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Preparing first-time slope failures hazard maps: from pixel-based to slope unit-based
by
Domènech Guillem
, Alvioli Massimiliano
, Corominas Jordi
in
Aggregation
/ Clustering
/ Failure
/ Failures
/ Geographic information systems
/ Geological hazards
/ Geomorphology
/ Information systems
/ Landslides
/ Landslides & mudslides
/ Pixels
/ Procedures
/ Size distribution
/ Slope stability
/ Susceptibility
2020
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Preparing first-time slope failures hazard maps: from pixel-based to slope unit-based
by
Domènech Guillem
, Alvioli Massimiliano
, Corominas Jordi
in
Aggregation
/ Clustering
/ Failure
/ Failures
/ Geographic information systems
/ Geological hazards
/ Geomorphology
/ Information systems
/ Landslides
/ Landslides & mudslides
/ Pixels
/ Procedures
/ Size distribution
/ Slope stability
/ Susceptibility
2020
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While trying to remove the title from your shelf something went wrong :( Kindly try again later!
Do you wish to request the book?
Preparing first-time slope failures hazard maps: from pixel-based to slope unit-based
by
Domènech Guillem
, Alvioli Massimiliano
, Corominas Jordi
in
Aggregation
/ Clustering
/ Failure
/ Failures
/ Geographic information systems
/ Geological hazards
/ Geomorphology
/ Information systems
/ Landslides
/ Landslides & mudslides
/ Pixels
/ Procedures
/ Size distribution
/ Slope stability
/ Susceptibility
2020
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Preparing first-time slope failures hazard maps: from pixel-based to slope unit-based
Journal Article
Preparing first-time slope failures hazard maps: from pixel-based to slope unit-based
2020
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Overview
In this work, we present a novel quantitative geographical information system-based procedure to obtain the magnitude (area) and frequency of medium to large first-time shallow slope failures. The procedure has been set up at the Barcedana Valley, in the Tremp Basin (Eastern Pyrenees). First, pixel-based susceptibility classes were defined using a slope stability index obtained with the physically based model SINMAP. The frequency calculated from the number of first-time failures recorded during the last 60 years was then assigned to each susceptibility class. We devised a procedure to estimate the size of potential failures by means of the aggregation of pixels within the boundaries of morphological slope units, optimized for the purpose. Finally, the landslide hazard was prepared using the magnitude-frequency matrix. Results show that a proper pixel clustering has been carried which avoids the generation of small groups of pixels with different susceptibility degrees within the same slope unit. For a given hill slope, the area of the cluster of pixels depends on the size of the slope unit, which is not unique as it depends on the criterion used to delineate them. Therefore, the latter is a key factor in the final results. In this study, we validated our results with the size distribution of the observed landslides. The methodology presented in this work can be applied using any susceptibility assessment method with a pixel-based output.
Publisher
Springer Nature B.V
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