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A spatio-temporal autocorrelation change detection approach using hyper-temporal satellite data
conference contribution
posted on 2023-05-23, 08:31 authored by Kleynhans, W, Brian SalmonBrian Salmon, Wessels, KJ, Jan OlivierJan OlivierThere has been recent developments in the use of hyper-temporal satellite time series data for land cover change detection and classification in South Africa and in particular, the monitoring of human settlement expansion is of relevance as it is the most pervasive form of land-cover change in the country. In this paper, a spatio-temporal change detection method is proposed that is applicable over large regions. This is achieved by adjusting the change threshold based on the change properties of a neighbourhood of pixels. Results indicate that the addition of spatial information increase change detection accuracy when compared to a pixel based approach.
History
Publication title
Proceedings of the 2013 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)Editors
C Fraser, J Walker and M WilliamsPagination
3459-3462ISBN
978-1-4799-1114-1Department/School
School of EngineeringPublisher
IEEEPlace of publication
USAEvent title
2013 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)Event Venue
Melbourne, AustraliaDate of Event (Start Date)
2013-07-21Date of Event (End Date)
2013-07-26Rights statement
Copyright 2013 IEEERepository Status
- Restricted