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Detecting land cover change using a sliding window temporal autocorrelation approach
conference contribution
posted on 2023-05-23, 07:14 authored by Kleynhans, W, Brian SalmonBrian Salmon, Jan OlivierJan Olivier, van den Bergh, F, Wessels, KJ, Grobler, TThere 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.
History
Publication title
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium 2012Editors
I Hajnsek and H RottPagination
6765-6768ISBN
978-1-4673-1159-5Department/School
School of EngineeringPublisher
22-27 JulyPlace of publication
MunichEvent title
IEEE International Geoscience and Remote Sensing Symposium 2012Event Venue
MunichDate of Event (Start Date)
2012-07-22Date of Event (End Date)
2012-07-27Rights statement
Copyright 2012 IEEERepository Status
- Restricted