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SCIENCE FOR THE ENVIRONMENTAARHUS, DENMARK
3-4. OCTOBER 2013
General and particular social vulnerability to natural hazards in
PolandPiotr Werner
Paulina Pokojska, Patryk Korzeniecki, Bartłomiej IwańczakFaculty of Geography and Regional Studies, University of Warsaw,
Warsaw, PolandMichał Kowalewski
Institute of Meteorology and Water Management - National Research Institute,Warsaw, Poland
Partial results of research project: 'Spatial Differentiation of Information Society Vulnerability to Defined Environmental Hazards in Poland' (granted by Polish National Science Centre)
Aims
• Research project:Spatial Differentiation of Information Society Vulnerability to Defined Environmental Hazards in Poland (2012-2015)
• Aims:• measurement and evaluation of social vulnerability to identified,
chosen environmental hazards in Poland, taking into account the level of ICT development,
• Intermediate and partial result will be (now) presented• Research framework involves several certain natural hazards
according to set defined by Government Center of Security in Poland.
• floods, landslides, hurricanes (strong winds), severe frost, heat waves, droughts, storms (hail), forest fires, flu.
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State of art and methodological considerations (1)
• Concept of a natural hazard can be clearly distinguished from a natural disaster (Lisowski, 1993).
• Natural hazard: situation of equilibrium of system before disaster event.
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State of art and methodological considerations (2)
According to specialists - multi-dimensionality of the vulnerability to natural hazards rises from
• exposure (environmental), • susceptibility (socio-economic) • coping capacity (organizational or system) conditions
(Eq.1., Villagrán 2006). ∗ . 1
• Usually approach to assessment of risk of extreme natural phenomena involves convolution of natural hazards and vulnerability (Bankoff et al 2004).
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Geographical studies of vulnerability (1)
Geographical studies of vulnerability to defined natural hazards describe usually the specific conditions of natural phenomena and socio-economic characteristics of the defined regions, taking the form of hardly comparable for different hazards, complex geographical indices.
• Vulnerability to a given hazard depends on, inter alia (Nelson 2013):
• Proximity to a possible hazardous event; Population density in the area proximal to the event; Scientific understanding of the hazard; Public education and awareness of the hazard; Existence or non-existence of early-warning systems and lines of communication; Availability and readiness of emergency infrastructure; Construction styles and building codes;Cultural factors that influence public response to warnings”
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Geographical studies of vulnerability (cont)
• Gall (2007) included the following dimensions to be involved into social vulnerability indices:
• Populations at risk; Income; Gender; Race (ethnicity); Age (e.g. elderly, children); Unemployment; Dependence on social services; Residential property – renters; housing conditions; Infrastructure ;Occupation/working conditions; Family structure; Education; Culture (risk culture, experience); Place (incl. rural/urban dichotomy); Population growth; Special needs populations (e.g. marginalized, disabled); Commercial and industrial development; Built environment; Vulnerability Science; Governance (social capital);
• Other aspect stressed are sustainable livelihoods analysis which involve such dimensions as:
• Inequality; health; broader economic context (inflation, debt service, etc.); civil liberties; political rights; sustainable livelihoods analysis; environmental stewardship (ibid.)
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Quotes
• Donald Rumsfeld's (2002): • There are known knowns; there are things we know that
we know.• There are known unknowns; that is to say, there are
things that we now know we don't know.• But there are also unknown unknowns – there are things
we do not know we don't know.• might be applied to natural hazards and disasters and
supplemented with:• unknown knowns which means that people sometimes
knowingly ignore the hazard or disaster (Kundzewicz et al 2010)
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Linguistic operationalization• These statements seem a part of the multi-
valued logic of propositional calculus. • We can distinguish:
• lack of … (unknowns), tacit and explicit (formal) knowledge of natural hazards,
and, on the other side: • lack of … (unknowns), conscious (intuition) and
known(s) (recognized) - awareness of hazard phenomena (risks)
• awareness is based on past experiences of peopleexposed to hazards.
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Linguistic variables
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All above linguistic variables represent different situations which take place in different places and are related to product of two phenomena: • exposure to intensity (or frequency) of certain natural hazards • maturity of society i.e. level of preparedness (or susceptibility) to
certain hazards.
Table 1. Linguistic variables of the product of knowledge and exposure to natural hazards
Multi-valued logic(reminder)
• Jan Łukasiewicz (1920), Alfred Tarski - Polishlogicians, mathematicians and philosophers.
• Stephen C. Kleene• Lofti A. Zadeh – fuzzy set theory, fuzzy logic
(1975)• Procedures (Lee 2005) : fuzzification, knowledge
base and decision-making logic, defuzzification• measures of fuzziness (to define membership
function) that can be applied: entropy, metric distance, Hamming, Euclidean or Minkowskidistance.
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Formal representation (partial,1)
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Fig.1. Example of theoretical numerical product of fuzzy possibilities of certain hazard as a product of physical and social vulnerabilities (without coping capacity)
∗
Formal representation (partial,2)
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Fig. 2. Example of theoretical exponential result of fuzzy possibilities of certain hazard as a product of physical and social vulnerabilities (without coping capacity)
Intermediate results: study concerning EHE (Extreme Heat Events) and EHVI (Extreme Heat Vulnerability Index) in Poland
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Raw data
Fuzzification (crisp probabilities)
Knowledge base and decision-making logic
Defuzzifaction (EHVI) EHVI
Physical EHEExposure
EHE Frequency
EHE Number
Studylength
EHEIntensity
EHE Length Temperatures
SOVI
People
Children Elderlypeople
Populationdensity
Urbanization
Regions
Builtareas
Deforestedareas
Roadsdensity
Elements and spatial differentiationExtreme Heat Vulnerability Index
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Intermediate results: study concerning exposure and susceptibility to frosts and final Extreme Frost Vulnerability Index (EFVI) in Poland
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Raw dataRaw dataFuzzification
(crispprobabilities)
Fuzzification(crisp
probabilities)
Knowledgebase and decision-
making logic
Knowledgebase and decision-
making logicDefuzzificationDefuzzification
EFVIEFVI
EFEVIExposureEFEVIExposure
Exposure to frosts and hoarfrosts
Exposure to frosts and hoarfrosts
TemperaturesTemperatures
DurationDuration
TimeTime
VariationVariation
SOVISOVI
PeoplePeople
ChildrenChildren
Elderly peopleElderly people
UrbanizationUrbanization
Populationdensity
Populationdensity
RegionsRegions
Bulit areaBulit area
Deforestedarea
Deforestedarea
RoadsdensityRoadsdensity
Elements and spatial differentiationExtreme Frost Vulnerability Index
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Intermediate results: study concerning exposure and susceptibility to snow and final Snow Events Vulnerability Index (SEVI)
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Raw
dat
aR
aw d
ata
Fuzz
ifica
tion
(cris
ppr
obab
ilitie
s)Fu
zzifi
catio
n(c
risp
prob
abilit
ies)
Kno
wle
dge
base
and
de
cisi
on-m
akin
g lo
gic
Kno
wle
dge
base
and
de
cisi
on-m
akin
g lo
gic
Def
uzzi
ficat
ion
Def
uzzi
ficat
ion
SEVISEVI
SEVIExposureSEVI
Exposure
Exposure to snowcover
Exposure to snowcover
ThicknessThickness
DurationDuration
Growth rateGrowth rate
Melting rateMelting rate
SOVISOVI
PeoplePeople
ChildrenChildren
Elderly peopleElderly people
UrbanizationUrbanization
Populationdensity
Populationdensity
RegionsRegions
Bulit areaBulit area
Deforestedarea
Deforestedarea
RoadsdensityRoadsdensity
Elements and spatial differentiationSnow Events Vulnerability Index
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Intermediate results: study concerning exposure and susceptibility to wind and final Strong Winds Events
Vulnerability Index - SWEVI
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Raw
dat
a
Fuzz
ifica
tion
(cris
ppr
obab
ilitie
s)
Kno
wle
dge
base
and
de
cisi
on-m
akin
g lo
gic
Def
uzzi
ficat
ion
SWEVI
SWEVIExposure
VulnerabilityIndex
Exposure to winds
Velocity
Probability
Relief
Squalls
Whirlwinds
SOVI
People
Children
Elderly people
Urbanization
Populationdensity
Regions
Bulit area
Deforestedarea
Roadsdensity
Elements and spatial differentiationStrong Winds Events Vulnerability Index
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Intermediate results: study concerning exposure and susceptibility to hailstorms and final Hail Events Vulnerability Index in Poland
(HEVI)
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Raw
dat
a
Fuzz
ifica
tion
(cris
ppr
obab
ilitie
s)
Kno
wle
dge
base
an
d de
cisi
on-
mak
ing
logi
c
Def
uzzi
ficat
ion
HEVI
HEVIExposure
Exposure to hailstorms
Hail Events
PotentialHailstormsWeather
Conditions
SOVI Regions
Orchards area
Density of cars
Elements and spatial differentiationHailstorm Events Vulnerability Index
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Intermediate results: study concerning exposure and susceptibility to forest fires and final Forest Fires Vulnerability Index (FFVI)
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Raw
dat
a
Fuzz
ifica
tion
(cris
ppr
obab
ilitie
s)
Kno
wle
dge
base
an
d de
cisi
on-
mak
ing
logi
c
Def
uzzi
ficat
ion
FFVI
FFEVIExposure
Exposure to forest fires
Frequency
Foresttypes
AirHumidity
Dry ForestFloor Cond.
SOVI
People PopulationDensity
Regions Roadsdensity
Elements and spatial differentiationForest Fires Vulnerability Index
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Final remarks and to do listThe particular case studies and individual indices to certain hazards and their
social vulnerability counterparts indices have been presented as are, i.e. we are in the middle of the project and these intermediate results can be revisedafter the deep discussion. • Looking for appropriate formal representation of fuzzy possibilities (e.g.
xy, power(x,y), xy*power(xy)• Deep discussion concerning the selection of appropriate elements for
certain particular social vulnerability indices (SoVI) to defined hazards• Separation of common elements of (SoVI) and discussion concerning
the ability of construction of overall Social Vulnerability Index to natural hazards
• Discussion concerning the ability of construction of overall Physical Index of Exposure to natural hazards – may be divided into two ones –for warm and cold seasons.
• Comparison with measures concerning digital division of information society in Poland (which is out of the topic presented now).
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Thank You for attentionBankoff, Greg, Georg Frerks, i Dorothea Hilhorst. 2004. Mapping Vulnerability Disasters,
Development, and People. London; Sterling, VA: Earthscan Publications. http://search.ebscohost.com.
Gall, Melanie. 2007. Indices of social vulnerability to natural hazards: a comparativeevaluation. ProQuest.
Kundzewicz, Z.W., P. Matczak, i Z Sadowski. 2010. „Wprowadzenie do raportu o zagrożeniach” 4. Nauka. http://www.portalwiedzy.pan.pl
Lee, Kwang H. 2005. First course on fuzzy theory and applications. Advances in softcomputing. Berlin ; New York: Springer-Verlag.
Nelson, S.A. 2013. „Natural Disasters & Assessing Hazards and Risk”. Aug. 18. http://www.tulane.edu/~sanelson/Natural_Disasters/introduction.htm.
Villagrán de León, Juan Carlos, i United Nations University. Institute for Environment and Human Security. 2006. Vulnerability : a Conceptual and Methodological Review. Bonn, Germany: United Nations University, Institute for Environment and Human Security.
Zadeh, L.A. 1975. „The concept of a linguistic variable and its application to approximatereasoning—I”. Information Sciences 8 (3): 199–249. doi:10.1016/0020-0255(75)90036-5
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