Support Vector Machines for Landslide Susceptibility Mapping: The Staffora River Basin Case Study, Italy

Mathematical Geosciences

Volumn 44, Issue 1, 2012, Pages 47-70

  Ballabio, Cristiano ^a   Sterlacchini, Simone ^b  

^a UNIVERSITY OF MILANO BICOCCA   (Italy)

^b CNR   (Italy)

Author keywords

Cross validation; Landslide susceptibility mapping; Spatial prediction; Support Vector Machines

Indexed keywords

CONCEPTUAL FRAMEWORKS; CROSS VALIDATION; DATA COMPLEXITY; FALSE POSITIVE; GENERALIZATION CAPACITY; HIGH DENSITY; LANDSLIDE SUSCEPTIBILITY; LANDSLIDE SUSCEPTIBILITY MAPPING; LINEAR DISCRIMINANT ANALYSIS; LOGISTIC REGRESSIONS; MACHINE LEARNING METHODS; MODEL SELECTION; MODELING RESULTS; NAIVE BAYES CLASSIFIERS; NORTHERN ITALY; PREDICTION RATE; PREDICTIVE VARIABLES; PROCEDURAL STEPS; RAINFALL EVENT; RANDOM NOISE; RECEIVER OPERATING CHARACTERISTIC CURVES; RIVER BASINS; SLOPE FAILURE; SPATIAL PREDICTION; STATISTICAL APPROACH; STUDY AREAS; SUSCEPTIBILITY MAPPING;

CLASSIFIERS; DISCRIMINANT ANALYSIS; LANDSLIDES; LEARNING ALGORITHMS; MAPPING; WATERSHEDS;

SUPPORT VECTOR MACHINES;

ARTIFICIAL INTELLIGENCE; DISCRIMINANT ANALYSIS; EMPIRICAL ANALYSIS; GEOLOGICAL MAPPING; LANDSLIDE; PREDICTION; REGRESSION ANALYSIS; RIVER BASIN; SLOPE FAILURE;

ITALY; LOMBARDY; PAVIA; STAFFORA BASIN;

EID: 84855652855     PISSN: 18748961     EISSN: 18748953     Source Type: Journal    
DOI: 10.1007/s11004-011-9379-9     Document Type: Article

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