Paper Info
Title
Land Cover Change Detection Using the Internal Covariance Matrix of the Extended Kalman Filter Over Multiple Spectral Bands
Abstract
In this paper, the internal operations of an Extended Kalman Filter is investigated to observe if information can be derived to detect land cover change in a MODerate-resolution Imaging Spectroradiometer (MODIS) time series. The concept is based on the internal covariance matrix used by the Extended Kalman Filter, which adjusts the internal state of the filter for any changes occurring in the time series. The Extended Kalman Filter expands the internal covariance matrix if a significant change in reflectance value is observed, followed by adapting the state parameters to compensate for this change. The analysis shows that a change detection accuracy above 90% can be attained when evaluating the elements within the internal covariance matrix to detect new human settlements, with a corresponding false alarm rate below 6%.
Year
DOI
Venue
2013
10.1109/JSTARS.2013.2241023
Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of
Keywords
Field
DocType
kalman filters,covariance matrices,remote sensing,terrain mapping,modis time series,moderate-resolution imaging spectroradiometer,extended kalman filter,false alarm rate,human settlements,internal covariance matrix,land cover change detection,multiple spectral bands,reflectance value,change detection algorithms,kalman filter,covariance matrix,spatial information,time series analysis
Alpha beta filter,Extended Kalman filter,Fast Kalman filter,Remote sensing,Covariance intersection,Kalman filter,Covariance matrix,Invariant extended Kalman filter,Ensemble Kalman filter,Mathematics
Journal
Volume
Issue
ISSN
6
3
1939-1404
Citations 
PageRank 
References 
3
0.55
4
Authors
6
Name
Order
Citations
PageRank
Brian P. Salmon115027.18
Waldo Kleynhans211127.45
Frans van den Bergh318921.35
Jan C. Olivier414829.36
t l grobler5182.95
Konrad J. Wessels69820.52