Examining the capability of supervised machine learning classifiers in extracting flooded areas from landsat tm imagery: A case study from a mediterranean flood

Remote Sensing

Volumn 7, Issue 3, 2015, Pages 3372-3399

  Ireland, Gareth ^a   Volpi, Michele ^b   Petropoulos, George P ^a  

^a ABERYSTWYTH UNIVERSITY   (United Kingdom)

^b UNIVERSITY OF EDINBURGH   (United Kingdom)

Author keywords

Evros River; Flooded area mapping; Greece; Landsat TM; Regularised kernel Fisher's discriminant analysis; Remote sensing; Support vector machines

Indexed keywords

ARTIFICIAL INTELLIGENCE; DISCRIMINANT ANALYSIS; LEARNING SYSTEMS; REMOTE SENSING; SUPERVISED LEARNING; SUPPORT VECTOR MACHINES;

CLASSIFICATION ACCURACY ASSESSMENTS; FLOODED AREAS; GREECE; KERNEL FISHER; LANDSAT TM; NORMALIZED DIFFERENCE WATER INDEX; SUPERVISED MACHINE LEARNING; SUPPORT VECTOR MACHINE (SVMS);

FLOODS;

EID: 84926369084     PISSN: None     EISSN: 20724292     Source Type: Journal    
DOI: 10.3390/rs70303372     Document Type: Article

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