Kleynhans, WSalmon, BPOlivier, JCVan den Bergh, FWessels, Konrad JGrobler, T2013-03-192013-03-192012-07Kleynhans, W, Salmon, BP, Olivier, JC, Van den Bergh, F, Wessels, KJ and Grobler, T. 2012. Detecting land cover change using a sliding window temporal autocorrelation approach. IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Munich, Germany, 22-27 July 2012http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6352552http://hdl.handle.net/10204/6578IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Munich, Germany, 22-27 July 2012. Published in IEEE XpolreThere has been recent developments in the use of hypertemporal satellite time series data for land cover change detection and classification. Recently, an Autocorrelation function (ACF) change detection method was proposed to detect the development of new human settlements in South Africa. In this paper, an extension to this change detection method is proposed that produces an estimate of the change date in addition to the change metric. Preliminary results indicate that comparable accuracy is achievable relative to the original formulation, with the added advantage of providing an estimate of the change date.enSatellite time series dataLand cover change detectionChange detection methodsConference PresentationKleynhans, W., Salmon, B., Olivier, J., Van den Bergh, F., Wessels, K. J., & Grobler, T. (2012). Detecting land cover change using a sliding window temporal autocorrelation approach. IEEE Xplore. http://hdl.handle.net/10204/6578Kleynhans, W, BP Salmon, JC Olivier, F Van den Bergh, Konrad J Wessels, and T Grobler. "Detecting land cover change using a sliding window temporal autocorrelation approach." (2012): http://hdl.handle.net/10204/6578Kleynhans W, Salmon B, Olivier J, Van den Bergh F, Wessels KJ, Grobler T, Detecting land cover change using a sliding window temporal autocorrelation approach; IEEE Xplore; 2012. http://hdl.handle.net/10204/6578 .TY - Conference Presentation AU - Kleynhans, W AU - Salmon, BP AU - Olivier, JC AU - Van den Bergh, F AU - Wessels, Konrad J AU - Grobler, T AB - There has been recent developments in the use of hypertemporal satellite time series data for land cover change detection and classification. Recently, an Autocorrelation function (ACF) change detection method was proposed to detect the development of new human settlements in South Africa. In this paper, an extension to this change detection method is proposed that produces an estimate of the change date in addition to the change metric. Preliminary results indicate that comparable accuracy is achievable relative to the original formulation, with the added advantage of providing an estimate of the change date. DA - 2012-07 DB - ResearchSpace DP - CSIR KW - Satellite time series data KW - Land cover change detection KW - Change detection methods LK - https://researchspace.csir.co.za PY - 2012 T1 - Detecting land cover change using a sliding window temporal autocorrelation approach TI - Detecting land cover change using a sliding window temporal autocorrelation approach UR - http://hdl.handle.net/10204/6578 ER -