Title :
Spectral analysis of aster and hyperion data for geological classification of volcano teide
Author :
Piscini, Alessandro ; Amici, Stefania ; Pieri, David
Author_Institution :
Ist. Naz. di Geofisica e Vulcanologia, Rome, Italy
Abstract :
This work is an evaluation, to which degree geological information can be obtained from modern remote sensing systems like the multispectral ASTER or the hyperspectral Hyperion sensor for a volcanic region like Teide Volcano (Tenerife, Canary Islands). To account for the enhanced information content these sensors provide, hyperspectral analysis methods, incorporating for example Minimum Noise Fraction-Transformation (MNF) for data quality assessment and noise reduction as well as Spectral Angle Mapper (SAM) and Support Vector Machine (SVM) for supervised classification, were applied. Ground Truth reflectance data were obtained with a FieldSpec Pro measurements campaign conducted during later summer of 2007 in the frame of the EC project PREVIEW (http://www.preview-risk.com/).
Keywords :
geophysical signal processing; remote sensing; signal classification; spectral analysis; support vector machines; volcanology; AD 2007; ASTER spectral analysis; Canary Islands; FieldSpec Pro measurements campaign; Hyperion spectral analysis; MNF; SVM; Teide volcano; Tenerife; geological classification; ground truth reflectance data; hyperspectral analysis methods; minimum noise fraction transformation; remote sensing systems; spectral angle mapper; supervised classification; support vector machine; Accuracy; Classification algorithms; Geology; Reflectivity; Spatial resolution; Support vector machines; Volcanoes; ASTER; Hyperion; Teide; classification; hyperspectral sensors; reflectance spectra;
Conference_Titel :
Geoscience and Remote Sensing Symposium (IGARSS), 2010 IEEE International
Conference_Location :
Honolulu, HI
Print_ISBN :
978-1-4244-9565-8
Electronic_ISBN :
2153-6996
DOI :
10.1109/IGARSS.2010.5652063