K.Fedra ‘97 Spatial DSS environmental applications of spatial decision support systems

K.Fedra ‘97

Spatial DSSSpatial DSSSpatial DSSSpatial DSS

environmental applications of environmental applications of spatial decision support spatial decision support

systemssystems

environmental applications of environmental applications of spatial decision support spatial decision support

systemssystems

K.Fedra ‘97

Spatial DecisionsSpatial DecisionsSpatial DecisionsSpatial Decisions

Spatial decisions:Spatial decisions:

• Set of criteriaSet of criteria– objectives

– constraints

are functions of spaceare functions of space

Spatial decisions:Spatial decisions:

• Set of criteriaSet of criteria– objectives

– constraints

are functions of spaceare functions of space

K.Fedra ‘97

Spatial DecisionsSpatial DecisionsSpatial DecisionsSpatial Decisions

Spatially distributed systems can be Spatially distributed systems can be represented by spatially distributed represented by spatially distributed models.models.

Modeling is used to Modeling is used to • design a design a set of alternativesset of alternatives to to

choose from (simulation models)choose from (simulation models)• design an design an optimal alternativeoptimal alternative

(optimisation models)(optimisation models)

Spatially distributed systems can be Spatially distributed systems can be represented by spatially distributed represented by spatially distributed models.models.

Modeling is used to Modeling is used to • design a design a set of alternativesset of alternatives to to

choose from (simulation models)choose from (simulation models)• design an design an optimal alternativeoptimal alternative

(optimisation models)(optimisation models)

K.Fedra ‘97

Why Modeling:Why Modeling:Why Modeling:Why Modeling:

• conceptualising, organisingconceptualising, organising

• communicatingcommunicating

• understanding, assessing understanding, assessing

• testing field measurementstesting field measurements

• forecasting, early warningforecasting, early warning

• optimising decision makingoptimising decision making

• conceptualising, organisingconceptualising, organising

• communicatingcommunicating

• understanding, assessing understanding, assessing

• testing field measurementstesting field measurements

• forecasting, early warningforecasting, early warning

• optimising decision makingoptimising decision making

K.Fedra ‘97

Modeling DomainsModeling DomainsModeling DomainsModeling Domains

• Atmospheric systemsAtmospheric systems• Hydrologic systemsHydrologic systems• Land surface and subsurfaceLand surface and subsurface• Biological and ecological systemsBiological and ecological systems• Risks and hazardsRisks and hazards• Technological systemsTechnological systems• Management and policy modelsManagement and policy models

• Atmospheric systemsAtmospheric systems• Hydrologic systemsHydrologic systems• Land surface and subsurfaceLand surface and subsurface• Biological and ecological systemsBiological and ecological systems• Risks and hazardsRisks and hazards• Technological systemsTechnological systems• Management and policy modelsManagement and policy models

K.Fedra ‘97

Structuring the problemStructuring the problemStructuring the problemStructuring the problem

• problem statement (description)problem statement (description)• criteria criteria (measurable attributes)(measurable attributes)

• objectives objectives (minimise, maximise)(minimise, maximise)

• constraintsconstraints (inequalities) (inequalities)

• contextcontext

• problem statement (description)problem statement (description)• criteria criteria (measurable attributes)(measurable attributes)

• objectives objectives (minimise, maximise)(minimise, maximise)

• constraintsconstraints (inequalities) (inequalities)

• contextcontext

K.Fedra ‘97


Atmospheric systemsAtmospheric systems• weather forecastingweather forecasting

• climate modelsclimate models

• air pollution: industry, traffic, air pollution: industry, traffic, domestic sources, accidental domestic sources, accidental releases (hazardous substances)releases (hazardous substances)

Atmospheric systemsAtmospheric systems• weather forecastingweather forecasting

• climate modelsclimate models

• air pollution: industry, traffic, air pollution: industry, traffic, domestic sources, accidental domestic sources, accidental releases (hazardous substances)releases (hazardous substances)

K.Fedra ‘97


Air pollution controlAir pollution control• impacts and hazardsimpacts and hazards

– human end environmental exposurehuman end environmental exposure

– damage through explosion and firedamage through explosion and fire

– damage through chemical reactionsdamage through chemical reactions (corrosion)(corrosion)

Air pollution controlAir pollution control• impacts and hazardsimpacts and hazards

– human end environmental exposurehuman end environmental exposure

– damage through explosion and firedamage through explosion and fire

– damage through chemical reactionsdamage through chemical reactions (corrosion)(corrosion)

K.Fedra ‘97


Hydrologic systemsHydrologic systems• hydrological cycle, rainfall-runoffhydrological cycle, rainfall-runoff• river flow and floodingriver flow and flooding• water distribution and allocationwater distribution and allocation• reservoir operationsreservoir operations• water quality, eutrophication, water quality, eutrophication, waste allocationwaste allocation• groundwater systemsgroundwater systems

Hydrologic systemsHydrologic systems• hydrological cycle, rainfall-runoffhydrological cycle, rainfall-runoff• river flow and floodingriver flow and flooding• water distribution and allocationwater distribution and allocation• reservoir operationsreservoir operations• water quality, eutrophication, water quality, eutrophication, waste allocationwaste allocation• groundwater systemsgroundwater systems

K.Fedra ‘97


Coastal waters and oceansCoastal waters and oceans• currents and energy balance currents and energy balance

(climate modeling)(climate modeling)

• coastal water qualitycoastal water quality

• nutrient cycles, eutrophicationnutrient cycles, eutrophication

• fisheries (sustainable yield)fisheries (sustainable yield)

Coastal waters and oceansCoastal waters and oceans• currents and energy balance currents and energy balance

(climate modeling)(climate modeling)

• coastal water qualitycoastal water quality

• nutrient cycles, eutrophicationnutrient cycles, eutrophication

• fisheries (sustainable yield)fisheries (sustainable yield)

K.Fedra ‘97


Land surface and subsurfaceLand surface and subsurface• erosion, soil processeserosion, soil processes

• vegetation, land covervegetation, land cover

• groundwater (unsaturated and groundwater (unsaturated and saturated zones, links to the saturated zones, links to the hydrological domain)hydrological domain)

Land surface and subsurfaceLand surface and subsurface• erosion, soil processeserosion, soil processes

• vegetation, land covervegetation, land cover

• groundwater (unsaturated and groundwater (unsaturated and saturated zones, links to the saturated zones, links to the hydrological domain)hydrological domain)

K.Fedra ‘97


Biological and ecological systemsBiological and ecological systems• population models, predator-prey population models, predator-prey

systems, food chainssystems, food chains

• ecosystem models (multi-ecosystem models (multi-compartment combining physical compartment combining physical and biological elements)and biological elements)

Biological and ecological systemsBiological and ecological systems• population models, predator-prey population models, predator-prey

systems, food chainssystems, food chains

• ecosystem models (multi-ecosystem models (multi-compartment combining physical compartment combining physical and biological elements)and biological elements)

K.Fedra ‘97


Agriculture and ForestryAgriculture and Forestry• agricultural production agricultural production

• livestock and grazing modelslivestock and grazing models

• forest models (stands, growth, yield, forest models (stands, growth, yield, deforestation and reforestation)deforestation and reforestation)

Agriculture and ForestryAgriculture and Forestry• agricultural production agricultural production

• livestock and grazing modelslivestock and grazing models

• forest models (stands, growth, yield, forest models (stands, growth, yield, deforestation and reforestation)deforestation and reforestation)

K.Fedra ‘97


Technological systemsTechnological systems

• transportationtransportation

• energy systemsenergy systems

• industrial impactsindustrial impacts

• waste managementwaste management

Technological systemsTechnological systems

• transportationtransportation

• energy systemsenergy systems

• industrial impactsindustrial impacts

• waste managementwaste management

K.Fedra ‘97


Risks and hazardsRisks and hazards• floods and droughtsfloods and droughts

• erosion, desertificationerosion, desertification

• spills and accidental releasesspills and accidental releases

• epidemiological models (pests, epidemiological models (pests, infectious diseases)infectious diseases)

Risks and hazardsRisks and hazards• floods and droughtsfloods and droughts

• erosion, desertificationerosion, desertification

• spills and accidental releasesspills and accidental releases

• epidemiological models (pests, epidemiological models (pests, infectious diseases)infectious diseases)

K.Fedra ‘97

Spatial decisionsSpatial decisionsSpatial decisionsSpatial decisions

Environmental decision are also Environmental decision are also spatial decisions:spatial decisions:

• site selection, locationsite selection, location• pollution controlpollution control• natural resources managementnatural resources management• environmental impact assessmentenvironmental impact assessment• risk analysis and managementrisk analysis and management

Environmental decision are also Environmental decision are also spatial decisions:spatial decisions:

• site selection, locationsite selection, location• pollution controlpollution control• natural resources managementnatural resources management• environmental impact assessmentenvironmental impact assessment• risk analysis and managementrisk analysis and management

K.Fedra ‘97


site selection, locationsite selection, location

• site selection for special activities or site selection for special activities or installations (power plants, incinerators, installations (power plants, incinerators, hazardous waste facilities): NIMBYhazardous waste facilities): NIMBY

• site suitability analysissite suitability analysis

• zoning, land use managementzoning, land use management

site selection, locationsite selection, location

• site selection for special activities or site selection for special activities or installations (power plants, incinerators, installations (power plants, incinerators, hazardous waste facilities): NIMBYhazardous waste facilities): NIMBY

• site suitability analysissite suitability analysis

• zoning, land use managementzoning, land use management

K.Fedra ‘97


pollution controlpollution control

• commissioning of sourcescommissioning of sources

• resource allocation to source controlresource allocation to source control

• incentives and taxes for emission incentives and taxes for emission sourcessources

• clean-up strategiesclean-up strategies

pollution controlpollution control

• commissioning of sourcescommissioning of sources

• resource allocation to source controlresource allocation to source control

• incentives and taxes for emission incentives and taxes for emission sourcessources

• clean-up strategiesclean-up strategies

K.Fedra ‘97


natural resources managementnatural resources management• harvest and management strategies harvest and management strategies

(maximum sustainable yield) for forestry, (maximum sustainable yield) for forestry, fisheries, livestockfisheries, livestock

• land-use (crop) allocationland-use (crop) allocation• commissioning (mining, extraction) commissioning (mining, extraction) • land reclamation, site remediationland reclamation, site remediation• water resources management, water water resources management, water

allocationallocation

natural resources managementnatural resources management• harvest and management strategies harvest and management strategies

(maximum sustainable yield) for forestry, (maximum sustainable yield) for forestry, fisheries, livestockfisheries, livestock

• land-use (crop) allocationland-use (crop) allocation• commissioning (mining, extraction) commissioning (mining, extraction) • land reclamation, site remediationland reclamation, site remediation• water resources management, water water resources management, water

allocationallocation

K.Fedra ‘97


environmental impact assessmentenvironmental impact assessment

• scoping and screeningscoping and screening

• impact assessment for major impact assessment for major development projectsdevelopment projects

• policy assessmentpolicy assessment

environmental impact assessmentenvironmental impact assessment

• scoping and screeningscoping and screening

• impact assessment for major impact assessment for major development projectsdevelopment projects

• policy assessmentpolicy assessment

K.Fedra ‘97


risk analysis and managementrisk analysis and management• siting and commissioning of hazardous siting and commissioning of hazardous

installationsinstallations• operational managementoperational management• hazardous substances and waste hazardous substances and waste

managementmanagement• emergency planningemergency planning• emergency managementemergency management

risk analysis and managementrisk analysis and management• siting and commissioning of hazardous siting and commissioning of hazardous

installationsinstallations• operational managementoperational management• hazardous substances and waste hazardous substances and waste

managementmanagement• emergency planningemergency planning• emergency managementemergency management

K.Fedra ‘97

MC DSS Application ExampleMC DSS Application ExampleMC DSS Application ExampleMC DSS Application Example

Selecting Nuclear Power Plant Selecting Nuclear Power Plant

Sites in the Pacific Northwest Sites in the Pacific Northwest

Using Decision Analysis Using Decision Analysis

Keeney and Nair, 1977Keeney and Nair, 1977

Selecting Nuclear Power Plant Selecting Nuclear Power Plant

Sites in the Pacific Northwest Sites in the Pacific Northwest

Using Decision Analysis Using Decision Analysis

Keeney and Nair, 1977Keeney and Nair, 1977

K.Fedra ‘97

Site SelectionSite SelectionSite SelectionSite Selection

Problem statement:Problem statement:

identify and recommend potential identify and recommend potential

new sites suitable for a nuclearnew sites suitable for a nuclear

3,000 MWe thermal power station 3,000 MWe thermal power station in the Pacific Northwest.in the Pacific Northwest.

Problem statement:Problem statement:

identify and recommend potential identify and recommend potential

new sites suitable for a nuclearnew sites suitable for a nuclear

3,000 MWe thermal power station 3,000 MWe thermal power station in the Pacific Northwest.in the Pacific Northwest.

K.Fedra ‘97


Objective:Objective:

identify sites with a high probability identify sites with a high probability

for successful licensing;for successful licensing;

screen sites for detailed site screen sites for detailed site

specific studiesspecific studies

Objective:Objective:

identify sites with a high probability identify sites with a high probability

for successful licensing;for successful licensing;

screen sites for detailed site screen sites for detailed site

specific studiesspecific studies

K.Fedra ‘97


Two step procedure:Two step procedure:

• a screening process to identify a screening process to identify candidate sitescandidate sites

• a decision analysis to evaluate a decision analysis to evaluate and rank the candidate sitesand rank the candidate sites

Two step procedure:Two step procedure:

• a screening process to identify a screening process to identify candidate sitescandidate sites

• a decision analysis to evaluate a decision analysis to evaluate and rank the candidate sitesand rank the candidate sites

K.Fedra ‘97


Study area:Study area:

250,000 km250,000 km22 including the State of including the State of Washington, major river basins in Washington, major river basins in Oregon and Idaho, Oregon coast, Oregon and Idaho, Oregon coast, excluding areas around existing excluding areas around existing TPS sites.TPS sites.

Study area:Study area:

250,000 km250,000 km22 including the State of including the State of Washington, major river basins in Washington, major river basins in Oregon and Idaho, Oregon coast, Oregon and Idaho, Oregon coast, excluding areas around existing excluding areas around existing TPS sites.TPS sites.

K.Fedra ‘97


Hierarchy of issues:Hierarchy of issues:• safetysafety• environmentalenvironmental• socialsocial• economiceconomic

with criteria and required levels of with criteria and required levels of achievements (constraints)achievements (constraints)

Hierarchy of issues:Hierarchy of issues:• safetysafety• environmentalenvironmental• socialsocial• economiceconomic

with criteria and required levels of with criteria and required levels of achievements (constraints)achievements (constraints)

K.Fedra ‘97


Safety:Safety: radiation exposure radiation exposure

Distance from populated areas:Distance from populated areas:

more than 5 km from populated more than 5 km from populated places > 2,500 inhabitantsplaces > 2,500 inhabitants

more than 2 km from populated more than 2 km from populated places < 2,500 inhabitantsplaces < 2,500 inhabitants

Safety:Safety: radiation exposure radiation exposure

Distance from populated areas:Distance from populated areas:

more than 5 km from populated more than 5 km from populated places > 2,500 inhabitantsplaces > 2,500 inhabitants

more than 2 km from populated more than 2 km from populated places < 2,500 inhabitantsplaces < 2,500 inhabitants

K.Fedra ‘97


Safety:Safety: Flooding Flooding

Height above nearest water source:Height above nearest water source:

area must be above primary flood area must be above primary flood

plain (100 year flood)plain (100 year flood)

Safety:Safety: Flooding Flooding

Height above nearest water source:Height above nearest water source:

area must be above primary flood area must be above primary flood

plain (100 year flood)plain (100 year flood)

K.Fedra ‘97


Safety:Safety: Surface faulting Surface faulting

Distance from fault:Distance from fault:

area a must be more than 10 km area a must be more than 10 km

from capable or > 15 km from from capable or > 15 km from

unclassified faultsunclassified faults

Safety:Safety: Surface faulting Surface faulting

Distance from fault:Distance from fault:

area a must be more than 10 km area a must be more than 10 km

from capable or > 15 km from from capable or > 15 km from

unclassified faultsunclassified faults

K.Fedra ‘97


Environment:Environment: Thermal pollution Thermal pollution

Average low flow:Average low flow:

Cooling water source (river, Cooling water source (river,

reservoir) yielding 7 day average reservoir) yielding 7 day average

10 year low-flow > 5 m10 year low-flow > 5 m33/sec/sec

Environment:Environment: Thermal pollution Thermal pollution

Average low flow:Average low flow:

Cooling water source (river, Cooling water source (river,

reservoir) yielding 7 day average reservoir) yielding 7 day average

10 year low-flow > 5 m10 year low-flow > 5 m33/sec/sec

K.Fedra ‘97


Environment:Environment: protected areas protected areas

Relative location:Relative location:

Location must be outside Location must be outside

designated or protected sensitive designated or protected sensitive

ecological areasecological areas

Environment:Environment: protected areas protected areas


Location must be outside Location must be outside

designated or protected sensitive designated or protected sensitive

ecological areasecological areas

K.Fedra ‘97


Socio-economics: Socio-economics: tourism, recreationtourism, recreation


Location must be outside designated Location must be outside designated

scenic and recreational areasscenic and recreational areas

Socio-economics: Socio-economics: tourism, recreationtourism, recreation


Location must be outside designated Location must be outside designated

scenic and recreational areasscenic and recreational areas

K.Fedra ‘97


Costs: Costs: routine/emergency water supply routine/emergency water supply

Cost/reliability of water source:Cost/reliability of water source:

Cooling water source (river, reservoir) Cooling water source (river, reservoir)

yielding 7 day average 10 year low- yielding 7 day average 10 year low-

flow > 5 mflow > 5 m33/sec/sec


Cost/reliability of water source:Cost/reliability of water source:

Cooling water source (river, reservoir) Cooling water source (river, reservoir)

yielding 7 day average 10 year low- yielding 7 day average 10 year low-

flow > 5 mflow > 5 m33/sec/sec

K.Fedra ‘97



Cost of pumping water:Cost of pumping water:

Location within 15 km from nearest Location within 15 km from nearest

water supply, and less than 250 m water supply, and less than 250 m

above the water levelabove the water level


Cost of pumping water:Cost of pumping water:

Location within 15 km from nearest Location within 15 km from nearest

water supply, and less than 250 m water supply, and less than 250 m

above the water levelabove the water level

K.Fedra ‘97


Cost: Cost: delivery of major componentsdelivery of major components

Cost of providing delivery access:Cost of providing delivery access:

Location must be within 50 km of Location must be within 50 km of

navigable waterwaysnavigable waterways

Cost: Cost: delivery of major componentsdelivery of major components

Cost of providing delivery access:Cost of providing delivery access:

Location must be within 50 km of Location must be within 50 km of

navigable waterwaysnavigable waterways

K.Fedra ‘97


Sensitivity:Sensitivity:

assume varying the cut-off values by assume varying the cut-off values by

a small percentage; how many a small percentage; how many

potential sites are included or potential sites are included or

excluded ?excluded ?

Sensitivity:Sensitivity:

assume varying the cut-off values by assume varying the cut-off values by

a small percentage; how many a small percentage; how many

potential sites are included or potential sites are included or

excluded ?excluded ?

K.Fedra ‘97


Site information: Site information: (approx. 30 attributes)(approx. 30 attributes)

• area, location, present use, ownershiparea, location, present use, ownership• quality, quantity, location of water quality, quantity, location of water • geology, topography, flooding potentialgeology, topography, flooding potential• population, vegetation, wildlifepopulation, vegetation, wildlife• access to transportation networksaccess to transportation networks• local workforce, potential socio-economic local workforce, potential socio-economic

problems during construction phase, …….problems during construction phase, …….

Site information: Site information: (approx. 30 attributes)(approx. 30 attributes)

• area, location, present use, ownershiparea, location, present use, ownership• quality, quantity, location of water quality, quantity, location of water • geology, topography, flooding potentialgeology, topography, flooding potential• population, vegetation, wildlifepopulation, vegetation, wildlife• access to transportation networksaccess to transportation networks• local workforce, potential socio-economic local workforce, potential socio-economic

problems during construction phase, …….problems during construction phase, …….

K.Fedra ‘97


Screening of attributes:Screening of attributes:• relative importancerelative importanceannualised capital cost of the TPS is around annualised capital cost of the TPS is around

200-300 MUS$;200-300 MUS$;

annual revenue loss from adverse effects on annual revenue loss from adverse effects on fisheries is around 0-50,000 US$fisheries is around 0-50,000 US$

ignore the fishignore the fish

Screening of attributes:Screening of attributes:• relative importancerelative importanceannualised capital cost of the TPS is around annualised capital cost of the TPS is around

200-300 MUS$;200-300 MUS$;

annual revenue loss from adverse effects on annual revenue loss from adverse effects on fisheries is around 0-50,000 US$fisheries is around 0-50,000 US$

ignore the fishignore the fish

K.Fedra ‘97


Screening of attributes:Screening of attributes:• site-dependent variationsite-dependent variation

even though manpower costs for even though manpower costs for operations are important, they don’t operations are important, they don’t vary significantly between sitesvary significantly between sites

ignore labor costsignore labor costs

Screening of attributes:Screening of attributes:• site-dependent variationsite-dependent variation

even though manpower costs for even though manpower costs for operations are important, they don’t operations are important, they don’t vary significantly between sitesvary significantly between sites

ignore labor costsignore labor costs

K.Fedra ‘97


Screening of attributes:Screening of attributes:• likelihood of occurrencelikelihood of occurrenceadverse effects on crops could amount adverse effects on crops could amount

to several million US$; the probability to several million US$; the probability of such extreme losses is near zeroof such extreme losses is near zero

ignore crop lossesignore crop losses

Screening of attributes:Screening of attributes:• likelihood of occurrencelikelihood of occurrenceadverse effects on crops could amount adverse effects on crops could amount

to several million US$; the probability to several million US$; the probability of such extreme losses is near zeroof such extreme losses is near zero

ignore crop lossesignore crop losses

K.Fedra ‘97


Final Objectives and Criteria:Final Objectives and Criteria:Health and SafetyHealth and Safety

XX11 = site population factor= site population factor

best: 0best: 0

worst: 0.20worst: 0.20

Final Objectives and Criteria:Final Objectives and Criteria:Health and SafetyHealth and Safety

XX11 = site population factor= site population factor

best: 0best: 0

worst: 0.20worst: 0.20

K.Fedra ‘97


Site Population FactorSite Population Factor(US Atomic Energy Commission)(US Atomic Energy Commission)

SUM ((SUM ((dd=1,50) P(=1,50) P(dd))dd-2-2)) SPF(L) = SPF(L) = SUM ((SUM ((dd=1,50) Q(=1,50) Q(dd))-2-2))where where dd is distance in miles, is distance in miles, PP is the population within this radius, is the population within this radius,QQ is the population in this radius at a density is the population in this radius at a density

of 1,000 people per square mileof 1,000 people per square mile

Site Population FactorSite Population Factor(US Atomic Energy Commission)(US Atomic Energy Commission)

SUM ((SUM ((dd=1,50) P(=1,50) P(dd))dd-2-2)) SPF(L) = SPF(L) = SUM ((SUM ((dd=1,50) Q(=1,50) Q(dd))-2-2))where where dd is distance in miles, is distance in miles, PP is the population within this radius, is the population within this radius,QQ is the population in this radius at a density is the population in this radius at a density

of 1,000 people per square mileof 1,000 people per square mile

K.Fedra ‘97


Final Objectives and Criteria:Final Objectives and Criteria:Environmental EffectsEnvironmental Effects

XX22 = loss of salmonides= loss of salmonides

best: 0best: 0

worst: 100 % of fish populationworst: 100 % of fish population


XX22 = loss of salmonides= loss of salmonides

best: 0best: 0

worst: 100 % of fish populationworst: 100 % of fish population

K.Fedra ‘97



XX33 = ecological impacts= ecological impacts

best: 0best: 0

worst: 8 worst: 8 (subjective ordinal scale)(subjective ordinal scale)


XX33 = ecological impacts= ecological impacts

best: 0best: 0


K.Fedra ‘97


ecological impacts:ecological impacts: loss per loss per mimi2 2 for sitefor site

0 0 agricultural or urban land, no nativeagricultural or urban land, no native ecological communities affectedecological communities affected

1 1 primarily agricultural land, no wetlands primarily agricultural land, no wetlands …………......77 mature community or 90% loss of wetlandsmature community or 90% loss of wetlands and endangered species habitatand endangered species habitat8 8 100% mature forest, virgin wetlands, or100% mature forest, virgin wetlands, or endangered species habitatsendangered species habitats

ecological impacts:ecological impacts: loss per loss per mimi2 2 for sitefor site

0 0 agricultural or urban land, no nativeagricultural or urban land, no native ecological communities affectedecological communities affected

1 1 primarily agricultural land, no wetlands primarily agricultural land, no wetlands …………......77 mature community or 90% loss of wetlandsmature community or 90% loss of wetlands and endangered species habitatand endangered species habitat8 8 100% mature forest, virgin wetlands, or100% mature forest, virgin wetlands, or endangered species habitatsendangered species habitats

K.Fedra ‘97



XX44 = length of 500 kV intertie= length of 500 kV intertie

best: 0best: 0

worst: 50 milesworst: 50 miles


XX44 = length of 500 kV intertie= length of 500 kV intertie

best: 0best: 0

worst: 50 milesworst: 50 miles

K.Fedra ‘97


Final Objectives and Criteria:Final Objectives and Criteria:Socio-Economic EffectsSocio-Economic Effects

XX55 = socio-economic impacts= socio-economic impacts

best: 0best: 0


Final Objectives and Criteria:Final Objectives and Criteria:Socio-Economic EffectsSocio-Economic Effects

XX55 = socio-economic impacts= socio-economic impacts

best: 0best: 0


K.Fedra ‘97


Final Objectives and Criteria:Final Objectives and Criteria:System CostSystem Cost

XX66 = annual differential cost (30 yr)= annual differential cost (30 yr)

best: 0best: 0

worst: 40,000,000 US$ (1985)worst: 40,000,000 US$ (1985)

Final Objectives and Criteria:Final Objectives and Criteria:System CostSystem Cost

XX66 = annual differential cost (30 yr)= annual differential cost (30 yr)

best: 0best: 0

worst: 40,000,000 US$ (1985)worst: 40,000,000 US$ (1985)

K.Fedra ‘97


Preference StructurePreference Structure

• determine the general preferencedetermine the general preference structurestructure

• assess the single-attribute utilityassess the single-attribute utility functionsfunctions

• evaluate the scaling constantsevaluate the scaling constants

• specify the combined utility functionspecify the combined utility function

Preference StructurePreference Structure

• determine the general preferencedetermine the general preference structurestructure

• assess the single-attribute utilityassess the single-attribute utility functionsfunctions

• evaluate the scaling constantsevaluate the scaling constants

• specify the combined utility functionspecify the combined utility function

K.Fedra ‘97


General Preference StructureGeneral Preference StructureIndependence of attributes:Independence of attributes:

{X{Xii, X, Xjj} } are are preferentially independentpreferentially independent

if the preference order for (xif the preference order for (x i, i, xxjj) does not) does not

depend on the levels of other attributes.depend on the levels of other attributes.

General Preference StructureGeneral Preference StructureIndependence of attributes:Independence of attributes:

{X{Xii, X, Xjj} } are are preferentially independentpreferentially independent

if the preference order for (xif the preference order for (x i, i, xxjj) does not) does not

depend on the levels of other attributes.depend on the levels of other attributes.

K.Fedra ‘97


Multiattribute utility functionMultiattribute utility functionattribute independenceattribute independencesuggests an suggests an

additive utility function:additive utility function:

u(x) = SUMu(x) = SUM(1,6)(1,6) ((kkiiuuii(x(xii))))where u is scaled 0 to 1, uwhere u is scaled 0 to 1, u ii are the single are the single

attribute utility functions, and kattribute utility functions, and k ii are are

scaling constants with 0<kscaling constants with 0<k ii<1<1

Multiattribute utility functionMultiattribute utility functionattribute independenceattribute independencesuggests an suggests an

additive utility function:additive utility function:

u(x) = SUMu(x) = SUM(1,6)(1,6) ((kkiiuuii(x(xii))))where u is scaled 0 to 1, uwhere u is scaled 0 to 1, u ii are the single are the single

attribute utility functions, and kattribute utility functions, and k ii are are

scaling constants with 0<kscaling constants with 0<k ii<1<1

K.Fedra ‘97


Single attribute utility functionsSingle attribute utility functions• 50-50 lottery method 50-50 lottery method (Keeney and Raiffa, 1976)(Keeney and Raiffa, 1976)

XX66 (cost, 0-40 M) (cost, 0-40 M)

offer various values of Xoffer various values of X66 against a against a50/50 “lottery” of 0 or 40 M.50/50 “lottery” of 0 or 40 M.Point of indifference: 22 MPoint of indifference: 22 Mu(0) = 1, and u(40) = 0 u(22) = 0.5u(0) = 1, and u(40) = 0 u(22) = 0.5

Single attribute utility functionsSingle attribute utility functions• 50-50 lottery method 50-50 lottery method (Keeney and Raiffa, 1976)(Keeney and Raiffa, 1976)

XX66 (cost, 0-40 M) (cost, 0-40 M)

offer various values of Xoffer various values of X66 against a against a50/50 “lottery” of 0 or 40 M.50/50 “lottery” of 0 or 40 M.Point of indifference: 22 MPoint of indifference: 22 Mu(0) = 1, and u(40) = 0 u(22) = 0.5u(0) = 1, and u(40) = 0 u(22) = 0.5

K.Fedra ‘97


Single attribute utility functionsSingle attribute utility functions

XX66 cost cost

u(40) = 0.0u(40) = 0.0

u(26) = 0.5u(26) = 0.5

u(0) = 1.0u(0) = 1.0


XX66 cost cost

u(40) = 0.0u(40) = 0.0

u(26) = 0.5u(26) = 0.5

u(0) = 1.0u(0) = 1.0

K.Fedra ‘97



XX33 ecology ecology

u(8) = 0.0u(8) = 0.0

u(5) = 0.5u(5) = 0.5

u(0) = 1.0u(0) = 1.0


XX33 ecology ecology

u(8) = 0.0u(8) = 0.0

u(5) = 0.5u(5) = 0.5

u(0) = 1.0u(0) = 1.0

K.Fedra ‘97


Scaling constantsScaling constants

• ranking of attribute (importance)ranking of attribute (importance)• quantifying the kquantifying the kii

Ranking: Ranking: everything else being equal, everything else being equal, which attribute would you prefer to be which attribute would you prefer to be at its best value ?at its best value ?

kk6 6 > k> k11 > k > k22 > k > k44 > k > k55 > k > k33

Scaling constantsScaling constants

• ranking of attribute (importance)ranking of attribute (importance)• quantifying the kquantifying the kii

Ranking: Ranking: everything else being equal, everything else being equal, which attribute would you prefer to be which attribute would you prefer to be at its best value ?at its best value ?

kk6 6 > k> k11 > k > k22 > k > k44 > k > k55 > k > k33

K.Fedra ‘97


Scaling constantsScaling constants• quantifying the kquantifying the kii trade-off between attributes:trade-off between attributes:

Site A: SPF = 0.0 cost = 40Site A: SPF = 0.0 cost = 40Site B: SPF = 0.2 cost = Site B: SPF = 0.2 cost = ??At which cost are A and B considered At which cost are A and B considered

equivalent (indifference) ?equivalent (indifference) ?

Scaling constantsScaling constants• quantifying the kquantifying the kii trade-off between attributes:trade-off between attributes:

Site A: SPF = 0.0 cost = 40Site A: SPF = 0.0 cost = 40Site B: SPF = 0.2 cost = Site B: SPF = 0.2 cost = ??At which cost are A and B considered At which cost are A and B considered

equivalent (indifference) ?equivalent (indifference) ?

K.Fedra ‘97

Site SelectionSite SelectionSite SelectionSite SelectionScaling constants Scaling constants trade-off betweentrade-off between attributes:attributes: cost cost versusversus

site factorsite factor

40 M ~ 0.040 M ~ 0.0 5 M ~ 0.25 M ~ 0.2

Scaling constants Scaling constants trade-off betweentrade-off between attributes:attributes: cost cost versusversus

site factorsite factor

40 M ~ 0.040 M ~ 0.0 5 M ~ 0.25 M ~ 0.2

K.Fedra ‘97


Utility functionUtility function establish probability (weight) establish probability (weight) pp such that such that option option AA: cost = 0, everything else : cost = 0, everything else

at the worst level is indifferent toat the worst level is indifferent to option option BB:: all attributes at best level (all attributes at best level (pp)) all attributes at worst level (all attributes at worst level (1-1-pp))

Utility functionUtility function establish probability (weight) establish probability (weight) pp such that such that option option AA: cost = 0, everything else : cost = 0, everything else

at the worst level is indifferent toat the worst level is indifferent to option option BB:: all attributes at best level (all attributes at best level (pp)) all attributes at worst level (all attributes at worst level (1-1-pp))

K.Fedra ‘97


Utility functionUtility function

p p = 0.4 = 0.4 utility of option utility of option AA::

pp(1.0)+(1-(1.0)+(1-pp)(0.0) = )(0.0) = pp

kk66 = = pp = 0.4 = 0.4

from trade-offs against kfrom trade-offs against k66, all other k, all other k ii can can

be determinedbe determined


p p = 0.4 = 0.4 utility of option utility of option AA::

pp(1.0)+(1-(1.0)+(1-pp)(0.0) = )(0.0) = pp

kk66 = = pp = 0.4 = 0.4

from trade-offs against kfrom trade-offs against k66, all other k, all other k ii can can

be determinedbe determined

K.Fedra ‘97



given all kgiven all kii, the multiattribute utility , the multiattribute utility

function can now be determined:function can now be determined:

u(x) = SUMu(x) = SUM(1,6)(1,6) ((kkiiuuii(x(xii))))

which leads to a ranking ofwhich leads to a ranking ofthe candidate sites.the candidate sites.


given all kgiven all kii, the multiattribute utility , the multiattribute utility

function can now be determined:function can now be determined:

u(x) = SUMu(x) = SUM(1,6)(1,6) ((kkiiuuii(x(xii))))

which leads to a ranking ofwhich leads to a ranking ofthe candidate sites.the candidate sites.

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K.Fedra ‘97 Spatial DSS environmental applications of spatial decision support systems