Journal
INTERNATIONAL JOURNAL OF SPELEOLOGY
Volume 46, Issue 2, Pages 191-204Publisher
SOCIETA SPELEOLOGICA ITALIANA
DOI: 10.5038/1827-806X.46.2.2099
Keywords
evaporite karst; sinkhole; susceptibility; nearest neighbour; prediction-rate curves
Categories
Funding
- Spanish Ministry of Economy and Competitiveness through the 'Juan de la Cierva' Programme
- Geological Survey of the Friuli Venezia Giulia Region [412/09/11/2011, 587-15/06/2015]
Ask authors/readers for more resources
- The significance of intra-mountain valleys to infrastructure and human settlements and the need to mitigate the geo-hazard affecting these assets are fundamental to the economy of Italian alpine regions. Therefore, there is a real need to recognize and assess possible geo-hazards affecting them. This study proposes the use of GIS-based analyses to construct a sinkhole susceptibility model based on conditioning factors such as land use, geomorphology, thickness of shallow deposits, distance to drainage network and distance to faults. Thirty-two models, applied to a test site (Enemonzo municipality, NE Italy), were produced using a method based on the Likelihood Ratio (lambda) function, nine with only one variable and 23 applying different combinations. The sinkhole susceptibility model with the best forecast performance, with an Area Under the Prediction Rate Curve (AUPRC) of 0.88, was that combining the following parameters: Nearest Sinkhole Distance (NSD), land use and thickness of the surficial deposits. The introduction of NSD as a continuous variable in the computation represents an important upgrade in the prediction capability of the model. Additionally, the model was refined using a kernel density estimation that produced a significant improvement in the forecast performance.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available