements within the internal covariance matrix to detect new human settlements, with a corresponding false alarm rate below 11%. DA - 2012-07 DB - ResearchSpace DP - CSIR KW - Change detection algorithms KW - Covariance matrix KW - Kalman Filter KW - Spatial information KW - Time series analysis LK - https://researchspace.csir.co.za PY - 2012 T1 - Detecting land cover change by evaluating the internal covariance matrix of the extended Kalman filter TI - Detecting land cover change by evaluating the internal covariance matrix of the extended Kalman filter UR - http://hdl.handle.net/10204/6569 ER -