Slow-moving landslides are widespread natural hazards that can affect both social and economic activities causing damage to structures and infrastructure networks. This paper aims at providing an innovative simplified procedure to analyse road damage induced by slow-moving landslides based on the joint use of landslide inventory maps, a road damage database (collecting both the results of in-situ surveys and Google Street View images) and ground displacement measurements derived from the interferometric processing of satellite SAR images (DInSAR data). The procedure was applied to the case study of the Calabria region (southern Italy) following a two-scale approach. First, a regional-scale analysis was carried out to gather information on the level of road exposure (namely, Index of Exposed Roads) to slow-moving landslides in order to identify the most representative case studies. Then at local scale, relationships between road damage severity level and a selected parameter (i.e. differential settlement computed in two different ways) of slow-moving landslide intensity were derived for two road stretches that differ in geo-lithological and topographic conditions. The results underline the importance of the availability of both reliable landslide inventories and rich road damage databases as well as the potential of high-resolution DInSAR data for obtaining quantitative information on movement rates of roads useful to carry out in-depth studies pursing vulnerability analyses of the infrastructure.
Slow-moving landslides interacting with the road network: Analysis of damage using ancillary data, in situ surveys and multi-source monitoring data
2019
Abstract
Slow-moving landslides are widespread natural hazards that can affect both social and economic activities causing damage to structures and infrastructure networks. This paper aims at providing an innovative simplified procedure to analyse road damage induced by slow-moving landslides based on the joint use of landslide inventory maps, a road damage database (collecting both the results of in-situ surveys and Google Street View images) and ground displacement measurements derived from the interferometric processing of satellite SAR images (DInSAR data). The procedure was applied to the case study of the Calabria region (southern Italy) following a two-scale approach. First, a regional-scale analysis was carried out to gather information on the level of road exposure (namely, Index of Exposed Roads) to slow-moving landslides in order to identify the most representative case studies. Then at local scale, relationships between road damage severity level and a selected parameter (i.e. differential settlement computed in two different ways) of slow-moving landslide intensity were derived for two road stretches that differ in geo-lithological and topographic conditions. The results underline the importance of the availability of both reliable landslide inventories and rich road damage databases as well as the potential of high-resolution DInSAR data for obtaining quantitative information on movement rates of roads useful to carry out in-depth studies pursing vulnerability analyses of the infrastructure.File | Dimensione | Formato | |
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Descrizione: Slow-moving landslides interacting with the road network: Analysis of damage using ancillary data, in situ surveys and multi-source monitoring data
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