Agung Wahyudi Promoter: Prof Marc Van Meirvenne Co-promoter: ir. Liesbet Cockx Introduction GIS Decision Making Integration Recent Dev’t Conclusions Home
Aug 17, 2014
Agung WahyudiPromoter: Prof Marc Van MeirvenneCo-promoter: ir. Liesbet Cockx
Introduction GIS Decision Making Integration Recent Dev’t ConclusionsHome
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IntroductionGIS Decision Making Integration Recent Dev’t Conclusions
Geographic Information System Decision Making
Fundamental
Data
Advanced
Data Management
Manipulation and Analysis
Output
How They Integrate?Loose integration
Tight Integration
Interoperable
evaluation criteria,
decision alt’s & constraints
criterion weighing,
decision rules, and
sensitivity analysisStatistical Modeling
Mathematical Modeling
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What is GISGIS Decision Making Integration Recent Dev’t Conclusions
Fundamental
Data
Advanced
Data Management
Manipulation and Analysis
Output
Statistical Modeling
Mathematical Modeling
Conventional Statistics are based on random, independent variables that assume zero continuity and allow for no extension of each data value.
Spatial Statistics is focuses on the spatial association between values observed at different locations (spatial dependency) and the systematic variation of phenomena by location (spatial heterogeneity or non-stationary)
Optimization is a normative approach to identify the best solution for a given decision problem
Simulation is a methodology for performing experiments using a model of the real world system.
Theory Example
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What is GISDecision Making Integration Recent Dev’t Conclusions
Theory Example
Advanced function. Network analysis from
ArcGIS
GIS
consensus weighting procedures and heuristics allow the evaluation and allocation
of land for multi-objective planning
Tools for multi-objective/multi-criteria decision support from IDRISI.
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Decision MakingGIS Decision Making Integration Recent Dev’t Conclusions
Problem Definition
ConstraintsEvaluation Criteria
AlternativesDecision Matrix
Decision-Maker’s
Preferences
Decision Rules
Sensitivity Analysis
Recommendation
Intelligence Phase GIS
Design Phase MCDM
Choice Phase MCDM/GIS
Evaluation Criteria involves;A comprehensive set of objectives that reflects all concerns relevant to the decision problem, and Measures for achieving those objectives
Criterion Weighing Decision Rule Sensitivity
AnalysisEvaluation
CriteriaDecision Alt’s&
Constraint
The set of evaluation criteria can be developed through;examination of relevant literature,
analytical studies, and
survey of opinions
“To maximize soil fertility”Evaluation
Criteria
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Decision MakingGIS Decision Making Integration Recent Dev’t Conclusions
Problem Definition
ConstraintsEvaluation Criteria
AlternativesDecision Matrix
Decision-Maker’s
Preferences
Decision Rules
Sensitivity Analysis
Recommendation
Intelligence Phase GIS
Design Phase MCDM
Choice Phase MCDM/GIS
Criterion Weighing Decision Rule Sensitivity
AnalysisEvaluation
CriteriaDecision Alt’s&
Constraint
Constraints
AlternativesDecision Matrix
The alternatives may represent different courses of action, different hypothesis, different land allocation, and so on.
Decision variables can be grouped into deterministic, random, linguistic variables
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“Decision is a choice between alternatives”
Constraints are limitations imposed by nature or by human beings that do not permit certain action to be taken
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Decision MakingGIS Decision Making Integration Recent Dev’t Conclusions
Problem Definition
ConstraintsEvaluation Criteria
AlternativesDecision Matrix
Decision-Maker’s
Preferences
Decision Rules
Sensitivity Analysis
Recommendation
Intelligence Phase GIS
Design Phase MCDM
Choice Phase MCDM/GIS
A criterion is some basis for decision that can be measured and evaluated.
Criterion Weighing Decision Rule Sensitivity
AnalysisEvaluation
CriteriaDecision Alt’s&
Constraint
Decision-Maker’s Preferences
Pairwise comparison method was developed by Saaty in the context of Analytical Hierarchy Process (AHP). This method involves pairwise comparisons to create a ratio matrix.
The decision maker’s preferences with respect to the evaluation criteria are incorporated into the decision model.
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Decision MakingGIS Integration Recent Dev’t Conclusions
Problem Definition
ConstraintsEvaluation Criteria
AlternativesDecision Matrix
Decision-Maker’s
Preferences
Decision Rules
Sensitivity Analysis
Recommendation
Intelligence Phase GIS
Design Phase MCDM
Choice Phase MCDM/GIS
“decision rules dictate which alternative is preferred to another”.
Decision Making
Criterion Weighing Decision Rule Sensitivity
AnalysisEvaluation
CriteriaDecision Alt’s&
Constraint
Decision Rules
Decision RuleThe procedure by which criteria are combined to arrive at a particular evaluation, and by which evaluations are compared and acted upon.
Simple Additive Weighting (SAW) are the most often techniques used. This techniques are also called scoring methods since the decision maker directly assign certain weight to “relative importance” attributes.
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Decision MakingGIS Integration Recent Dev’t Conclusions
Problem Definition
ConstraintsEvaluation Criteria
AlternativesDecision Matrix
Decision-Maker’s
Preferences
Decision Rules
Sensitivity Analysis
Recommendation
Intelligence Phase GIS
Design Phase MCDM
Choice Phase MCDM/GIS
Sensitivity analysis is a procedure for determining how the recommended course of action is affected by changes in the inputs of the analysis.
Decision Making
Criterion Weighing Decision Rule Sensitivity
AnalysisEvaluation
CriteriaDecision Alt’s&
Constraint
Sensitivity Analysis
Monte Carlo simulation is a way of evaluating a large number of possible scenarios.
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“if the weight change, will the final ranks vary?”
Sensitivity of Weight by giving small changes in value of attributes
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How They IntegrateGIS Decision Making Integration Recent Dev’t Conclusions
User
Loose Coupling; MC-SDSS
MCDMUser
Interface
GISUser
Interface
Shared Files
Loose coupling strategy combines the capabilities of separate models for GIS functions and MCDM by transferring files. to works in GIS-
MCDM model we have to switch between GIS software, database/spreadsheet software, and
MCDM software very often
Loose Tight Interoperable
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How They IntegrateGIS Decision Making Recent Dev’t Conclusions
User
Tight Coupling; MC-SDSS
MCDMShared Files
GIS
User Interface
Tightly or close integration strategy is based on a single data or model manager and a common user interface. With this strategy, there is no need to leave the GIS to run multicriteria decision analysis
ArcGIS 9 Statistical Analysis Module
IDRISIDecision Analysis Module
Loose Tight Interoperable
IntegrationIntroductionHome
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How They IntegrateGIS Decision Making Recent Dev’t Conclusions
Interoperable
GISdatabase
Code
Spatial Analysis Software
Interoperable is the ability of two or more software components to directly
cooperate/communicate despite of their differences in programming language,
interface, and execution platform
VBA (Visual Basic Application) code to deploy ADO (Microsoft Active Data
Object)
VBA (Visual Basic Application) code for GIS AS (Advisor System) Module
VBA (Visual Basic Application) code for AHP Excel Application
Eldrandaly et.al. (2003)
Loose Tight Interoperable
IntegrationIntroductionHome
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Recent DevelopmentGIS Decision Making Integration Recent Dev’t Conclusions
GIS systems have evolved from a ‘close’ expert oriented to an ‘open’ user-oriented technology
An integration of MCDA and geo-computation can enhance the GIS-MCDA capabilities of handling larger and more diverse spatial data sets.
GIS and decision making would likely to come in interoperable geo-processing services that can be chained to build specific spatial
decision support services
GIS and decision making will moves to distributed systems where everyone have an access to use it.
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ConclusionsGIS Decision Making Integration Recent Dev’t Conclusions
We have reviewed the most important component of GIS and decision making
GIS and decision making is different from common feature of GIS.
GIS in the decision making framework still contains some limitation, the most important criticism in GIS is that GIS has limited ability to compare and asses different scenarios of alternatives
In the framework of decision making, it is argued that GIS can only play significant role in intelligence phase, whereas in choice phase GIS has some limitation to play its role
In the way to integrate Multicriteria Decision Making (MCDA) and GIS, there are three methods that can be proposed; loose coupling, tight coupling, and interoperable
Recent development within the GIS and decision making framework are related with the development of interoperable software
Further experiment to solve real world spatial problems is still challenging especially in the framework of soil science and decision making
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ClosingGIS Decision Making Integration Recent Dev’t Conclusions
Thank YouMerci Beaucoup
Danke je WelVielen Dank
Gracias
Terima KasihKyay zuuCám ón Shukron
Arigato gozaimasXie xie
Dhanyabad
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ClosingIntroduction Case Study GIS Decision Making Integration Recent Dev’t Conclusions
Thank YouMercy
Danke WelXie xie
Terima KasihKeumeunShukron
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Case StudyIntroduction Case Study GIS Decision Making Integration Recent Dev’t ConclusionsHome
The objective : to ensure the productivity of forest resources over time, taking into consideration the environmental, economic and social values of the forest.
Multicriteria Evaluation Tools in Sustainable Forest Management
Criteria : slopes, precipitation, temperature, soil type, distance from coast line and land use
The application of the fuzzy functions for each of the factors allowed the creation of a series of raster maps that reflected their particular importance for the cultivation of each species.