Title :
Multi-temporal damage assessment of linear infrastructural objects using Dynamic Bayesian Networks
Author :
Frey, Daniel ; Butenuth, Matthias
Author_Institution :
Remote Sensing Technol., Tech. Univ. Munchen, München, Germany
Abstract :
In this paper, a Dynamic Bayesian Network (DBN) is presented which assesses infrastructural objects concerning their functionality after natural disasters. The presented model combines multi-temporal observations from remote sensed images with simulations based on Digital Elevation Models (DEM). The inference in the DBN is established using the sum-product algorithm. The improved performance of DBN is shown compared to simpler pixel-based and topology-based graphical models. The paper shows results of the model assessing roads concerning their trafficability after flooding. In addition, an evaluation of the results with a reference is conducted.
Keywords :
Bayes methods; digital elevation models; disasters; floods; geophysical image processing; hydrological techniques; object detection; remote sensing; topology; digital elevation model; dynamic Bayesian network; flood simulation process; linear infrastructural objects; multitemporal damage assessment; multitemporal observation; pixel-based graphical model; remote sensing image; sum-product algorithm; topology-based graphical model; Bayesian methods; Graphical models; Mathematical model; Random variables; Remote sensing; Roads; Topology; Classification; Damage Assessment; Dynamic Bayesian Network; Graphical Models; Natural Disasters;
Conference_Titel :
Analysis of Multi-temporal Remote Sensing Images (Multi-Temp), 2011 6th International Workshop on the
Conference_Location :
Trento
Print_ISBN :
978-1-4577-1202-9
DOI :
10.1109/Multi-Temp.2011.6005048