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Detecting land cover change by evaluating the internal covariance matrix of the extended Kalman filter
conference contribution
posted on 2023-05-23, 07:14 authored by Brian SalmonBrian Salmon, Kleynhans, W, van den Bergh, F, Jan OlivierJan Olivier, Wessels, KJIn this paper, the internal operations of an Extended Kalman Filter is investigated to see if any useful information can be derived to detect land cover change in a MODIS time series. The Extended Kalman Filter expands its internal covariance if a significant change in reflectance value is observed, followed by adapting the state parameters to compensate for this change. The analysis shows 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 11%.
History
Publication title
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium 2012Editors
I Hajnsek and H RottPagination
6209-6212ISBN
978-1-4673-1159-5Department/School
School of EngineeringPublisher
Institute of Electrical and Electronics EngineersPlace 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