A model for assessing the systemic vulnerability in landslide prone areas

被引:33
作者
Pascale, S. [2 ]
Sdao, F. [1 ]
Sole, A. [2 ]
机构
[1] Univ Basilicata, Dept Struct, I-85100 Potenza, Italy
[2] Univ Basilicata, Dept Environm Engn & Phys, I-85100 Potenza, Italy
关键词
URBAN AREA; SUSCEPTIBILITY; HAZARD;
D O I
10.5194/nhess-10-1575-2010
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
The objectives of spatial planning should include the definition and assessment of possible mitigation strategies regarding the effects of natural hazards on the surrounding territory. Unfortunately, however, there is often a lack of adequate tools to provide necessary support to the local bodies responsible for land management. This paper deals with the conception, the development and the validation of an integrated numerical model for assessing systemic vulnerability in complex and urbanized landslide-prone areas. The proposed model considers this vulnerability not as a characteristic of a particular element at risk, but as a peculiarity of a complex territorial system, in which the elements are reciprocally linked in a functional way. It is an index of the tendency of a given territorial element to suffer damage (usually of a functional kind) due to its interconnections with other elements of the same territorial system. The innovative nature of this work also lies in the formalization of a procedure based on a network of influences for an adequate assessment of such 'systemic' vulnerability. This approach can be used to obtain information which is useful, in any given situation of a territory hit by a landslide event, for the identification of the element which has suffered the most functional damage, ie the most 'critical' element and the element which has the greatest repercussions on other elements of the system and thus a 'decisive' role in the management of the emergency. This model was developed within a GIS system through the following phases: 1. the topological characterization of the territorial system studied and the assessment of the scenarios in terms of spatial landslide hazard. A statistical method, based on neural networks was proposed for the assessment of landslide hazard; 2. the analysis of the direct consequences of a scenario event on the system; 3. the definition of the assessment model of systemic vulnerability in landslide-prone areas. To highlight the potentialities of the proposed approach we have described a specific case study of landslide hazard in the local council area of Potenza.
引用
收藏
页码:1575 / 1590
页数:16
相关论文
共 50 条
  • [41] Assessing landslide susceptibility using Bayesian probability-based weight of evidence model
    Evangelin Ramani Sujatha
    P. Kumaravel
    G. Victor Rajamanickam
    Bulletin of Engineering Geology and the Environment, 2014, 73 : 147 - 161
  • [42] Assessment of landslide susceptibility, exposure, vulnerability, and risk in shahpur valley, eastern hindu kush
    Rahman, Ghani
    Bacha, Alam Sher
    Ul Moazzam, Muhammad Farhan
    Rahman, Atta Ur
    Mahmood, Shakeel
    Almohamad, Hussein
    Al Dughairi, Ahmed Abdullah
    Al-Mutiry, Motrih
    Alrasheedi, Mona
    Abdo, Hazem Ghassan
    FRONTIERS IN EARTH SCIENCE, 2022, 10
  • [43] Integration of Vulnerability and Hazard Factors for Landslide Risk Assessment
    Arrogante-Funes, Patricia
    Bruzon, Adrian G.
    Arrogante-Funes, Fatima
    Ramos-Bernal, Rocio N.
    Vazquez-Jimenez, Rene
    INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH, 2021, 18 (22)
  • [44] Understanding the effect of spatial patterns on the vulnerability of urban areas to flooding
    Sakieh, Yousef
    INTERNATIONAL JOURNAL OF DISASTER RISK REDUCTION, 2017, 25 : 125 - 136
  • [45] Assessing landslide susceptibility using Bayesian probability-based weight of evidence model
    Sujatha, Evangelin Ramani
    Kumaravel, P.
    Rajamanickam, G. Victor
    BULLETIN OF ENGINEERING GEOLOGY AND THE ENVIRONMENT, 2014, 73 (01) : 147 - 161
  • [46] Assessing population exposure for landslide risk analysis using dasymetric cartography
    Garcia, Ricardo A. C.
    Oliveira, Sergio C.
    Zezere, Jose L.
    NATURAL HAZARDS AND EARTH SYSTEM SCIENCES, 2016, 16 (12) : 2769 - 2782
  • [47] Cross-Validation of Logistic Regression Model for Landslide Susceptibility Mapping at Ganeoung Areas, Korea
    Hyun-Joo, Oh
    Saro, Lee
    DISASTER ADVANCES, 2010, 3 (02): : 44 - 55
  • [48] Modelling antecedent soil hydrological conditions to improve the prediction of landslide susceptibility in typhoon-prone regions
    Abanco, Claudia
    Asurza, Flavio Alexander
    Medina, Vicente
    Hurlimann, Marcel
    Bennett, Georgina L.
    LANDSLIDES, 2024, 21 (07) : 1531 - 1547
  • [49] Landslide Susceptibility Mapping by Neuro-Fuzzy Approach in a Landslide-Prone Area (Cameron Highlands, Malaysia)
    Pradhan, Biswajeet
    Sezer, Ebru Akcapinar
    Gokceoglu, Candan
    Buchroithner, Manfred F.
    IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2010, 48 (12): : 4164 - 4177
  • [50] Detecting fingerprints of landslide drivers: A MaxEnt model
    Convertino, M.
    Troccoli, A.
    Catani, F.
    JOURNAL OF GEOPHYSICAL RESEARCH-EARTH SURFACE, 2013, 118 (03) : 1367 - 1386