eCite Digital Repository

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:Electrical and Electronic Engineering
Research Field:Signal Processing
Objective Division:Environment
Objective Group:Environmental and Natural Resource Evaluation
Objective Field:Environmental Management Systems
Author:Salmon, BP (Dr Brian Salmon)
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

Repository Staff Only: item control page