Towards automatic lithological classification from remote sensing data using support vector machines

Computers and Geosciences

Volumn 45, Issue , 2012, Pages 229-239

  Yu, Le ^a   Porwal, Alok ^b   Holden, Eun Jung ^c   Dentith, Michael C ^c  

^a TSINGHUA UNIVERSITY   (China)

^b CURTIN UNIVERSITY   (Australia)

^c UNIVERSITY OF WESTERN AUSTRALIA   (Australia)

Author keywords

Aeromagnetic; ASTER; DEM; Lithological classification; Supervised classification; Support vector machine (SVM)

Indexed keywords

AEROMAGNETIC; AEROMAGNETIC DATA; ASTER; CLASSIFICATION ACCURACY; DATA SETS; DEM; DIGITAL ELEVATION MODEL; ENHANCEMENT TECHNIQUES; IN-BUILDINGS; INDEPENDENT COMPONENTS; LITHOLOGICAL MAP; MAXIMUM LIKELIHOOD CLASSIFIERS; PRINCIPAL COMPONENTS; REMOTE SENSING DATA; SPACE-BORNE; STUDY AREAS; SUPERVISED CLASSIFICATION; SUPPORT VECTOR MACHINE ALGORITHM; THERMAL EMISSIONS;

CLASSIFICATION (OF INFORMATION); LITHOLOGY; MAGNETIC SUSCEPTIBILITY; REMOTE SENSING; SPACE OPTICS; SPECTROMETRY;

SUPPORT VECTOR MACHINES;

AEROMAGNETIC SURVEY; ALGORITHM; ASTER; CURVATURE; DATA SET; DIGITAL ELEVATION MODEL; GEOLOGICAL MAPPING; IMAGE CLASSIFICATION; LITHOLOGY; MAGNETIC SUSCEPTIBILITY; PRINCIPAL COMPONENT ANALYSIS; REMOTE SENSING; ROUGHNESS; SATELLITE IMAGERY; SLOPE;

INDIA;

EID: 84863469677     PISSN: 00983004     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.cageo.2011.11.019     Document Type: Article

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