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Automated land cover change detection: the quest for meaningful high temporal time series extraction


Salmon, BP and Olivier, JC and Kleynhans, W and Wessels, KJ and van den Bergh, F, Automated land cover change detection: the quest for meaningful high temporal time series extraction, IEEE International Geoscience and Remote Sensing Symposium, 25-30 July 2010, Hawaii, USA, pp. 1968 - 1971. ISBN 978-1-4244-9564-1 (2010) [Refereed Conference Paper]

Copyright Statement

Copyright 2012 IEEE

DOI: doi:10.1109/IGARSS.2010.5653723


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.

Item Details

Item Type:Refereed Conference Paper
Keywords:Change detection, clustering, satellite, time series
Research Division:Engineering
Research Group:Geomatic engineering
Research Field:Photogrammetry and remote sensing
Objective Division:Expanding Knowledge
Objective Group:Expanding knowledge
Objective Field:Expanding knowledge in engineering
UTAS Author:Salmon, BP (Dr Brian Salmon)
UTAS Author:Olivier, JC (Professor JC Olivier)
ID Code:84582
Year Published:2010
Web of Science® Times Cited:2
Deposited By:Engineering
Deposited On:2013-05-21
Last Modified:2015-03-25

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