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The quest for automated land cover change detection using satellite time series data
Citation
Salmon, BP and Olivier, JC and Kleynhans, W and Wessels, KJ and van den Bergh, F, The quest for automated land cover change detection using satellite time series data, Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 12-17 July 2009, Cape Town, South Africa, pp. 244-247. ISBN 978-1-4244-3395-7 (2009) [Refereed Conference Paper]
Copyright Statement
Copyright 2009 IEEE
DOI: doi:10.1109/IGARSS.2009.5417328
Abstract
This paper shows that a feedforward Multilayer Perceptron
(MLP) operating over a temporal sliding window of multispectral
time series MODerate-resolution Imaging Spectroradiometer
(MODIS) satellite data is able to detect land cover
change that was artificially introduced by concatenating time
series belonging to different types of land cover. The method
employs an iteratively retrained MLP that is a supervised
method, and thus captures all local environmental patterns.
Depending on the length of the temporal sliding window used
in the short-term Fourier transform, an overall change detection
accuracy of between 87.62% and 97.02% was achieved.
It is shown that for this type of simulated land cover change,
where land cover change was abrupt, a short-term FFT window
of 18 months or less, using only the two NDVI spectral
bands of MODIS data was sufficient to detect change reliably.
Item Details
Item Type: | Refereed Conference Paper |
---|---|
Keywords: | classification, feedforward neural networks, satellites, 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: | 84574 |
Year Published: | 2009 |
Deposited By: | Engineering |
Deposited On: | 2013-05-21 |
Last Modified: | 2014-12-11 |
Downloads: | 0 |
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