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Background of the problem
Some inactive landslides had been recently re-activated in a study area.
Answering these questions is the target of this contribution
Illustrated by using the Bonn Case Study, Germany and Fuzzy SetModel, a typical spatial prediction model.
Open Questions Of the remaining inactive landslides, which ones are likely be re-activated near
future?
In answering the question using spatial modeling, should we use the activelandslides only or both groups of active and inactive ones?
Why?
Chung C.-J.. & Glade T. (2004): Use of Active and Inactive Landslides for Spatial Landslide Hazard Modeling.-Presentation givenat the EGU conference in Nice, April 2004
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Bonn Case Study, Germany
23 active landslides1983 pixels
45 inactive landslides4064 pixels
23 active landslides arereactivated landslides
Bedrock geology
DEM consisting ofSlope angles,Elevations, andAspects angles
10m x 10m pixels
1,074,440 pixels instudy area (107 squarekm)
Chung C.-J.. & Glade T. (2004): Use of Active and Inactive Landslides for Spatial Landslide Hazard Modeling.-Presentation givenat the EGU conference in Nice, April 2004
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Landslide distributions
23 active landslides scars,1983 pixels
45 inactive landslides scars, 4064pixels
Bedrock geology map
DEM consisting of
Slope angles,Elevations, andAspects angles
10m x 10m pixels
1328 pixels x 1298 lines
1,074,440 pixels in study area(107 square km)
Non-landslide area 1,068,393pixels
Chung C.-J.. & Glade T. (2004): Use of Active and Inactive Landslides for Spatial Landslide Hazard Modeling.-Presentation givenat the EGU conference in Nice, April 2004
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Empirical distribution functions (histograms) of slope angles:1. 23 active landslides (1983 pixels) Red curve
2. 45 inactive landslides (4064 pixels) Blue curve
3. All 68 landslides (6047 pixels) Green curve
4. Remaining area (1,068,393 pixels) black curve
Emprical frequency distribution functions of slope angles
0.000
0.002
0.004
0.006
0.008
0 10 20 30 40
Slope angle in degree
Normalisedfrequency Inactive landslides
Acti ve l andslid es
All lan dsli des
Non-landslide area
Slope angles, a topographical characterization
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Empirical distribution functions (histograms) of elevation:1. 23 active landslides (1983 pixels) Red curve
2. 45 inactive landslides (4064 pixels) Blue curve
3. All 68 landslides (6047 pixels) Green curve
4. Remaining area (1,068,393 pixels) black curve
Emprical frequency distribution functions of elevations
0.000
0.001
0.002
0.003
0.004
0.005
0 50 100 150 200 250 300
Elevation in m
Norma
lise
dfrequency
Inactive landslides
Active l andsli des
All landsl ides
Non-landslide are a
Elevation, a topographical characterization
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Empirical distribution functions (histograms) of elevation:1. 23 active landslides (1983 pixels) Red bars
2. 45 inactive landslides (4064 pixels) Blue bars
3. All 68 landslides (6047 pixels) Green bars
4. Remaining area (1,068,393 pixels) black bars
0.00
0.05
0.10
0.15
0.20
0.25
0.30
0.35
1 3 5 7 911
13
15
17
19
21
23
25
27
29
31
33
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Bedrock types
Norma
lize
dfrequency
Acti ve la nd sli de s
Inactive landslides
All la nd sli de s
Non-landslide are a
Bedrock Geology, a geological characterization
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75%
Top 1%2,5 - 5%10 - 15%
20 - 25%
50%
Prediction
23 active
107,444 km2
1,0% 1,07 km2
2,5% 6,80 km2ChungC-JF & Glade T (2004) Useof active andinactive landslides for spatial landslide hazardmodelling.- In: EGU, 26.-30 April 2004, Nizza, France
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75%
Top 1%2,5 - 5%10 - 15%
20 - 25%
50%
Prediction45 inactive
107,444 km2
1,0% 1,07 km2
2,5% 2,68 km2
Chung & Glade (2004)
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InactivelandslidesWITHOUT
expectedreactivation
InactivelandslideswithPARTIALLY
expectedreactivation
SCENARIO:Susceptibility map calculated withactive landslides and combined with locations of
currently inactive landslides
A
A
D C
B
B
D C
Top 1% area5.0-10.0%
20.0-25.0%
30.0-60.0%
Chung & Glade (2004)
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Resolution of data sets example DHM
1m 5m 10m
20m 50m 100m
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Of 45 inactive landslides, 37 expected to re-activate. Two (inpink circles) expected to partially re-activated, while only sixlandslides (in black circles) NOT expected to re-activate.
Active landslides help identifying which ones will re-activate.
Fuzzy sets are valuable tools however experiments with logisticdiscriminant analysis and likelihood ratio models providesimilar results
Concluding remarks
Chung C.-J.. & Glade T. (2004): Use of Active and Inactive Landslides for Spatial Landslide Hazard Modeling.-Presentation givenat the EGU conference in Nice, April 2004
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Example of the Swabian Alb, Germany- a contrast: the geometrical approach
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Example of the Swabian Alb, Germany
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Example of the Swabian Alb, Germany
Preliminary results of the InterRISK project
Local and regional landslide risk analysis
Aims of the study
Geomorphological and soil mechanical investigation of asingle landslide
Measurement and modeling of recent kinematics Analysis of climatic thresholds
Natural hazard modeling
Risk analysis (R = H x E x V)
Coupling of local and regional results => upscaling
Validation of regional results using statistical methods andhistorical data
Integrative risk management
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Study areas
Regional: ca. 2000 km
Regional 2: ca. 400km
Local:
Mssingen schingen (1)
Lichtenstein -Unterhausen (2)
Irrenberg (3) (planned)
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Preliminary results: local scale Mssingen-schingen
rotational and translational slides
various ages and magnitudes
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Preliminary results: local scale Mssingen-schingen
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Investigation
Oes 1
Oes 3
Oes 2
Plateau schingen linear structures linear arranged small dolines => linear network of fissures?
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Scenarios of complex landslide evolution
1.5 Mio m
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Evolution of a complex landslide
17 Mio. m
5 Mio m
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21DOP, Source: Landesvermessungsamt Baden-Wrttemberg(www.lv-bw.de), AZ.: 2851.9-1/11
DEM, Source: Kreja, R., Uni Tbingen
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Common limitation of landslide hazard assessments
No information on potential landslide volume
One solution: Sloping Local Base Level (SLBL)
Assumptions
All undercut slopes are unstable on a longterm scale
These slopes can be detected from a DTM by the SLBL
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Sloping Local Base Level (SLBL)
Iterative routine Lowers each point of the DTM located above the average altitude
of two opposite points among its four direct neighbours untilconvergence is reached(Jaboyedoff et al. 2004, 2005)
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Study area schingen
0 400m
DOP, Source: Landesvermessungsamt Baden-Wrttemberg(www.lv-bw.de), AZ.: 2851.9-1/11
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Study area schingen
5m DEM
Source: Kreja, R.,Uni Tbingen
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SLBL profile spur
400
500
600
700
800
900
1000
0 200 400 600 800 1000 1200 1400
Length (m)
Height(m)
P1_slbl
P1_orig
Profile
Legend
landslide thickness (m)
>1 - 10
>10 - 20
>20 - 30
>30 - 40>40 - 50
>50 - 60
>60 - 70
>70 - 80
>80 - 100
Sliding of whole spur
DOP, Source: Landesvermessungsamt Baden-Wrttemberg(www.lv-bw.de), AZ.: 2851.9-1/11
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Profile
SLBL profile spur front
400
500
600
700
800
900
1000
0 200 400 600 800 1000 1200 1400
Length (m)
Height(m)
P1_slbl
P1_orig
Legend
landslide thickness (m)
>1 - 10
>10 - 20
>20 - 30
>30 - 40
>40 - 50
>50 - 60
>60 - 70
>70 - 80
>80 - 100
Sliding of spur front
DOP, Source: Landesvermessungsamt Baden-Wrttemberg(www.lv-bw.de), AZ.: 2851.9-1/11
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Profile
SLBL profile lowest landslide block
400
500
600
700
800
900
1000
0 200 400 600 800 1000 1200 1400
Length (m)
Height(m)
P2_slbl
P2_orig
Legend
landslide thickness (m)
>1 - 10
>10 - 20
>20 - 30
>30 - 40>40 - 50
>50 - 60
>60 - 70
>70 - 80
>80 - 100
Sliding of lowest landslide block
DOP, Source: Landesvermessungsamt Baden-Wrttemberg(www.lv-bw.de), AZ.: 2851.9-1/11
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17 Mio. m
5 Mio. m1.5 Mio. m
Volume estimation whole spur
spur frontlowest landslide block
Legend
landslide thickness (m)
>1 - 10
>10 - 20
>20 - 30
>30 - 40
>40 - 50
>50 - 60
>60 - 70
>70 - 80
>80 - 100
DOP, Source: Landesvermessungsamt Baden-Wrttemberg(www.lv-bw.de), AZ.: 2851.9-1/11
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Applied Methods for validation
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Validation of SLBL results
Sass, Bell & Glade (submitted)
2D-resistivity
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Spatial distribution of landslides trigger????
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Classification 1 Classification 2
Logistic RegressionGeomorphometry 50m (Height, slope, aspect)GeologySoilsLandslide locations (Uni Tbingen)
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SLBL at regional scale
36Land use data provided by Blchl & Braun, InterRISK Assess
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Spatial distribution of landslides Rainfall????
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Conclusion
First results of the SLBL are very promissing
The shear plane for different landslide scenarios can bemodelled in 3D
SLBL can reliably estimate potential landslide volume
SLBL can be applied at local and regional scale Integration of lanslide volume in local and regional landslide
hazard assessment will lead to significant improvements
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Use of landslide risk maps in landuse planningand restrictive zoning
PD Dr. Thomas Gladethomas.glade@uni-bonn.de
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Risk assessment & management (1/3)
P robability oflandsliding
Triggeringfactors
Landslideinventory
P reparatoryfactors
Hazardassessment
Runoutbehavior
Land use
E lements atrisk
Vulnerabilityassessment
Riskassessment
Riskmanagement
C ost-benefitanalysis Dai et al. (2002)
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Lecture Overview
Risk management Risk management and spatial planning
Risk assessment
protection objects
Acceptable and tolerable risk
Risk treatment options
Strategies for risk reduction
Efficiency of mitigation measures
Contribution of spatial planning to risk managementstrategies
Natural hazards in land use plans
Some preliminary findings of ARMONIA on spatialplanning & risk
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.... Everything a question of management?
Risk-perception
Risk-management
Risk-evaluation
Cartoon: Sidney Harris
Weichselgartner J (2003): Risiken im Naturrisikomanagement: Herausforderungen einer politikrelevanten Naturgefahrenforschung.- 54. DeutscherGeographentag Bern, FS 11 'Katastrophenvorsorge als Thema der Hazard- und Risikoforschung'
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Definitions of risk management
Application of measures and methods to achieve thetargeted security and to adapt security planning tochanging circumstances. Risk managementcomprehends risk control and risk communication.
(BUWAL, 1999)
The process of weighting policy alternatives in thelight of the results of risk assessment and, if required,selecting and implementing appropriate control
options, including regulatory measures.(FAO, 1997)
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Risk management development
Risks used to be treated technically (Greiving, 2002)
Focusing on defence of risks
E.g. disaster management originated during the cold war(planning for nuclear war/bomb shelters) (Pearce, 2003)
Influence on probability of events influence on damage
potential Sustainable Development => greater focus on prevention
Shift of paradigm towards risk and disaster management
Spatial planning as an important actor
Partly due to technical and economical limitations ofdefence of risks (Greiving, 2002)
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Shift in management strategies
Salter, 1998 in Pierce, 2002
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Risk management & spatial planning
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Risk management & spatial planning
Natural disasters are typical examples of people living inconflict with the environment
The vulnerability of populated areas to natural disaster ispartly a consequence of decades of spatial planningpolicies that have failed to take account of hazards andrisks in land use zoning and development decisions
Spatial planning as one important actor plays animportant role for the prevention of natural hazards by:
Selecting the areas most suitable for further urbandevelopment
Restricting future development in areas at risk(Greiving, 2005)
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Risk management & spatial planning
There is a need to develop a more effective methodologyto incorporate:
Natural hazard assessment and disaster reduction intospatial planning
Knowledge, technology and actors in the field of risk
assessment and land use zoning(Greiving, 2005)
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What is safe?
Before risk is managed, risk needs to be assessed
Definition of protection objects
Definition of acceptable and tolerable risk
acceptable risk of a single individual
acceptable risk of the whole population
acceptable risk of objects
Giovanni Crosta
Residual Risk!!!!!
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Protectionobjectives &planning
Utilisation Hazard
Protectionobjectives
Lack ofprotection
Sufficientprotection
Protection ofactual state
Action planning
Actions technically,economically &
ecologicallyproportional ?
Implementation ofaction
& emergency plans
Yes
No
Correction ofgoal of
protection/utilisation
Adapted from KAWA, TBA &AGR, 1999
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Acceptable and tolerable risk
Who defines acceptable risk level?
Differs from country to country, region to region,
Formation of opinion in socio-political discourse
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Acceptable and tolerable risk
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Risk treatment options
Accept the risk
Avoid the risk
Reduce the likelihood
Reduce the consequences
Monitoring and warning systems
Transfer the risk
Postpone the decision
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Strategies for risk reduction
1. Increasing of social acceptable threshold risk
2. Mitigation of risk through structural action to hazardreduction
3. Mitigation of risk through non structural action topotential damage reduction
The total risk evaluation, (in terms expected annualcost of damage), permits to choose through differentmitigations strategies with cost-benefit analysis. Byevery single cost of each action, a benefit in terms ofrisk reduction should be associated, expressed by thereduction of annual cost of landslide damage.ARMONIA Project report, 2005
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Increasing of social acceptable threshold risk (1/2)
It is very seldom that local governments attempt toeducate the public to the hazards that threaten them(Aguirre, 1994)
But: (Drabek, 1986)
Surveys indicate that the public would welcome suchefforts
Relationship between the degree to which communitiesaccept disaster management planning and to the degree to
which they experience disasters
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Increasing of social acceptable threshold risk (2/2)
Instruments for awareness campaigns:
use of mass media communication
diffusion of informative brochures that describe the kindof risk and the behavior to assume in case of alarm andemergency
assemblies and meetings with administrations andstakeholders
installation of hazard signage
stipulation of insurance for damage coverage
ARMONIA Project report, 2005
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Mitigation of risk through structural action to
hazard reduction Reduction of the triggering factors
Land use reclamations and hydrological and geologicalenvironmental restoration work
rationalisation of land use and agricultural activities
Direct intervention on active landslides in order toprevent remobilisation and control the evolution
Stabilisation works designed to reduce the mobilisation
forces (slope re-profiling, detachment of unstable blocks)or increase resistant forces (i.e. drainage, chemical andphysical treatment, concrete injection, walls, nails,anchors, bolts, piling)
=> Usually of high costsARMONIA Project report, 2005
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Mitigation of risk through non structural action topotential damage reduction
Reduction of the potential damage
Acting on elements at risk and vulnerability
Delocalisation of EE
Limitation of urban expansion
Land use definition of unstable areas
Implementation of technical measures or restrains
More flexible than structural measures
=> Usually lower costs ARMONIA Project report, 2005
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Efficiency of mitigation measures (1/2)
Usually done in cost-benefit analysis
Evaluation of protection objects and acceptable risk
Definition of maximal costs for risk reduction(depending on the element at risk)
(Hollenstein, Merz, Bhler, 2004)
benefit
tEfficiency
cos=
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Efficiency of mitigation measures (2/2)
Example (Adapted from BUWAL, 1999):
If a landslide hits a road it will cause 0.05 deaths/year
Through geotechnical measures the risk will be reduced to0.01 deaths/year
Cost for the measures: 5 million US$
Expected durability: 50 years
=> yearly cost of measures: 100.000 US$ (w/o discounting)
=> Risk reduction costs = Costs for measures/risk reduction
lifesavedperlifesaved
treductionrisk 000.500.2*)01.005.0(
000.100cos =
=
Proportional or not ?
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Non-landslide specific contribution of spatial
planning to risk management
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Possibilities topresent naturalhazards in landuse plans
EPSON Hazardsproject report, 2006
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LandslidesDamages following the event on 2-6 November 1994 in the Piemonte
Region, Northwest Italy
Photographs: Casale & Margottinieds., 1996
Photographs: Regione Piemonte, 1998
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Some preliminary findings of ARMONIA onspatial planning & risk
Spatial planning is not responsible for undertakingrisk assessment, but makes use of the results provided
by sectoral planning.
However, the relevance of risk assessment for spatial
planning has to be readjusted again: Spatial planningnormally needs only hazard information; risk andvulnerability are only important in a few extremesituations (e.g. where relocation of existingdevelopment is being considered).
Greiving, 2005
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Some preliminary findings of ARMONIA on
spatial planning & risk For risk management (non-structural mitigation
activities), only the vulnerability of the differentobjects to be protected is, in general, of relevance(e. g. the different type of land-uses or the differenttypes of buildings).
In contrast, structural mitigation and emergencyplanning need information about the existingvulnerability. This information has to be seen as a
basis for the analysis of costs and benefits of givenalternatives or evacuation plans.
Greiving, 2005
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Some preliminary findings of ARMONIA onspatial planning & risk
In consequence, the further scientific work shouldconcentrate on the optimisation and harmonisation ofhazard assessment, which is principally needed forthe daily, routine practice of spatial planning.
For extreme situations of high hazard and likelihoodwhere the relation of existing population anddevelopment is being considered; further work shouldmake use of an existing multi-risk approach whichcan be adopted for spatial planning. Here, the need toagree on a common definition of vulnerability hasto be seen as crucial.
Greiving, 2005
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Some preliminary findings of ARMONIA on
spatial planning & risk Spatial scales: Hazard information is needed on two
different scales: a regional and a local one. Inconsequence, there is only a need for two harmonisedlegends.
Multi-risk approach: There is no real need to createmulti-risk indicators or indices from a spatial
planning point of view. It is more important that allrelevant hazards are really considered in spatial
planning practice.
Multi-hazard approach: Most of the examples haveshown that relative hazard scales are a possibility tocreate integrated multi-hazard information.Greiving, 2005
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Some preliminary findings of ARMONIA onspatial planning & risk
Information management: It is highly important thatexisting information is accessible and thatinformation flows are managed.
Indicators: the most important indicator for spatialplanning is the extent of the hazard; further, theoccurrence is important; for some planningdesignations, indicators about hazard intensities(water depth, water speed etc.) are important
Greiving, 2005
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Some preliminary findings of ARMONIA on
spatial planning & risk Addressees: Sectoral planning has to be seen as the
direct addressee of the forthcoming Directive whereasspatial planning can be characterised as one of severalend-users which have to take into account the
provided hazard information.
Greiving, 2005
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Current European situation
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References
Aguirre B. 1994: Planning, Warning, Evacuation, and search and rescue:A review of the social science research literature. Texas A & MUniversity, 46 pp.
ARMONIA Project report 2005: Collection and evaluation of currentmethodologies for risk map production - Task 2.3: Collection andevaluation of current methodologies for landslides. 88pp.
Bundesamt fr Umwelt, Wald und Landschaft 1999:Risikoanalyse beigravitativen Naturgefahren - Fallbeispiele und Daten. In: Umwelt-Materialien Nr. 107/II Naturgefahren. Bern, 129 pp.
Dai, F.C., Lee, C.F. and Ngai, Y.Y. 2002:Landslide risk assessment andmanagement: an overview. Engineering Geology 64, 65-87.
Drabek, T. E. 1986:Human system responses to disaster: An inventory ofsociological findings.New York. 509 pp.
EPSON Hazards project report 2006: The Spatial Effects and Managementof Natural and Technological Hazards in Europe. 198 pp.
FAO 1997:Risk management and food safety. Report of a joint FAO/WHOConsultation. Rome, 32 pp.
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References
Greiving, S. 2002: Planung und Katastrophenvorsorge Verknpfung berVerfahren und organisatorische Regelungen. In: Deutsches Komitee frKatastrophenvorsorge e.V. (DKKV): Zweites Forum KatastrophenvorsorgeExtreme Naturereignisse Folgen, Vorsorge, Werkzeuge, 120-127.
Hollenstein K., Merz, H. & Bhler, B. 2004:Methoden des risikobasiertenPlanens und Handelns bei der Naturgefahrenabwehr. ETH Zrich. 47 pp.
Pearce, L. 2003:Disaster management and community planning, and
public participation: How to achieve sustainable hazard mitigation.Natural Hazards 28, 211-228.
Volkswirtschaftsdirektion Amt fr Wald, Bau-, Verkehrs- undEnergiedirektion Tiefbauamt, Justiz-, Gemeinde- und KirchendirektionAmt fr Gemeinden und Raumordnung 1999:Achtung, Naturgefahr! Verantwortung des Kantons und der Gemeinden im Umgang mit
Naturgefahren. Bern, 29 pp.