Title :
Rapid estimation of point source chemical pollutant coverage in catastrophe situation using hierarchical binary decision tree ensemble and probability membership value based ensemble approaches
Author :
Bakos, K.L. ; Gamba, P. ; Bura, P.
Author_Institution :
Dept. of Electron., Univ. of Pavia, Pavia, Italy
Abstract :
In this paper we present the test results of an extension developed to the Hierarchical Binary Decision Tree (HBDT) ensemble classifier that was introduced in the WHISPERS2009 conference. The new methodology is the Probability Membership Value based Ensemble (PMVE). It uses the HBDTC designer algorithm to select suitable processing chains for decision fusion, but the actual decision fusion is carried out in an unsupervised manner using a weighted re-mapping of the probability membership values of multiple classifiers. The test data used in this study was acquired during the “red sludge” event in Hungary at the end of 2010. Results of traditional classification approaches are also presented for sake of comparison.
Keywords :
decision trees; disasters; geophysical image processing; geophysical techniques; industrial pollution; land pollution; pattern classification; sensor fusion; uncertainty handling; AD 2010; HBDT ensemble classifier; HBDTC designer algorithm; Hungary; catastrophe situation; decision fusion; hierarchical binary decision tree ensemble; multiple classifier; point source chemical pollutant coverage; probability membership value based ensemble; rapid estimation; red sludge event; Accuracy; Algorithm design and analysis; Classification algorithms; Hyperspectral imaging; Principal component analysis; Support vector machines; Classification; Decision Fusion; Ensembles; Hyperspectral; Machine Learning;
Conference_Titel :
Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), 2011 3rd Workshop on
Conference_Location :
Lisbon
Print_ISBN :
978-1-4577-2202-8
DOI :
10.1109/WHISPERS.2011.6080942