2021
DOI: 10.1016/j.enggeo.2021.106288
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Landslide size matters: A new data-driven, spatial prototype

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Cited by 54 publications
(36 citation statements)
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“…Guzzetti et al (1999) proposed to alternatively model landslide areas, which can be easily extracted from a polygonal inventory. Nevertheless, the first spatially-explicit model able to estimate landslide areas has only been recently proposed by Lombardo et al (2021). In their work, the authors exclusively estimated the potential landslide size at a given location, without informing whether the given location would have been susceptible in the first place.…”
Section: Introductionmentioning
confidence: 99%
“…Guzzetti et al (1999) proposed to alternatively model landslide areas, which can be easily extracted from a polygonal inventory. Nevertheless, the first spatially-explicit model able to estimate landslide areas has only been recently proposed by Lombardo et al (2021). In their work, the authors exclusively estimated the potential landslide size at a given location, without informing whether the given location would have been susceptible in the first place.…”
Section: Introductionmentioning
confidence: 99%
“…For this reason, we already envision future models that would take the measured extent of TS and TEG as the response variable, this time solving a regression task rather than a classification, one as per susceptibility requirement. Such direction has recently been explored for landslides occurring at lower latitudes (Lombardo et al, 2021;Moreno et al, 2022). And, an even better extension has already been tested where the expectation of locations prone to landslides are modelled together with the expectation of the resulting landslide size (Aguilera et al, 2022;Bryce et al, 2022).…”
Section: Considerations Within and Beyond Svalbard: Supporting And Op...mentioning
confidence: 99%
“…LGCPs are widely used in the modeling of spatial point patterns and have risen as a counterpart of Gaussian processes (used for continuous variables) for modeling discrete spatial phenomena. Recently, LGCP models have drawn attention in modeling landslide occurrences; see, e.g., Lombardo et al (2018Lombardo et al ( , 2020Lombardo et al ( , 2021 and Opitz et al (2020). In this work, we take LGCP models as a basis and in § §3.2-3.4, we build joint models for landslide occurrences and sizes (here defined as the square root of landslide areas), where sizes are viewed as numerical marks, each associated with exactly one point.…”
Section: Poisson Processes Andmentioning
confidence: 99%
“…Precisely, we shall model the square root of the landslide area, which is lighter-tailed than the area itself, and can be measured and intuitively interpreted on the same scale as the landslide diameter. In the literature, other attempts have already been made to model and predict landslide sizes or "magnitudes" in addition to the modeling of landslide counts (see, e.g., Guo et al, 2017;Roback et al, 2018;Valagussa et al, 2019;Vanani et al, 2021;Lombardo et al, 2021). For example, Guo et al (2017) used power-law relationships of the size distribution to study earthquake-induced landslides in both the Himalayan and Lesser Himalayan regions.…”
Section: Introductionmentioning
confidence: 99%
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