Análise da vulnerabilidade das edificações em áreas afetadas por movimentos de massa

A ocorrência dos movimentos de massa pode assumir distintas grandezas diante do número de mortes e dos severos danos sociais e ambientais para a região afetada. Diferentes esforços têm sido empregados para avaliar os impactos destes processos e dentre eles estão os métodos de cartografia de risco como o mapeamento da vulnerabilidade das edificações. O objetivo do trabalho é analisar a vulnerabilidade das edificações e sua distribuição espacial na área urbana do município de Itaoca (SP) afetado por fluxo de detritos e lama em janeiro de 2014. Foi empregado o método PTVA (Papathoma Tsunami Vulnerability Assessment) sendo adotados os seguintes critérios: número de pavimentos, distância do canal (<30m), existência de muro de alvenaria e tipo de material. Os resultados revelaram que a maioria das edificações tem um valor alto de vulnerabilidade (>0,83), sendo que a ausência de muros de alvenaria é o critério de maior peso. A espacialização registrou uma Baixa Vulnerabilidade para um pouco mais de 14% da área, e Muito Alta Vulnerabilidade para aproximadamente 10%. As classes Média e Alta marcaram 39% e 35%.

A revised (PTVA) model for assessing the vulnerability of buildings to tsunami damage

Natural Hazards and Earth System Science ◽

10.5194/nhess-9-1557-2009 ◽

2009 ◽

Vol 9 (5) ◽

pp. 1557-1565 ◽

Cited By ~ 52

Author(s):

F. Dall'Osso ◽

M. Gonella ◽

G. Gabbianelli ◽

G. Withycombe ◽

D. Dominey-Howes

Keyword(s):

Analytic Hierarchy Process ◽

Original Model ◽

Building Vulnerability ◽

Analytic Hierarchy ◽

Tsunami Damage ◽

Vulnerability Of Buildings ◽

Tsunami Vulnerability Assessment ◽

Hierarchy Process ◽

Sydney Australia

Abstract. The Papathoma Tsunami Vulnerability Assessment (PTVA) Model (Papathoma, 2003) was developed in the absence of robust, well-constructed and validated building fragility models for assessing the vulnerability of buildings to tsunami. It has proven to be a useful tool for providing assessments of building vulnerability. We present an enhanced version (PTVA-3) of the model that takes account of new understanding of the factors that influence building vulnerability and significantly, introduce the use of the Analytic Hierarchy Process (AHP) for weighting the various attributes in order to limit concerns about subjective ranking of attributes in the original model. We successfully test PTVA-3 using building data from Maroubra, Sydney, Australia.

A 3-tier tsunami vulnerability assessment technique for the north-west coast of Peninsular Malaysia

Natural Hazards ◽

10.1007/s11069-012-0166-9 ◽

2012 ◽

Vol 63 (2) ◽

pp. 549-573 ◽

Cited By ~ 6

Author(s):

H. Ismail ◽

A. K. Abd Wahab ◽

M. F. Mohd Amin ◽

M. Z. Mohd Yunus ◽

F. Jaffar Sidek ◽

...

Keyword(s):

West Coast ◽

Peninsular Malaysia ◽

Assessment Technique ◽

North West ◽

The North ◽

Tsunami vulnerability assessment and its implications for coastal hazard analysis and disaster management planning, Gulf of Corinth, Greece

Natural Hazards and Earth System Science ◽

10.5194/nhess-3-733-2003 ◽

2003 ◽

Vol 3 (6) ◽

pp. 733-747 ◽

Cited By ~ 76

Author(s):

M. Papathoma ◽

D. Dominey-Howes

Keyword(s):

Disaster Management ◽

Hazard Analysis ◽

Assessment Method ◽

Case Scenario ◽

Management Planning ◽

Gulf Of Corinth ◽

Run Up ◽

Tsunami Vulnerability Assessment ◽

Disaster Management Planning

Abstract. We apply a new tsunami vulnerability assessment method to two coastal villages in the Gulf of Corinth, Greece using the 7th February 1963 tsunami as a worse case scenario. In Akoli, 46.5% of all buildings are classified highly vulnerable (BV). Approximately, 26.3% of all households are located within buildings with a High BV classification whereas 85% of all businesses are located within buildings with a High BV classification and 13.7% of the population is located within buildings with a High BV classification. In Selianitika, 28.8% of all buildings are classified with a High BV and 11% of all households are located within buildings with a High BV classification. Also 29.3% of all businesses and 33.4% of all services are located within buildings with a High BV classification and 6.7% of the population is located within buildings with a High BV classification. We estimate the minimum costs of a hypothetical tsunami with a wave run-up (H(m)max) of + 5 m. The results are considered significant because they have important implications for coastal risk assessment, resource allocation and disaster management planning.

Natural resources and environment Composite methodology for tsunami vulnerability assessment based on the numerical simulation of 1755 Lisbon tsunami—application on two Portuguese coastal areas

Safety and Reliability: Methodology and Applications ◽

10.1201/b17399-218 ◽

2014 ◽

pp. 1617-1624

Keyword(s):

Numerical Simulation ◽

Natural Resources ◽

Coastal Areas ◽

Tsunami vulnerability assessment in urban areas using numerical model and GIS

Natural Hazards ◽

10.1007/s11069-011-9957-7 ◽

2011 ◽

Vol 60 (1) ◽

pp. 135-147 ◽

Cited By ~ 9

Author(s):

Tune Usha ◽

M. V. Ramana Murthy ◽

N. T. Reddy ◽

Pravakar Mishra

Keyword(s):

Numerical Model ◽

Urban Areas ◽

Tsunami Vulnerability Assessment and Its Implications for Disaster Risk Management in the coastal area of Purworejo Regency

IOP Conference Series Earth and Environmental Science ◽

10.1088/1755-1315/884/1/012012 ◽

2021 ◽

Vol 884 (1) ◽

pp. 012012

Author(s):

Tanasiva ◽

Chatarina Muryani ◽

Pipit Wijiyanti

Keyword(s):

Risk Management ◽

Social Vulnerability ◽

Subduction Zones ◽

Disaster Risk ◽

Disaster Risk Management ◽

Vulnerable Communities ◽

The Indian Ocean ◽

Productive Land ◽

Abstract Tsunamis are disasters with unpredictable events, but the occurrence of tsunamis in Indonesia always has a significant impact on every sector of life, especially the economy and society. The position of the Indonesian State, which is located in the subduction zones as well as the increasing human activity in coastal areas, are the factors that trigger the tsunami, which is accompanied by losses and damages. One of them is Purworejo Regency, which is directly adjacent to the Indian Ocean. Vulnerability assessment is the focus of this paper. This study uses a quantitative analysis approach with analytical methods in the form of scoring analysis. Weighted cell-based data processing is the main cog in vulnerability assessment. The combination of economic and social parameters creates a vulnerability. Financial vulnerability is measured based on GRDP and productive land, while social vulnerability is estimated based on population density and vulnerable communities. The vulnerability analysis results are in the form of total vulnerability level in the medium class, the level of economic vulnerability in the low, quality, and social vulnerability in the medium class associated with the implication of disaster risk management.