Application of machine learning methods to spatial interpolation of environmental variables

Environmental Modelling and Software

Volumn 26, Issue 12, 2011, Pages 1647-1659

  Li, Jin ^a   Heap, Andrew D ^a   Potter, Anna ^a   Daniell, James J ^a  

^a GEOSCIENCE AUSTRALIA   (Australia)

Author keywords

Geostatistics; Kriging; Random forest; Spatial prediction; Spatially continuous variable; Support vector machine

Indexed keywords

CONTINUOUS VARIABLES; GEO-STATISTICS; KRIGING; RANDOM FORESTS; SPATIAL PREDICTION; SUPPORT VECTOR;

DECISION TREES; FORECASTING; FORESTRY; SUPPORT VECTOR MACHINES;

INTERPOLATION;

ACCURACY ASSESSMENT; AREAL INTERPOLATION; GEOSTATISTICS; INVERSE ANALYSIS; KRIGING; LEARNING; MODEL VALIDATION; MUD; VECTOR;

ALGORITHMS; FORECASTS; FORESTS; STATISTICAL ANALYSIS;

AUSTRALIA;

EID: 84855493098     PISSN: 13648152     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.envsoft.2011.07.004     Document Type: Article

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