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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 |
| UTAS Author: | Salmon, BP (Dr Brian Salmon) |
| UTAS Author: | Olivier, JC (Professor JC Olivier) |
| ID Code: | 82341 |
| Year Published: | 2012 |
| Web of Science® Times Cited: | 4 |
| Deposited By: | Engineering |
| Deposited On: | 2013-01-25 |
| Last Modified: | 2017-11-06 |
| Downloads: | 0 |
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