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Unsupervised land cover change detection: Meaningful Sequential Time Series Analysis
Citation
Salmon, BP and Olivier, JC and Wessels, KJ and Kleynhans, W and van den Bergh, F and Steenkamp, KC, Unsupervised land cover change detection: Meaningful Sequential Time Series Analysis, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 4, (2) pp. 327-335. ISSN 1939-1404 (2011) [Refereed Article]
Copyright Statement
Copyright 2010 IEEE
DOI: doi:10.1109/JSTARS.2010.2053918
Abstract
An automated land cover change detection method
is proposed that uses coarse spatial resolution hyper-temporal
earth observation satellite time series data. The study compared
three different unsupervised clustering approaches that operate
on short term Fourier transform coefficients computed over
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 exceeding
76% on real land cover conversion and more than 70% on
simulated land cover conversion.
Item Details
Item Type: | Refereed Article |
---|---|
Research Division: | Engineering |
Research Group: | Electrical engineering |
Research Field: | Electrical engineering not elsewhere classified |
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: | 77853 |
Year Published: | 2011 |
Web of Science® Times Cited: | 37 |
Deposited By: | Engineering |
Deposited On: | 2012-06-01 |
Last Modified: | 2015-02-08 |
Downloads: | 0 |
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