dc.contributor.author |
Salmon, BP
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dc.contributor.author |
Olivier, JC
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|
dc.contributor.author |
Kleynhans, W
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dc.contributor.author |
Wessels, Konrad J
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dc.contributor.author |
Van den Bergh, F
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dc.date.accessioned |
2010-03-08T09:55:43Z |
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dc.date.available |
2010-03-08T09:55:43Z |
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dc.date.issued |
2009-07 |
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dc.identifier.citation |
Salmon, BP, Olivier, JC et al. 2009. Quest for automated land cover change detection using satellite time series data. IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Cape Town, South Africa, 12-17 July 2009, pp 244-247 |
en |
dc.identifier.isbn |
978-1-4244-3395-7 |
en |
dc.identifier.uri |
http://hdl.handle.net/10204/3978
|
|
dc.description |
IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Cape Town, South Africa, 12-17 July 2009 |
en |
dc.description.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. |
en |
dc.language.iso |
en |
en |
dc.publisher |
IEEE |
en |
dc.subject |
MLP |
en |
dc.subject |
Feedforward multilayer perceptron |
en |
dc.subject |
Land cover |
en |
dc.subject |
Satellites time series |
en |
dc.subject |
Feedforward neural networks |
en |
dc.subject |
MODIS data |
en |
dc.subject |
MODerate-resolution imaging spectroradiometer |
en |
dc.subject |
Remote sensing |
en |
dc.subject |
Geosciences |
en |
dc.title |
Quest for automated land cover change detection using satellite time series data |
en |
dc.type |
Conference Presentation |
en |
dc.identifier.apacitation |
Salmon, B., Olivier, J., Kleynhans, W., Wessels, K. J., & Van den Bergh, F. (2009). Quest for automated land cover change detection using satellite time series data. IEEE. http://hdl.handle.net/10204/3978 |
en_ZA |
dc.identifier.chicagocitation |
Salmon, BP, JC Olivier, W Kleynhans, Konrad J Wessels, and F Van den Bergh. "Quest for automated land cover change detection using satellite time series data." (2009): http://hdl.handle.net/10204/3978 |
en_ZA |
dc.identifier.vancouvercitation |
Salmon B, Olivier J, Kleynhans W, Wessels KJ, Van den Bergh F, Quest for automated land cover change detection using satellite time series data; IEEE; 2009. http://hdl.handle.net/10204/3978 . |
en_ZA |
dc.identifier.ris |
TY - Conference Presentation
AU - Salmon, BP
AU - Olivier, JC
AU - Kleynhans, W
AU - Wessels, Konrad J
AU - Van den Bergh, F
AB - 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.
DA - 2009-07
DB - ResearchSpace
DP - CSIR
KW - MLP
KW - Feedforward multilayer perceptron
KW - Land cover
KW - Satellites time series
KW - Feedforward neural networks
KW - MODIS data
KW - MODerate-resolution imaging spectroradiometer
KW - Remote sensing
KW - Geosciences
LK - https://researchspace.csir.co.za
PY - 2009
SM - 978-1-4244-3395-7
T1 - Quest for automated land cover change detection using satellite time series data
TI - Quest for automated land cover change detection using satellite time series data
UR - http://hdl.handle.net/10204/3978
ER -
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en_ZA |