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Orientador(es)
Resumo(s)
Landslides are well-known for their destructive capacity;
however, risk only exists if an interaction with people,
activities, structures and infrastructures occurs. When
landslides affect roads and potential human losses, both
road damage and road disruption can cause significant
economic losses. Therefore, in the framework of spatial
planning, civil protection, emergency and risk management and the evaluation of road network landslide
exposure is necessary. The primary goal of this work is
to assess the present road network exposure to
deep-seated and shallow slides at the Grande da Pipa
River basin (North of Lisbon region, Portugal), an area
naturally prone to geomorphological hazards. Our
approach to assessing road network exposure is sustained
by two different dataset inputs: (i) three landslide
susceptibility maps and (ii) one road network map. The
susceptibility to landslides, computed with the Information Value method and validated with success and
prediction rate curves, as well as with the estimation of
the area under the curves, was individually assessed for
deep-seated rotational, shallow rotational and shallow
translational slides. The road network exposure to each
landslide type resulted from the intersection between the
two top landslide susceptibility classes and the classified
road network according to its rank, allowing the critical
road sections to be identified. The road network is mainly
exposed to deep-seated rotational slides. However, the
other landslide types can also disrupt the road functionality and affect residents and economic activities.
Descrição
Palavras-chave
Deep-seated and shallow slides Road network Susceptibility Exposure Basin-scale
Contexto Educativo
Citação
Branco, I., Oliveira, S. C. & Melo, R. (2023). Road network exposure to deep-seated and shallow slides at the basin-scale (Grande da Pipa River Basin, Portugal). In: A. Malheiro, F. Fernandes, & H. I. Chaminé. (eds) Advances in Natural Hazards and Volcanic Risks: Shaping a Sustainable Future. NATHAZ 2022. Advances in Science, Technology & Innovation (pp. 115-119). Springe. https://doi.org/10.1007/978-3-031-25042-2_21
Editora
Springer
