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Please use this identifier to cite or link to this item: http://hdl.handle.net/10204/4590

Title: Automated land cover change detection: the quest for meaningful high temporal time series extraction
Authors: Salmon, BP
Olivier, JC
Kleynhans, W
Wessels, KJ
Van den Bergh, F
Keywords: Change detection
Clustering
Satellite
Time series
Land cover
Geoscience
Remote sensing
Issue Date: Jul-2010
Publisher: IEEE
Citation: Salmon, BP, Olivier, JC, Kleynhans, W et al. 2010. Automated land cover change detection: the quest for meaningful high temporal time series extraction. Proceedings of the 2010 IEEE International Geoscience and Remote Sensing Symposium, Honolulu, Hawaii, USA, 25-30 July 2010, pp 1-4
Series/Report no.: Conference Paper
Abstract: An automated land cover change detection method is proposed that uses coarse resolution hyper-temporal satellite time series data. The study compared two different unsupervised clustering approaches that operate on the short term Fourier transform coefficients of subsequences of 8-day composite MODerate-resolution Imaging Spectroradiometer (MODIS) surface reflectance data that were extracted with a temporal sliding window. The method uses a feature extraction process that creates meaningful sequential time series that can be analyzed and processed for change detection. The method was evaluated on real and simulated land cover change examples and obtained a change detection accuracy higher than 76% on real land cover conversion and more than 70% on simulated land cover conversion.
Description: Proceedings of the 2010 IEEE International Geoscience and Remote Sensing Symposium, Honolulu, Hawaii, USA, 25-30 July 2010
URI: http://hdl.handle.net/10204/4590
Appears in Collections:Mining and geoscience
Earth observation
General science, engineering & technology

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