Director: Prof. dr. Iuliana ARMAS, University of Bucharest

Research Project:Research Project: Multihazard and vulnerability in the Multihazard and vulnerability in the

seismic context of the Bucharest seismic context of the Bucharest Municipality Municipality

COST Action TU0801: Semantic Enrichment of 3D city models for sustainable urban development

Acronym: HERA (HAZARD, EXPOSURE, RISK, ADAPTABILITY)

Research Partners• Faculty of Geography, Risk Research Center-

University of Bucharest, prof. dr. Iuliana Armas (Coord.)

• Faculty of Cybernetics - Academy for Economic Studies, prof. dr. Marian Dardala

• National Institute for Earth Physics, dr. Mircea Radulian

• Faculty of Civil, Industrial and Agricultural Constructions -Technical University of Constructions in Bucharest, prof. dr. Al. Aldea

OBJECTIVE of PHASE 2009OBJECTIVE of PHASE 2009

URBAN VULNERABILITY ASSESSMENT TO SEISMIC HAZARD THROUGH SPATIAL MULTI-CRITERIA ANALYSIS.  Overall Vulnerability = Total Vulnerability/Capacity Overall Vulnerability = Total Vulnerability/Capacity

where: the total vulnerability of the analysed urban space was considered as a function between the seismic susceptibility of the natural system and the susceptibility of the socio-human system to be affected by a seismic hazard; the capacity of the urban system to adapt and cope with disasters, was considered in the estimation of the overall vulnerability. The output map was classified in qualitative classes, comparing the histogram from the overall vulnerability.

Complex vulnerability is the central predictive variable in the risk equation. A half-century of experience in the natural risk field shows that the only effective way to diminish the natural risk is by reducing the vulnerability of natural and socio-economic systems. Although multiple definitions and different conceptual vulnerability frameworks have been proposed, it is still difficult to quantitatively estimate physical and social vulnerability.After a general evaluation through the SMCA method of the overall vulnerability of Bucharest city, a focused research on the most vulnerable area of the historic center was done with the development of a soft to filter, analyze and visualize the results.

Conceptual Background • Methodological FrameworkThe following terminology background outlines vulnerability and capacity

VulnerabilityVulnerability

“The conditions determined by physical, social, economic and environmental factors or processes, which increase the susceptibility of a community to the impact of hazards.” (UN/ISDR, 2004)

CapacityCapacity

“A combination of all the strengths and resources available within a community (...) that can reduce the level of risk or the effects of a disaster. “

(UN/ISDR, 2004)

• Study area• Bucharest, the capital of

Romania, is a populous city (1.9 mil.inhabitants – INSSE. 2009* ) located in the alluvial Romanian Plain .

• The total urbanized area is 228 km2

• The dwellings are part of 32 residential areas divided up into 6 sectors.

• Combining the natural and urban attributes, with the seismic hazard induced by Vrancea source, Bucharest has been ranked as the 10th capital city worldwide in the terms of seismic risk.

* National Institute of Statistics – ROMANIA

MethodologyMethodology

•The first step was to determine human vulnerability with the use of census data of population and housing, dated 2002 (Cutter et al. 2003; Dwyer et al. 2004).• The scale of analysis was considered at the level of census units (2002).

Composite Indicators Computed statistical variables based on census data (2002) Selected References 1.Environmntal Vulnerability

Average acceleration values for medium magnitude earthquakes (2002-2006), Average acceleration values for high magnitude earthquakes (1977, 1986, 1990)

Davidson, 1997; Bonjer et al., 1999; Mândrescu, N. and M. Radulian, 1999; Grecu et al., 2003; Radulian et al., 2006 a and b; HAZUS, 2007; Zaharia et al., 2008

2.Social vulnerability Ratio of elderly population, Ratio of female population in total population, Ratio of children, Ratio of widows in female population, Housing density, Average number of persons per household, Average number of wage earners per household, Minimum level of education, Women with 5 children and more

Slovic, 1992, Marris et al., 1995, Rohrmann, 1995; Flynn et al. 1994; Davidson, 1997; Davidson and Freudenburg, 1996; Fordham, 2000, Armaş, 2006, 2008a, 2008b, 2009

3.Economic Vulnerability of the Population and Housing quality

Percentage of unemployed, Ratio of low incomes and high incomes per mapping units, Degree of occupancy per room, Room area per person, Average area of rooms, Private residences with more than 5 rooms, Population density per residence

Granger et al., 1999; King and MacGregor, 2000, Wisner et al., 2004, Pelling, 2003, Dwyer et al., 2004; Eakin and Luers, 2006; Blaikie, Cannon et al, 1994; UN-ISDR, 2004

4.Building-stock vulnerability (Physical Vulnerability)

Residence density in building, Density of buildings per census units, Age and average height of buildings, type of buildings per census units (structure and building materials)

Sandi, 1986; Vacareanu et al., 2001; Cutter et al. 2003, Lungu et al., 2004; Ebert et al., 2009

5.Capacity Distance to hospitals, Distance to fire stations, distance to police stations (preparedness level), literacy rate (awareness level)

Dwyer et al., 2004; Dayton-Johnson. 2004; Birkmann, 2006; Bollin and Hidajat, 2006

• The next step consisted in database processing through a series of structure exploration techniques based on the cluster analysis and factorial reduction procedures. Both techniques revealed the “coagulation” of variables in factors. During the subsequent processing, the scores of the variables in which the selected factors are saturated were aggregated and applied in a standard Spatial Multi-Criteria Analysis (SMCA).

SVF = (Np + Nc + Nw5 + Nm.e.) - Nw.e.

Primary statistical variables: Computed statistical relative (non-dimensional) variables

Npt = Total no. of persons on census unit

(census population) Nh

t = Total no. of households on census unit Nc

t = Total no. of children on census unit Nw

t = Total no. of women on census unit Nw5

t = Total no. of women having 5 or more children on census unit Nm.e.

t = Total no. of persons with minimum education level on census unit Nw.e

t = Total no. of wage earners per household on census unit

Np = Average no. of persons per household = Np

t / Nht

Nc = Average no. of children on census unit = Nc

t / Npt

Nw5 = Average no. of women having 5 or more children on census unit = Nw5

t / Nwt

Nm.e. = Average no. of persons with minimum education level on census unit = Nm.e.

t / Npt

Nw.e. = Average no. of wage earners per household on census unit = Nw.e.

t / Npt

Complex social vulnerability factor (SVF) resulted from the factorial reduction procedure (PCA, Varimax)

The vulnerability of the housing quality (HQ) was calculated based on the formula: HQ = (Nr.a.

+ Np.a. + No5 ) – ( No + Nd)

The higher the value of this composite factor, the lower becomes the vulnerability of the area.

Primary statistical variables: Computed statistical relative (non-dimensional) variables

Nat = Total area of household rooms

(bedrooms, livingrooms) on census unit Nr

t = Total no. of rooms on census unit No

t = Total no. of private/owned households on census unit No5

t = Total no. of private/owned households with 5 or more rooms on census unit

Nr.a. = Average household room area on census unit = Na

t / Nrt

No = Room occupancy per household (average no. of persons per room) on census unit = Np

t / Nrt

Nd = Household population density (average no. of persons per household) on census unit = Np

t / Nht

No5 = Average no. of private/owned households with 5 or more rooms on census unit = No5

t / Not

Np.a. = Average room area per person on census unit = Na

t / Npt

The vulnerability of the economic level (EL) was calculated based on the formula:

EL = (Nu + Nl) – (Nh.m. + Nh.w.)

Primary statistical variables: Computed statistical relative (non-dimensional) variables

Nut = Total no. of unemployed persons (non-

wage-earners/unemployed) on census unit Nl

t = Total no. of low income wage earners on census unit Nm

t = Total no. of men on census unit Nh.m.

t = Total no. of high income wage earner men on census unit Nh.w.

t = Total no. of high income wage earner women on census unit

Nu = Relative no. of unemployed persons on census unit = Nu

t / Npt

Nl = Relative no. of low income wage earners on census unit = Nl

t / Npt

Nh.m. = Relative no. of high income wage earner men on census unit = Nh.m.

t / Nmt

Nh.w. = Relative no. of high income wage earner women on census unit = Nh.w.

t / Nwt

• Environmental Vulnerability

• Environmental Vulnerability

• the assessment was done based on the RADIUS methodology, in which Peak Ground Acceleration was calculated for 11 earthquake scenarios (the vulnerability hazard map compiling the average of the PGA values), and the amplification of soil was treated by simple multiplication values with the use of the 1:200000 Romanian geological map. Nevertheless, this method gives only a very general approximation of the hazard.

• focused on 4 groups of vulnerability indexes, selected according to the available data, the statistical results and the expert’s opinion: social vulnerability (aggregated social factor, elderly population, ratio of female population in total population, ratio of widowed persons, housing density), economic vulnerability (aggregated economic factor and housing quality), physical vulnerability (the assessment of the buildings) and environmental vulnerability (susceptibility to the seismic hazards). In addition, the coping and resilience capacity was estimated based on a Distance analysis to the hospitals, fire stations and police stations and, also, based on the literacy rate index.

• The (spatial) Multi-Criteria Analysis (SMCA)

• The (spatial) Multi-Criteria Analysis (SMCA)

Methodological flowchart

• Following the MCA standardization (goal and maximum standardization) was the estimation of the weights among groups of factors using pairwise comparison and ranking methods (Saaty, 1980; Janssen, 2001). • In the process, weights were multiplied with the standardised values and intermediate criteria maps were generated and combined using decision rules, for a better definition of the weights. • As a result, the total vulnerability index map was obtained by adding up the performance of all cell values of the human and environmental vulnerability criteria for the particular alternative.

• The (spatial) Multi-Criteria Analysis (SMCA)

• The (spatial) Multi-Criteria Analysis (SMCA)

ResultsResults

• Building-stock Vulnerability

• Building-stock Vulnerability

Structure

Averageheight

VuAverage density

The total vulnerability index map The total vulnerability index map for Bucharest cityfor Bucharest city

• resulted from the previous spatial composite indicators: social, economic and building stock vulnerability criteria, for describing the human vulnerability, and by adding the environmental vulnerability into the spatial multicriterial analysis. Green city areas and barren grounds were, also, included as spatial constraints.

• Capacity• Capacity• In order to measure the level

of capacity that would help reduce the overall vulnerability, two indicators were used: preparedness level (expressed through distance to hospitals, fire stations and police stations) and awareness level (based on the literacy rate).

• The best position is for the city central and pericentral areas (with very good accessibility to the emergency centers and scoring the highest values of the literacy rate).

The overallThe overall vulnerability index vulnerability index map for Bucharest citymap for Bucharest city

• it was calculated by dividing the total human vulnerability values to the capacity composite factor. • the configuration reveals a radial spatial pattern with values increasing from the central to the marginal areas. • The historic city center scores high based on the building stock vulnerability criteria and the environmental vulnerability level to the seismic hazard. Frequently, brick buildings are in poor repair, and many of them are in total ruin today. A population of modest means now inhabits these buildings. Most of the buildings are included in categories of the greatest seismic vulnerability, and were built between 1875 and 1940.

Study area

(1977)

Editing building

81%/ out of brick

16%concrete

3% timber work/ other materials

Building materials of residential houses

1%

24%

75% / private households

public property

property of religious cults

Ownership of households

ResultsResults

StreetsContour lines

18%

17%

42%7%9% 6%

1%

Age and costs of buildings

Before 1977

1920/1940

XIXth century

XXth century

XIXth century, renovated

A very good state / a building that is completely restored or new;A good state / a building that is partially restored or not restored, but with the plaster damaged less than 15%;

A bad state / a building that is not restored, with deep fissures and the plaster damaged from 20% to 55%;

A very bad state / a building that is not restored, often uninhabited, with broken windows or lacking windows and the plaster damaged over 60%;

Ruin

The state of buildings

24%bad state 50%

very good state

13%very good

state

13%very bad

state

56%female

44%male

16%45%

39%

70-90 years

36-69 years

0-35 years

10%

16%

13%

61%

By dividing the number of persons that live in the buildings having a maximum probability of being seriously damaged with the total population number, results an exposure index of 0.49, which shows that almost half of the inhabitants of this sector undergo the maximum danger of being injured, losing their lives and/or all their possessions.

Demographic Assessment

•was based on the matrix approach between the vulnerability factors of the buildings (resulted from the factorial analysis), their condition and the function of the edifices, on the principle of a differentiated degree of occupancy during the day.•The spatial analysis indicates a reduced vulnerability concerning the buildings with financial-banking and cultural functions, built in the inter-war period, many of them being renovated. •Maximum vulnerability levels define the old houses, litigated, many of them being in an advanced state of degradation or even ruins and also defines the inter-war apartment houses, unfunded, with many inhabitants and large commercial spaces at the ground floor.

Vulnerability Assessment

Low

High

Vulnerability

LegendVery low riskLow riskMedium riskHigh riskVery high risk

Earthquake Risk Assessment(Direct Costs)Risk was computed on the basis of the combination of the vulnerability and the value of the elements at risk (buildings), following a contingency matrix approach.

StreetsContour lines

21%, very low

14%

26%, medium

36%high

3% v. high

Risk to lifeIn a day scenario In a night scenario

Day Night+5%

+13%

-16%

-2%

54%

16%

5%

25%

67%

21%9%3%

High risk: a nr of over 100 people in buildings that can be affected up to 30% or a max. of 50 people in unsafe buildings.Very high risk: a nr of over 50 people in unsafe buildings.

Conclusions

The flaws of the methodological approach developed consist of a implicit degree of subjectivity and in the possibility of errors to appear because of the numerous classifications needed that rely strongly on the competence of the specialists. The SMCA-method is based on Vulnerability indices with no direct relation with the different hazard intensitiesThe informational system created can be considered an adequate instrument to evaluate vulnerability and risk, and to fit the needs of a susceptible population based on:

- an extended range of applicability; - the short processing period; - accessibility;- capacity of support for a large amount of information

Selected ReferencesArion C., Vacareanu R., Lungu D.: (2004), WP10 - Application to Bucharest, RISK-UE. An advanced approach to earthquake risk scenarios with applications to different European towns. At ftp.brgm.fr/pub/Risk-UE.Birkmann, J. (Ed.) (2006), Measuring Vulnerability to Hazards of Natural Origin, Towards Disaster Resilient Society.UNU Press, Tokyo.Global Review of Disaster Reduction Initiatives. (2004 version). United Nations, Geneva, p. 430.Grecu, B., M. Popa, M. Radulian, (2003). Seismic ground motion characteristics in the Bucharest area: Sedimentary cover versus seismic source control, Romanian Reports in Physics, 55, 511-520.HAZUS – Technical Manual (1997). Earthquake Loss Estimation Methodology, 3 Vol.Janssen R (2001) On the use of multi-criteria analysis in environmental impact assessment in The Netherlands. J Multi-Criteria Decis Anal 10:101–109King, D., MacGregor, C., (2000), Using social indicators to measure community vulnerability to natural hazards. Australian Journal of Emergency Management, 15(3): 52–57.Lungu, D., Aldea, A., Arion, C., Cornea, T., Vãcãreanu, R. (2004), RISK-UE, WP1: European Distinctive features, inventory database and typology, Proceedings of the International Conference “Earthquake Loss Estimation and Risk Reduction” 24-26, Oct. 2002, Bucuresti, Vol. 2, Romania, pp. 251-272.Mândrescu, N., M. Radulian, (1999). Seismic microzoning of Bucharest (Romania): A critical review”, Vrancea Earthquakes: Tectonics, Hazard, and Risk Mitigation, Editors: Wenzel, F., Lungu, D., O. Novak, Kluwer Academic Publishers, 109-122.RISK-UE, An advanced approach to earthquake risk scenarios with applications to different European towns , Fifth Framework Programme of the European Commission, 2000-2004.Saaty TL (1980) The analytic hierarchy process. McGraw-Hill International Book Company, New YorkUN/ISDR (United Nations International Strategy for Disaster Reduction) (2004), Living with Risk. A Global Review of Disaster Reduction Initiatives. 2004 version. United Nations, Geneva, p. 430. . UNEP (2002), Global Environment Outlook 3 – Past, Present and Future Perspectives.Earthscan Publications Ltd, London, United Kingdom, p. 426.Yeh C, Willis R, Deng H, Pan H (1999) Task oriented weighting in multi-criteria analysis. Eur J Oper Res. 119:130–146.Zaharia, B., M. Radulian, M. Popa, B. Grecu, A. Bǎlǎ and D. Tǎtaru, (2008). Estimation of the local response using Nakamura method for Bucharest area, Romanian Reports in Physics, 60, 1, 131-144.