Estimating fractional shrub cover using simulated enmap data: A comparison of three machine learning regression techniques

Remote Sensing

Volumn 6, Issue 4, 2014, Pages 3427-3445

  Schwieder, Marcel ^a   Leitão, Pedro J ^a   Suess, Stefan ^a   Senf, Cornelius ^a   Hostert, Patrick ^a  

^a HUMBOLDT UNIVERSITY   (Germany)

Author keywords

EnMAP; Hyperspectral; Land cover; Partial least squares regression; Portugal; Random forest regression; Shrub encroachment; Sub pixel mapping; Support vector regression

Indexed keywords

AGRICULTURAL MACHINERY; ARTIFICIAL INTELLIGENCE; DECISION TREES; ECOLOGY; ECOSYSTEMS; LAND USE; LEARNING SYSTEMS; LEAST SQUARES APPROXIMATIONS; MAPPING; REMOTE SENSING;

ENMAP; HYPERSPECTRAL; LAND COVER; PARTIAL LEAST SQUARES REGRESSION; PORTUGAL; RANDOM FORESTS; SHRUB ENCROACHMENTS; SUB-PIXEL MAPPING; SUPPORT VECTOR REGRESSION (SVR);

REGRESSION ANALYSIS;

EID: 84987957311     PISSN: None     EISSN: 20724292     Source Type: Journal    
DOI: 10.3390/rs6043427     Document Type: Article

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