GENERAL ENQUIRIES: Tel: + 27 12 841 2911 | Email: callcentre@csir.co.za

Show simple item record

dc.contributor.author Kleynhans, W
dc.contributor.author Salmon, BP
dc.contributor.author Olivier, JC
dc.contributor.author Wessels, Konrad J
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 Presentation en_US


Files in this item

This item appears in the following Collection(s)

Show simple item record

Search ResearchSpace


Advanced Search

Browse

My Account