The influence of grid resolution on the prediction of natural and road-related shallow landslides

Penna, Daniele; Borga, Marco; Aronica, Giuseppe Tito; Brigandì, Giuseppina; Tarolli, Paolo

doi:10.5194/hess-18-2127-2014

Cited by 56 publications

(50 citation statements)

References 50 publications

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“…This abandonment was due to the conversion from manual to mechanical cultivation practices that increased the difficulties in the maintenance of vineyards, especially for those located on very steep slopes (> 25 • ) (Persichillo et al, 2017a). Moreover, societal changes, together with the decreasing number of people actively cultivating the area, caused a reduction in land care practices and maintenance works in both abandoned and cultivated vineyards (Persichillo et al, 2017a(Persichillo et al, , 2018.…”

Section: The Study Areamentioning

confidence: 99%

“…Moreover, societal changes, together with the decreasing number of people actively cultivating the area, caused a reduction in land care practices and maintenance works in both abandoned and cultivated vineyards (Persichillo et al, 2017a(Persichillo et al, , 2018.…”

Section: The Study Areamentioning

confidence: 99%

“…The inventory map of affected road traits include all the sectors hit by the shallow landslides occurred in the study area during 27-28 April 2009, March/April 2013 and 28 February-2 March 2014 rainfall events. For the 2009 event, colour aerial photographs at a resolution of 15 cm acquired immediately after the event were examined (Persichillo et al, 2017a). For 2013 event, affected road traits were identified by visual interpretation of Pleiades satellite images with a resolution of less than 1 m (Persichillo et al, 2017a).…”

Section: The Study Areamentioning

confidence: 99%

“…However, land use changes can have significant impacts both on the locations of landslide triggering zones (Glade, 2003;Begueria, 2006;Reichenbach et al, 2014;Persichillo et al, 2017a) and on the connectivity of the mobilized sediments (Foerster et al, 2014;Lopez-Vicente et al, 2013. Thus, susceptibility scenarios of different land use distributions may allow the identification of land man-agement practices able to reduce the slope instability which can induce damages to roads.…”

Section: Introductionmentioning

confidence: 99%

“…In recent years, several data-driven methodologies were built to identify the susceptible sectors of a road network to landslides (Budetta, 2004;Hearn et al, 2008;Jaiswal et al, 2010aJaiswal et al, , b, 2011Quinn et al, 2010;Michoud et al, 2012;Tarolli et al, 2013;Bil et al, 2014Bil et al, , 2017Penna et al, 2014;Ramesh and Anbazhagan, 2015;Tarolli and Sofia, 2016;Winter et al, 2016;Donnini et al, 2017;Pellicani et al, 2017;Postance et al, 2017;Martinovic et al, 2018). These methods are based on quantitative statistical relationships between predisposing factors and a response variable.…”

Section: Introductionmentioning

confidence: 99%

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Estimation of the susceptibility of a road network to shallow landslides with the integration of the sediment connectivity

Bordoni

Persichillo

Meisina

et al. 2018

Nat. Hazards Earth Syst. Sci.

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Abstract. Landslides cause severe damage to the road network of the hit zone, in terms of both direct (partial or complete destruction of a road or blockages) and indirect (traffic restriction or the cut-off of a certain area) costs. Thus, the identification of the parts of the road network that are more susceptible to landslides is fundamental to reduce the risk to the population potentially exposed and the financial expense caused by the damage. For these reasons, this paper aimed to develop and test a data-driven model for the identification of road sectors that are susceptible to being hit by shallow landslides triggered in slopes upstream from the infrastructure. This model was based on the Generalized Additive Method, where the function relating predictors and response variable is an empirically fitted smooth function that allows fitting the data in the more likely functional form, considering also non-linear relations. This work also analyzed the importance, on the estimation of the susceptibility, of considering or not the sediment connectivity, which influences the path and the travel distance of the materials mobilized by a slope failure until hitting a potential barrier such as a road. The study was carried out in a catchment of northeastern Oltrepò Pavese (northern Italy), where several shallow landslides affected roads in the last 8 years. The most significant explanatory variables were selected by a random partition of the available dataset in two parts (training and test subsets), 100 times according to a bootstrap procedure. These variables (selected 80 times by the bootstrap procedure) were used to build the final susceptibility model, the accuracy of which was estimated through a 100-fold repetition of the holdout method for regression, based on the training and test sets created through the 100 bootstrap model selection. The presented methodology allows the identification, in a robust and reliable way, of the most susceptible road sectors that could be hit by sediments delivered by landslides. The best predictive capability was obtained using a model in which the index of connectivity was also calculated according to a linear relationship, was considered. Most susceptible road traits resulted to be located below steep slopes with a limited height (lower than 50 m), where sediment connectivity is high. Different land use scenarios were considered in order to estimate possible changes in road susceptibility. Land use classes of the study area were characterized by similar connectivity features. As a consequence, variations on the susceptibility of the road network according to different scenarios of distribution of land cover were limited. The results of this research demonstrate the ability of the developed methodology in the assessment of susceptible roads. This could give the managers of infrastructure information about the criticality of the different road traits, thereby allowing attention and economic budgets to be shifted towards the most critical assets, where structural and non-structur...

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Section: The Study Areamentioning

confidence: 99%

Section: The Study Areamentioning

confidence: 99%

Section: The Study Areamentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Estimation of the susceptibility of a road network to shallow landslides with the integration of the sediment connectivity

Bordoni

Persichillo

Meisina

et al. 2018

Nat. Hazards Earth Syst. Sci.

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Metrics for quantifying anthropogenic impacts on geomorphology: road networks

Sofia

Marinello

Tarolli

2015

Earth Surf Processes Landf

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This work tests the capability of a recently published topographic index, the Slope Local Length of Auto‐correlation (SLLAC), to portrait and delineate anthropogenic geomorphologies. The patterns of the anthropogenic pressure are defined considering the road network density and the Urban Complexity Index (UCI). First, the research investigates the changes in the SLLAC in two derived parameters (average SLLAC and the SLLAC surface peak curvature – Spc – per km2) connected to the increasing of the anthropogenic structures. Next, natural and anthropogenic landscapes are clustered and classified. The results show that there is a direct correlation between the road network density and the UCI, and the mean SLLAC per km2. However, the Spc is inversely correlated with the anthropogenic pressure (network density and urban complexity). This shows that the surface morphology (slope) of regions presenting anthropogenic structures tends to be well organized (low Spc) and, in general, self‐similar at a long distance (higher average SLLAC). The results of the clustering approach show that the procedure can correctly depict anthropogenic landscapes having a road network density greater than about 3 km/km2, also in areas covered by vegetation. This latter result is promising for the use of such a procedure in regions that cannot be seen directly from orthophotos or satellite images. The proposed method can actively capture the alteration produced by road networks on surface morphology identifying different signatures of urban development: exploration and densification networks that are responsible for increasing the local density of the network and expanding the network into new areas, respectively. The effects of this alteration on surface processes could be significant for future research, creating new questions about differences due to human or landscape forcing on Earth surface processes. Copyright © 2015 John Wiley & Sons, Ltd.

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Exploiting Maximum Entropy method and ASTER data for assessing debris flow and debris slide susceptibility for the Giampilieri catchment (north‐eastern Sicily, Italy)

Lombardo

Bachofer

Cama

et al. 2016

Earth Surf Processes Landf

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This study aims at evaluating the performance of the Maximum Entropy method in assessing landslide susceptibility, exploiting topographic and multispectral remote sensing predictors. We selected the catchment of the Giampilieri stream, which is located in the north‐eastern sector of Sicily (southern Italy), as test site. On 1 October 2009, a storm rainfall triggered in this area hundreds of debris flow/avalanche phenomena causing extensive economical damage and loss of life. Within this area a presence‐only‐based statistical method was applied to obtain susceptibility models capable of distinguishing future activation sites of debris flow and debris slide, which where the main source of failure mechanisms for flow or avalanche type propagation. The set of predictors used in this experiment comprised primary and secondary topographic attributes, derived by processing a high resolution digital elevation model, CORINE land cover data and a set of vegetation and mineral indices obtained by processing multispectral ASTER images. All the selected data sources are dated before the disaster. A spatially random partition technique was adopted for validation, generating 50 replicates for each of the two considered movement typologies in order to assess accuracy, precision and reliability of the models. The debris slide and debris flow susceptibility models produced high performances with the first type being the best fit. The evaluation of the probability estimates around the mean value for each mapped pixel shows an inverted relation, with the most robust models corresponding to the debris flows. With respect to the role of each predictor within the modelling phase, debris flows appeared to be primarily controlled by topographic attributes whilst the debris slides were better explained by remotely sensed derived indices, particularly by the occurrence of previous wildfires across the slope. The overall excellent performances of the two models suggest promising perspectives for the application of presence‐only methods and remote sensing derived predictors. Copyright © 2016 John Wiley & Sons, Ltd.

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The influence of grid resolution on the prediction of natural and road-related shallow landslides

Cited by 56 publications

References 50 publications

Estimation of the susceptibility of a road network to shallow landslides with the integration of the sediment connectivity

Estimation of the susceptibility of a road network to shallow landslides with the integration of the sediment connectivity

Metrics for quantifying anthropogenic impacts on geomorphology: road networks

Exploiting Maximum Entropy method and ASTER data for assessing debris flow and debris slide susceptibility for the Giampilieri catchment (north‐eastern Sicily, Italy)

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