dc.contributor.author |
Kleynhans, W
|
|
dc.contributor.author |
Salmon, BP
|
|
dc.contributor.author |
Olivier, JC
|
|
dc.contributor.author |
Wessels, Konrad J
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|
dc.contributor.author |
Van den Bergh, F
|
|
dc.date.accessioned |
2011-12-05T13:38:17Z |
|
dc.date.available |
2011-12-05T13:38:17Z |
|
dc.date.issued |
2011-07 |
|
dc.identifier.citation |
Kleynhans, W, Salmon, BP, Olivier, JC et al. 2011. An autocorrelation analysis approach to detecting land cover change using hyper-temporal time-series data. IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Vancouver, Canada, 24-29 July 2011 |
en_US |
dc.identifier.uri |
http://hdl.handle.net/10204/5363
|
|
dc.description |
IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Vancouver, Canada, 24-29 July 2011 |
en_US |
dc.description.abstract |
Human settlement expansion is one of the most pervasive forms of land cover change in the Gauteng province of South Africa. A method for detecting new settlement developments in areas that are typically covered by natural vegetation using 500m MODIS time-series satellite data is proposed. The method is a per pixel change alarm that uses the temporal autocorrelation to infer a change metric which yields a change or no-change decision after thresholding. Simulated change data was generated and used to determine a threshold during a preliminary off-line optimization phase. After optimization the method was evaluated on examples of known land cover change in the study area and experimental results indicate a 92% change detection accuracy with a 15% false alarm rate. |
en_US |
dc.language.iso |
en |
en_US |
dc.relation.ispartofseries |
Workflow request;7208 |
|
dc.subject |
Human settlements |
en_US |
dc.subject |
Hyper temporal time series data |
en_US |
dc.subject |
Settlement developments |
en_US |
dc.subject |
Land cover change |
en_US |
dc.subject |
Gauteng land cover change |
en_US |
dc.subject |
Time series data |
en_US |
dc.subject |
Remote sensing |
en_US |
dc.subject |
Geosciences |
en_US |
dc.subject |
IGARSS 2011 |
en_US |
dc.title |
An autocorrelation analysis approach to detecting land cover change using hyper-temporal time-series data |
en_US |
dc.type |
Conference Presentation |
en_US |
dc.identifier.apacitation |
Kleynhans, W., Salmon, B., Olivier, J., Wessels, K. J., & Van den Bergh, F. (2011). An autocorrelation analysis approach to detecting land cover change using hyper-temporal time-series data. http://hdl.handle.net/10204/5363 |
en_ZA |
dc.identifier.chicagocitation |
Kleynhans, W, BP Salmon, JC Olivier, Konrad J Wessels, and F Van den Bergh. "An autocorrelation analysis approach to detecting land cover change using hyper-temporal time-series data." (2011): http://hdl.handle.net/10204/5363 |
en_ZA |
dc.identifier.vancouvercitation |
Kleynhans W, Salmon B, Olivier J, Wessels KJ, Van den Bergh F, An autocorrelation analysis approach to detecting land cover change using hyper-temporal time-series data; 2011. http://hdl.handle.net/10204/5363 . |
en_ZA |
dc.identifier.ris |
TY - Conference Presentation
AU - Kleynhans, W
AU - Salmon, BP
AU - Olivier, JC
AU - Wessels, Konrad J
AU - Van den Bergh, F
AB - Human settlement expansion is one of the most pervasive forms of land cover change in the Gauteng province of South Africa. A method for detecting new settlement developments in areas that are typically covered by natural vegetation using 500m MODIS time-series satellite data is proposed. The method is a per pixel change alarm that uses the temporal autocorrelation to infer a change metric which yields a change or no-change decision after thresholding. Simulated change data was generated and used to determine a threshold during a preliminary off-line optimization phase. After optimization the method was evaluated on examples of known land cover change in the study area and experimental results indicate a 92% change detection accuracy with a 15% false alarm rate.
DA - 2011-07
DB - ResearchSpace
DP - CSIR
KW - Human settlements
KW - Hyper temporal time series data
KW - Settlement developments
KW - Land cover change
KW - Gauteng land cover change
KW - Time series data
KW - Remote sensing
KW - Geosciences
KW - IGARSS 2011
LK - https://researchspace.csir.co.za
PY - 2011
T1 - An autocorrelation analysis approach to detecting land cover change using hyper-temporal time-series data
TI - An autocorrelation analysis approach to detecting land cover change using hyper-temporal time-series data
UR - http://hdl.handle.net/10204/5363
ER -
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en_ZA |