ResearchSpace

Transforming the autocorrelation function of a time series to detect land cover change

Show simple item record

dc.contributor.author Salmon, BP
dc.contributor.author Kleynhans, Waldo
dc.contributor.author Olivier, JC
dc.contributor.author Schwegmann, Colin P
dc.date.accessioned 2017-05-17T06:57:22Z
dc.date.available 2017-05-17T06:57:22Z
dc.date.issued 2015-07
dc.identifier.citation Salmon, B.P., Kleynhans, W., Olivier, J.C. and Schwegmann, C.P. 2016. Transforming the autocorrelation function of a time series to detect land cover change. International Geoscience and Remote Sensing Symposium (IEEE IGARSS 2016), 10-15 July 2016, Beijing, China. DOI: 10.1109/IGARSS.2016.7730350 en_US
dc.identifier.issn 2153-7003
dc.identifier.issn DOI: 10.1109/IGARSS.2016.7730350
dc.identifier.uri http://ieeexplore.ieee.org/document/7730350/
dc.identifier.uri http://hdl.handle.net/10204/9084
dc.description International Geoscience and Remote Sensing Symposium (IEEE IGARSS 2016), 10-15 July 2016, Beijing, China. 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 Regional monitoring of land cover conversion of natural vegetation to new informal human settlements is essential when investigating the migration of people to urbanized cities. Detecting these new settlements require reliable change detection methods. A robust change detection metric can be derived by analyzing the area under the autocorrelation function for a time series. The time dependence on the first and second moment causes a non-stationary event within the time series which results in non-symmetrical variations. In this work we explore the behavior of the autocorrelation function using new integration, differentiation and windowing approaches. Experiments were conducted in the Gauteng province of South Africa and we found a proper windowing function improved the overall detection accuracy. en_US
dc.language.iso en en_US
dc.publisher IEEE en_US
dc.relation.ispartofseries Worklist;17907
dc.subject Autocorrelation en_US
dc.subject Change detection en_US
dc.subject MODIS en_US
dc.subject Time series en_US
dc.title Transforming the autocorrelation function of a time series to detect land cover change en_US
dc.type Conference Presentation en_US
dc.identifier.apacitation Salmon, B., Kleynhans, W., Olivier, J., & Schwegmann, C. P. (2015). Transforming the autocorrelation function of a time series to detect land cover change. IEEE. http://hdl.handle.net/10204/9084 en_ZA
dc.identifier.chicagocitation Salmon, BP, Waldo Kleynhans, JC Olivier, and Colin P Schwegmann. "Transforming the autocorrelation function of a time series to detect land cover change." (2015): http://hdl.handle.net/10204/9084 en_ZA
dc.identifier.vancouvercitation Salmon B, Kleynhans W, Olivier J, Schwegmann CP, Transforming the autocorrelation function of a time series to detect land cover change; IEEE; 2015. http://hdl.handle.net/10204/9084 . en_ZA
dc.identifier.ris TY - Conference Presentation AU - Salmon, BP AU - Kleynhans, Waldo AU - Olivier, JC AU - Schwegmann, Colin P AB - Regional monitoring of land cover conversion of natural vegetation to new informal human settlements is essential when investigating the migration of people to urbanized cities. Detecting these new settlements require reliable change detection methods. A robust change detection metric can be derived by analyzing the area under the autocorrelation function for a time series. The time dependence on the first and second moment causes a non-stationary event within the time series which results in non-symmetrical variations. In this work we explore the behavior of the autocorrelation function using new integration, differentiation and windowing approaches. Experiments were conducted in the Gauteng province of South Africa and we found a proper windowing function improved the overall detection accuracy. DA - 2015-07 DB - ResearchSpace DP - CSIR KW - Autocorrelation KW - Change detection KW - MODIS KW - Time series LK - https://researchspace.csir.co.za PY - 2015 SM - 2153-7003 SM - DOI: 10.1109/IGARSS.2016.7730350 T1 - Transforming the autocorrelation function of a time series to detect land cover change TI - Transforming the autocorrelation function of a time series to detect land cover change UR - http://hdl.handle.net/10204/9084 ER - en_ZA


Files in this item

Thumbnail
Name: Salmon_2016.pdf
Size: 176.0Kb
Format: PDF
Description: Abstract
View/Open

This item appears in the following Collection(s)

Show simple item record