Co-Orbital Sentinel 1 and 2 for LULC mapping with emphasis on wetlands in a mediterranean setting based on machine learning

Remote Sensing

Volumn 9, Issue 12, 2017, Pages

  Chatziantoniou, Andromachi ^a   Petropoulos, George P ^b,c   Psomiadis, Emmanouil ^a  

^a AGRICULTURAL UNIVERSITY OF ATHENS   (Greece)

^b ABERYSTWYTH UNIVERSITY   (United Kingdom)

^c TECHNICAL UNIVERSITY OF CRETE   (Greece)

Author keywords

Classification; SAR; Sentinel 1; Sentinel 2; Support Vector Machines; Wetlands

Indexed keywords

ARTIFICIAL INTELLIGENCE; CLASSIFICATION (OF INFORMATION); COMPUTATION THEORY; COST EFFECTIVENESS; ERROR STATISTICS; KNOWLEDGE BASED SYSTEMS; LAND USE; LEARNING SYSTEMS; MAPPING; MAPS; SUPPORT VECTOR MACHINES; WETLANDS;

CLASSIFICATION ACCURACY; CLASSIFICATION ERRORS; CLASSIFICATION RESULTS; GREY-LEVEL CO-OCCURRENCE MATRIXES; MINIMUM NOISE FRACTION; SENTINEL 2; SENTINEL-1; SUPPORT VECTOR MACHINE (SVMS);

PRINCIPAL COMPONENT ANALYSIS;

EID: 85038216455     PISSN: None     EISSN: 20724292     Source Type: Journal    
DOI: 10.3390/rs9121259     Document Type: Article

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