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Agung Wahyudi Promoter: Prof Marc Van Meirvenne Co-promoter: ir. Liesbet Cockx Introduction GIS Decision Making Integration Recent Dev’t Conclusions Home
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GIS and Decision Making, Literature Review

Aug 17, 2014

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Page 1: GIS and Decision Making, Literature Review

Agung WahyudiPromoter: Prof Marc Van MeirvenneCo-promoter: ir. Liesbet Cockx

Introduction GIS Decision Making Integration Recent Dev’t ConclusionsHome

Page 2: GIS and Decision Making, Literature Review

© Agung Wahyudi 2

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

IntroductionHome

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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

IntroductionHome

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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.

IntroductionHome

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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

IntroductionHome

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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

IntroductionHome

“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.

IntroductionHome

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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.

IntroductionHome

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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.

IntroductionHome

“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

IntroductionHome

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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

Home

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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.