Estimation of Information Loss When Masking Conditional Dependence and Categorizing Continuous Data: Further Experiments on a Database for Spatial Prediction Modelling in Northern Italy
Prediction patterns are generated using different data sets from a database for landslides hazard in northern Italy. A direct supporting pattern of the distribution of 28 complex landslides was previously used to obtain their spatial relationships with five categorical indirect supporting patterns representing the spatial context of the landslides: geology, land use, and permeability in addition to internal relief and slope, the latter two categorized into five classes. The five indirect supporting patterns were selected to minimize the effects of conditional dependence on prediction patterns by a Weight-of-Evidence model. The same set of patterns is reanalysed applying the Empirical Likelihood Ratio model using also uncategorized continuous supporting patterns: aspect, curvature, and digital elevation, in addition to internal relief and slope. The resulting prediction patterns are compared in terms of prediction rates and target-uncertainty patterns.
KeywordsSpatial Relationship Landslide Hazard Spatial Database Spatial Context Spatial Prediction
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