Estimating soil moisture with the support vector regression technique

IEEE Geoscience and Remote Sensing Letters

Volumn 8, Issue 6, 2011, Pages 1080-1084

  Pasolli, Luca ^a,b   Notarnicola, Claudia ^b   Bruzzone, Lorenzo ^a  

^a UNIVERSITY OF TRENTO   (Italy)

^b INSTITUTE FOR RENEWABLE ENERGY   (Italy)

Author keywords

Estimation; microwave signals; regression; remote sensing; soil moisture; support vector regression (SVR)

Indexed keywords

ACQUISITION GEOMETRY; EASE OF USE; EXPERIMENTAL ANALYSIS; FIELD MEASUREMENT; GENERALIZATION CAPABILITY; INPUT FEATURES; MICROWAVE SIGNALS; MULTI-LAYER PERCEPTRON NEURAL NETWORKS; NEAR-REAL TIME; PASSIVE MICROWAVE MEASUREMENTS; REGRESSION; REMOTELY SENSED DATA; SENSOR FREQUENCY; SOIL MOISTURE ESTIMATION; SUPPORT VECTOR REGRESSION (SVR); SUPPORT VECTOR REGRESSIONS; TRAINING DATA;

BENCHMARKING; COMPUTATIONAL COMPLEXITY; ESTIMATION; MICROWAVE SENSORS; NEURAL NETWORKS; REGRESSION ANALYSIS; REMOTE SENSING; SOIL MOISTURE; SOIL SURVEYS;

MOISTURE DETERMINATION;

EID: 80255137400     PISSN: 1545598X     EISSN: None     Source Type: Journal    
DOI: 10.1109/LGRS.2011.2156759     Document Type: Article

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