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 |
2010-12-06T08:36:48Z |
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dc.date.available |
2010-12-06T08:36:48Z |
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dc.date.issued |
2010-07 |
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dc.identifier.citation |
Salmon, BP, Olivier, JC, Kleynhans, W et al. 2010. Automated land cover change detection: the quest for meaningful high temporal time series extraction. Proceedings of the 2010 IEEE International Geoscience and Remote Sensing Symposium, Honolulu, Hawaii, USA, 25-30 July 2010, pp 1-4 |
en |
dc.identifier.uri |
http://hdl.handle.net/10204/4590
|
|
dc.description |
Proceedings of the 2010 IEEE International Geoscience and Remote Sensing Symposium, Honolulu, Hawaii, USA, 25-30 July 2010 |
en |
dc.description.abstract |
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. |
en |
dc.language.iso |
en |
en |
dc.publisher |
IEEE |
en |
dc.relation.ispartofseries |
Conference Paper |
en |
dc.subject |
Change detection |
en |
dc.subject |
Clustering |
en |
dc.subject |
Satellite |
en |
dc.subject |
Time series |
en |
dc.subject |
Land cover |
en |
dc.subject |
Geoscience |
en |
dc.subject |
Remote sensing |
en |
dc.title |
Automated land cover change detection: the quest for meaningful high temporal time series extraction |
en |
dc.type |
Conference Presentation |
en |
dc.identifier.apacitation |
Salmon, B., Olivier, J., Kleynhans, W., Wessels, K. J., & Van den Bergh, F. (2010). Automated land cover change detection: the quest for meaningful high temporal time series extraction. IEEE. http://hdl.handle.net/10204/4590 |
en_ZA |
dc.identifier.chicagocitation |
Salmon, BP, JC Olivier, W Kleynhans, Konrad J Wessels, and F Van den Bergh. "Automated land cover change detection: the quest for meaningful high temporal time series extraction." (2010): http://hdl.handle.net/10204/4590 |
en_ZA |
dc.identifier.vancouvercitation |
Salmon B, Olivier J, Kleynhans W, Wessels KJ, Van den Bergh F, Automated land cover change detection: the quest for meaningful high temporal time series extraction; IEEE; 2010. http://hdl.handle.net/10204/4590 . |
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 - 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.
DA - 2010-07
DB - ResearchSpace
DP - CSIR
KW - Change detection
KW - Clustering
KW - Satellite
KW - Time series
KW - Land cover
KW - Geoscience
KW - Remote sensing
LK - https://researchspace.csir.co.za
PY - 2010
T1 - Automated land cover change detection: the quest for meaningful high temporal time series extraction
TI - Automated land cover change detection: the quest for meaningful high temporal time series extraction
UR - http://hdl.handle.net/10204/4590
ER -
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en_ZA |