Title
A spatio-temporal autocorrelation change detection approach using hyper-temporal satellite data
Abstract
There 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.
Year
DOI
Venue
2013
10.1109/IGARSS.2013.6723573
Geoscience and Remote Sensing Symposium
Keywords
Field
DocType
geophysical image processing,geophysical techniques,image classification,land cover,South Africa,human settlement expansion monitoring,hyper-temporal satellite time series data,land cover change classification,land cover change detection,pixel based approach,pixel neighbourhood change properties,spatio-temporal autocorrelation change detection approach
Spatial analysis,Time series,Change detection,Computer science,Remote sensing,Pixel,Communications satellite,Contextual image classification,Land cover,Autocorrelation
Conference
ISSN
ISBN
Citations 
2153-6996
978-1-4799-1114-1
1
PageRank 
References 
Authors
0.36
3
4
Name
Order
Citations
PageRank
Waldo Kleynhans111127.45
Brian P. Salmon215027.18
Konrad J. Wessels39820.52
J. Corne Olivier4203.50