dc.contributor.author |
Salmon, BP
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|
dc.contributor.author |
Kleynhans, Waldo
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dc.contributor.author |
Olivier, JC
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dc.contributor.author |
Olding, WC
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dc.contributor.author |
Wessels, Konrad J
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dc.contributor.author |
Van den Bergh, Frans
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dc.date.accessioned |
2017-06-07T07:07:36Z |
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dc.date.available |
2017-06-07T07:07:36Z |
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dc.date.issued |
2014-07 |
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dc.identifier.citation |
Salmon, B.P., Kleynhans, W., Olivier, J.C. et al. 2014. Modified temporal approach to meta-optimizing an extended Kalman filter's parameters. 2014 IEEE International Geoscience and Remote Sensing Symposium, Québec, Canada, 13-18 July 2014. DOI: 10.1109/IGARSS.2014.6946632 |
en_US |
dc.identifier.issn |
2153-7003 |
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dc.identifier.uri |
DOI: 10.1109/IGARSS.2014.6946632
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dc.identifier.uri |
http://ieeexplore.ieee.org/document/6946632/
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dc.identifier.uri |
http://hdl.handle.net/10204/9156
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dc.description |
Copyright: 2014 EE Publishers. Due to copyright restrictions, the attached PDF file only contains the abstract of the full text item. For access to the full text item, please consult the publisher's website. |
en_US |
dc.description.abstract |
It has been shown that time series containing reflectance values from the first two spectral bands of the MODerateresolution Imaging Spectroradiometer (MODIS) land surface reflectance product can be modelled as a triply modulated cosine function. A meta-optimization approach has been proposed in the literature for setting the parameters of the non-linear Extended Kalman Filter (EKF) to rapidly and efficiently estimate the features for these triply modulated cosine functions using spatial information. In this paper we modify this approach to utilize temporal information instead of spatial information to greatly reduce the processing time and storage requirements to process each time series. The parameters derived from the newly proposed method is classified with a support vector machine and compared to the original approach. Performance of the methods is tested on the Limpopo province in South Africa. |
en_US |
dc.language.iso |
en |
en_US |
dc.publisher |
IEEE |
en_US |
dc.relation.ispartofseries |
Worklist;18647 |
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dc.relation.ispartofseries |
Worklist;14304 |
|
dc.subject |
MODerateresolution Imaging Spectroradiometer |
en_US |
dc.subject |
MODIS |
en_US |
dc.subject |
Kalman filtering |
en_US |
dc.subject |
Remote sensing |
en_US |
dc.subject |
Satellites |
en_US |
dc.subject |
Time series |
en_US |
dc.title |
Modified temporal approach to meta-optimizing an extended Kalman filter's parameters |
en_US |
dc.type |
Conference Presentation |
en_US |
dc.identifier.apacitation |
Salmon, B., Kleynhans, W., Olivier, J., Olding, W., Wessels, K. J., & Van den Bergh, F. (2014). Modified temporal approach to meta-optimizing an extended Kalman filter's parameters. IEEE. http://hdl.handle.net/10204/9156 |
en_ZA |
dc.identifier.chicagocitation |
Salmon, BP, Waldo Kleynhans, JC Olivier, WC Olding, Konrad J Wessels, and Frans Van den Bergh. "Modified temporal approach to meta-optimizing an extended Kalman filter's parameters." (2014): http://hdl.handle.net/10204/9156 |
en_ZA |
dc.identifier.vancouvercitation |
Salmon B, Kleynhans W, Olivier J, Olding W, Wessels KJ, Van den Bergh F, Modified temporal approach to meta-optimizing an extended Kalman filter's parameters; IEEE; 2014. http://hdl.handle.net/10204/9156 . |
en_ZA |
dc.identifier.ris |
TY - Conference Presentation
AU - Salmon, BP
AU - Kleynhans, Waldo
AU - Olivier, JC
AU - Olding, WC
AU - Wessels, Konrad J
AU - Van den Bergh, Frans
AB - It has been shown that time series containing reflectance values from the first two spectral bands of the MODerateresolution Imaging Spectroradiometer (MODIS) land surface reflectance product can be modelled as a triply modulated cosine function. A meta-optimization approach has been proposed in the literature for setting the parameters of the non-linear Extended Kalman Filter (EKF) to rapidly and efficiently estimate the features for these triply modulated cosine functions using spatial information. In this paper we modify this approach to utilize temporal information instead of spatial information to greatly reduce the processing time and storage requirements to process each time series. The parameters derived from the newly proposed method is classified with a support vector machine and compared to the original approach. Performance of the methods is tested on the Limpopo province in South Africa.
DA - 2014-07
DB - ResearchSpace
DP - CSIR
KW - MODerateresolution Imaging Spectroradiometer
KW - MODIS
KW - Kalman filtering
KW - Remote sensing
KW - Satellites
KW - Time series
LK - https://researchspace.csir.co.za
PY - 2014
SM - 2153-7003
T1 - Modified temporal approach to meta-optimizing an extended Kalman filter's parameters
TI - Modified temporal approach to meta-optimizing an extended Kalman filter's parameters
UR - http://hdl.handle.net/10204/9156
ER -
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en_ZA |