Skip to Main Content (Press Enter)

Logo CNR
  • ×
  • Home
  • People
  • Outputs
  • Organizations
  • Expertise & Skills

UNI-FIND
Logo CNR

|

UNI-FIND

cnr.it
  • ×
  • Home
  • People
  • Outputs
  • Organizations
  • Expertise & Skills
  1. Outputs

Different landslide sampling strategies in a grid-based bivariate statistical susceptibility model

Academic Article
Publication Date:
2015
abstract:
This study had three aims. The first was to assess the performance of the weights-of-evidence (WofE) landslide susceptibility model in areas that are very different in terms of size, geoenvironmental settings, and landslide types. The second was to test the appropriate strategies to sample the mapped landslide polygon. The final aim was to evaluate the performance of the method to changes in the landslide sample size used to train the model. The method was applied to two areas: the Fella River basin (eastern Italian Alps) containing debris flows, and Buzau County (Romanian Carpathians) with shallow landslides. The three landslide sampling strate- gies used were: (1) the landslide scarp centroid, (2) points populating the scarp on a 50-m grid, and (3) the entire scarp polygon. The highest success rates were obtained when sampling shallow landslides as 50-m grid-points and debris flow scarps as polygons. Prediction rates were highest when using the entire scarp polygon method for both landslide types. The sample size test using the landslide centroids showed that a sample of 104 debris flow scarps was sufficient to predict the remaining 941 debris flows in the Fella River basin, while 161 shallow landslides was the minimum required number to predict the remaining 1451 scarps in Buzau County. Below these landslide sample thresholds, model performance was too low. However, using more landslides than the threshold produced a plateau effect with little to no increase in the model performance rates.
Iris type:
01.01 Articolo in rivista
Keywords:
Landslide susceptibility; Weights-of-evidence (WofE); Landslide sampling; Grid-based analysis
List of contributors:
Reichenbach, Paola; Sterlacchini, Simone
Authors of the University:
REICHENBACH PAOLA
STERLACCHINI SIMONE
Handle:
https://iris.cnr.it/handle/20.500.14243/302078
Published in:
GEOMORPHOLOGY
Journal
  • Use of cookies

Powered by VIVO | Designed by Cineca | 26.5.0.0 | Sorgente dati: PREPROD (Ribaltamento disabilitato)