In a study of debris flow susceptibility on the European continent, an analysis of the impact between known location and a location accuracy offset for 99 debris flows demonstrates the impact of uncertainty in defining appropriate predisposing factors and consequent analysis for areas of susceptibility. The dominant predisposing environmental factors, as determined through Maximum Entropy modeling, are presented and analyzed with respect to the values found at debris flow event points versus a buffered distance of locational uncertainty around each point. Maximum Entropy susceptibility models are developed utilizing the original debris flow inventory of points, randomly generated points, and two models utilizing a subset of points with an uncertainty of 5 km, 1 km, and a model utilizing only points with a known location of “exact”. The AUCs are 0.891, 0.893, 0.896, 0.921, and 0.93, respectively. The “exact” model, with the highest AUC, is ignored in final analyses due to the small number of points and localized distribution, and hence susceptibility results are likely non‐representational of the continent. Each model is analyzed with respect to the AUC, highest contributing factors, factor classes, susceptibility impact, and comparisons of the susceptibility distributions and susceptibility value differences. Based on model comparisons, geographic extent, and the context of this study, the models utilizing points with a location uncertainty of less than or equal to 5 km best represent debris flow susceptibility for the continent of Europe. A novel representation of the uncertainty is expressed and included in a final susceptibility map, as an overlay of standard deviation and mean of susceptibility values for the two best models, provid-ing additional insight for subsequent action.

Impact and a Novel Representation of Spatial Data Uncertainty in Debris Flow Susceptibility Analysis

Kurilla L. J.;Fubelli G.
2022

Abstract

In a study of debris flow susceptibility on the European continent, an analysis of the impact between known location and a location accuracy offset for 99 debris flows demonstrates the impact of uncertainty in defining appropriate predisposing factors and consequent analysis for areas of susceptibility. The dominant predisposing environmental factors, as determined through Maximum Entropy modeling, are presented and analyzed with respect to the values found at debris flow event points versus a buffered distance of locational uncertainty around each point. Maximum Entropy susceptibility models are developed utilizing the original debris flow inventory of points, randomly generated points, and two models utilizing a subset of points with an uncertainty of 5 km, 1 km, and a model utilizing only points with a known location of “exact”. The AUCs are 0.891, 0.893, 0.896, 0.921, and 0.93, respectively. The “exact” model, with the highest AUC, is ignored in final analyses due to the small number of points and localized distribution, and hence susceptibility results are likely non‐representational of the continent. Each model is analyzed with respect to the AUC, highest contributing factors, factor classes, susceptibility impact, and comparisons of the susceptibility distributions and susceptibility value differences. Based on model comparisons, geographic extent, and the context of this study, the models utilizing points with a location uncertainty of less than or equal to 5 km best represent debris flow susceptibility for the continent of Europe. A novel representation of the uncertainty is expressed and included in a final susceptibility map, as an overlay of standard deviation and mean of susceptibility values for the two best models, provid-ing additional insight for subsequent action.
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debris flow; spatial uncertainty; susceptibility
Kurilla L.J.; Fubelli G.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/1873856
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