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Detecting land cover change by evaluating the internal covariance matrix of the extended Kalman filter
Citation
Salmon, BP and Kleynhans, W and van den Bergh, F and Olivier, JC and Wessels, KJ, Detecting land cover change by evaluating the internal covariance matrix of the extended Kalman filter, Proceedings of the IEEE International Geoscience and Remote Sensing Symposium 2012, 22-27 July, Munich, pp. 6209-6212. ISBN 978-1-4673-1159-5 (2012) [Refereed Conference Paper]
Copyright Statement
Copyright 2012 IEEE
DOI: doi:10.1109/IGARSS.2012.6352676
Abstract
In 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%.
Item Details
| Item Type: | Refereed Conference Paper |
|---|---|
| Keywords: | change detection algorithms, covariance matrix, Kalman filter, spatial information, time series analysis |
| Research Division: | Engineering |
| Research Group: | Communications engineering |
| Research Field: | Signal processing |
| Objective Division: | Environmental Management |
| Objective Group: | Other environmental management |
| Objective Field: | Other environmental management not elsewhere classified |
| UTAS Author: | Salmon, BP (Dr Brian Salmon) |
| UTAS Author: | Olivier, JC (Professor JC Olivier) |
| ID Code: | 82339 |
| Year Published: | 2012 |
| Deposited By: | Engineering |
| Deposited On: | 2013-01-25 |
| Last Modified: | 2017-11-06 |
| Downloads: | 0 |
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