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Detecting land cover change using a sliding window temporal autocorrelation approach

Citation

Kleynhans, W and Salmon, BP and Olivier, JC and van den Bergh, F and Wessels, KJ and Grobler, T, Detecting land cover change using a sliding window temporal autocorrelation approach, Proceedings of the IEEE International Geoscience and Remote Sensing Symposium 2012, 22-27 July, Munich, pp. 6765-6768. ISBN 978-1-4673-1159-5 (2012) [Refereed Conference Paper]

Copyright Statement

Copyright 2012 IEEE

DOI: doi:10.1109/IGARSS.2012.6352552

Abstract

There has been recent developments in the use of hypertemporal satellite time series data for land cover change detection and classification. Recently, an Autocorrelation function (ACF) change detection method was proposed to detect the development of new human settlements in South Africa. In this paper, an extension to this change detection method is proposed that produces an estimate of the change date in addition to the change metric. Preliminary results indicate that comparable accuracy is achievable relative to the original formulation, with the added advantage of providing an estimate of the change date.

Item Details

Item Type:Refereed Conference Paper
Keywords:Detecting land cover change using a sliding window temporal autocorrelation approach
Research Division:Engineering
Research Group:Electrical and Electronic Engineering
Research Field:Signal Processing
Objective Division:Environment
Objective Group:Environmental and Natural Resource Evaluation
Objective Field:Environmental Management Systems
Author:Salmon, BP (Dr Brian Salmon)
Author:Olivier, JC (Professor JC Olivier)
ID Code:82341
Year Published:2012
Web of Science® Times Cited:2
Deposited By:Engineering
Deposited On:2013-01-25
Last Modified:2017-11-06
Downloads:0

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