Evaluating EO1-Hyperion capability for mapping conifer and broadleaved forests

European Journal of Remote Sensing

Volumn 49, Issue , 2016, Pages 157-169

  Puletti, Nicola ^a,b   Camarretta, Nicolò ^a   Corona, Piermaria ^a  

^a ISTITUTO NAZIONALE DELLA NUTRIZIONE   (Italy)

^b FOREST RESEARCH INSTITUTE   (Poland)

Author keywords

Hyperspectral images; Image classification; Mediterranean areas; Multivariate adaptive regression splines; Random forest; Support vector machine

Indexed keywords

DECISION TREES; FORESTRY; HYPERSPECTRAL IMAGING; IMAGE CLASSIFICATION; MAPPING; MAPS; RANDOM FORESTS; SPECTROSCOPY; SPLINES; SUPPORT VECTOR REGRESSION;

BROAD-LEAVED FORESTS; CLASSIFICATION METHODS; CONFUSION MATRICES; CONIFEROUS FORESTS; EARTH OBSERVATIONS; MEDITERRANEAN AREAS; MULTIVARIATE ADAPTIVE REGRESSION SPLINES; OVERALL ACCURACIES;

SUPPORT VECTOR MACHINES;

ACCURACY ASSESSMENT; BROAD-LEAVED FOREST; CONIFEROUS FOREST; DATA ASSIMILATION; EOS; FOREST COVER; HYPERION; IMAGE CLASSIFICATION; LANDSAT; MEDITERRANEAN ENVIRONMENT; MULTIVARIATE ANALYSIS; SATELLITE IMAGERY; SUPPORT VECTOR MACHINE; VEGETATION MAPPING;

CONIFEROPHYTA;

EID: 84964834993     PISSN: None     EISSN: 22797254     Source Type: Journal    
DOI: 10.5721/EuJRS20164909     Document Type: Article

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