Multi Criteria Modelling In Gis

MULTI CRITERIA MODELLING IN GIS

Dr. S. K. Pathan Scientist ‘G’ and Head,

Geo-Informatics and Databases DivisionGovt. of India, Ahmedabad Space Applications Centre (ISRO),

MULTI CRITERIA MODELLING IN GIS MC MODELLING PLANNING SCENARIOS DECISION MAKING

Disaster Management Services

Water Services

Forest Services

G IS

Transport services

SPATIAL

Agriculture Services

Taxes

ASPATIAL

Municipal Services Railway Services

Water Supply Electricity

Pension, DCRG, Commutation, Family Pension, Medical Bills, Pay Fixation, Appraisals, Promotions

Birth/Death certificates

Administrative Services

MULTI CRITERIA MODELLING IN GIS

MULTI CRITERIA MODELLING IN GIS Option-1

Option-2

Criteria-2

Criteria-1

Option-3

Criteria-3

MULTI CRITERIA MODELLING IN GIS

MULTI CRITERIA MODELLING IN GIS

Connecting ‘N’ number of objects

MULTI CRITERIA MODELLING IN GIS Information

Information

MULTI CRITERIA MODELLING IN GIS Knowledge

Knowledge

MULTI CRITERIA MODELLING IN GIS Management

Management

MULTI CRITERIA MODELLING IN GIS Information and Knowledge Management

Knowledge

Information

Management MCM

MCM

DECISION MAKING

MULTI CRITERIA MODELLING IN GIS

INFORMATION

=

DATA LEGEND Forest land Agricultural land Waste land Rivers/Streams

MULTI CRITERIA MODELLING IN GIS INFORMATION

SPATIAL

ASPATIAL NON-GEOGRAPHIC

GEOGRAPHIC

LIS

OTHERS

CAD/CAM

CENSUS

PARCEL BASED NON-PARCEL

OTHERS

TAXONOMY OF INFORMATION SYSTEM

MULTI CRITERIA MODELLING IN GIS

DATA

=

INFORMATION = KNOWLEDGE

INFORMATION KNOWLEDGE

= MANAGEMENT

MULTI CRITERIA MODELLING IN GIS IT – Information Technology IM – Information Management

DATA

-

?

Alpha or Numeric Punya Vishaya

INFORMATION ?

--

937

Punya Vishaya city -- Year 937

Data within a context

Punya Vishaya (Pune) city found in the Year 937

KNOWLEDGE

?

Combination of Information

KM – Knowledge Management People and Processes

MULTI CRITERIA MODELLING IN GIS

KNOWLEDGE MANAGEMENT An integration of ‘People, Process and Technology’ to enable the harnessing of an organisation’s information elements into an ‘Intuitive and Dynamic collection of Knowledge Assets’ that will provide ‘Value, Advantage and Benefit’ to the enterprise KM TOOLS - Notes , Documentation, Live link and Fulcrum

MULTI CRITERIA MODELLING IN GIS

GPS GPR TS

RS / GIS

GEOINFORMATICS

PHOTOGRAMMETRY

CARTOGRAPHY

MULTI CRITERIA MODELLING IN GIS Information, Knowledge and Management

Transparency, Speed, Less Cost and Man power

MULTI CRITERIA MODELLING IN GIS Advances in geo-information technology, has created very efficient possibility of collecting, and managing large amounts of data for earth resource processes in various form and scales. Remote Sensing and GIS technology have offered a great potential to capture data through variety of Earth Observation Platforms, and integrate/relate them through their common spatial denominator. They also offer appropriate technology for data management, information extraction, routine manipulation and visualization, but they lack necessary analytical capabilities to support management and decision-making processes.

MULTI CRITERIA MODELLING IN GIS In many cases now the problem is not lack of data/information, but the selection and process of data to generate meaningful and timely information that can support better management of resources. For improved decision-making, the required information, tools, techniques, models and decision-making procedure have to become integrated in a user-friendly information processing system called "Spatial Decision Support Systems (SDSS)”. SDSS provide insight in to the tradeoffs between various options that decision makers are facing.

MULTI CRITERIA MODELLING IN GIS DECISION SUPPORT SYSTEM

A DECISION SUPPORT SYSTEM INVOLVES THE INTEGRATION OF SPATIALLY REFERENCED DATA IN

A

PROBLEM

SOLVING

ENVIRON-MENT.

Source : Cowen, 1988

MULTI CRITERIA MODELLING IN GIS Principles and components of multiple-criteria decision making. Multiple-criteria evaluation methods/techniques. Theory and practice of spatial multiple criteria evaluation Application of spatial multiple-criteria evaluation method in planning and decision making. Application of the above techniques in case studies

MULTI CRITERIA MODELLING IN GIS

MULTI CRITERIA MODELLING IN GIS DATA MODEL : A procedure used to convert the geographic variation into “GIS” Geographic features are represented with ‘x,y’ cartesian co-ordinate system Lines and points are represented by their explicit x,y coordinates. Vector format is best suited for representing spatial objects with high coordinate precision. Storage space less.

Area is divided into a regular array of cells. Fineness is limited by the cell size. Space filling GIS One set of cells and associated values – Layer Storage space high QUAD TREE: Area of interest is recursively decomposed. Storage space less.

MULTI CRITERIA MODELLING IN GIS

MULTI CRITERIA MODELLING IN GIS RASTER MODEL

VECTOR MODEL

TELLS WHAT OCCURS EVERY WHERE, AT EACH PLACE IN THE AREA.

TELLS WHERE EVERYTHING OCCURS, GIVES A LOCATION TO EVERY OBJECT.

IT SUFFERS TO REPRESENT PRECISE DETAILS OF MEASURED QUANTITIES DUE TO DESCRETISATION.

IT IS PRECISE AND HAS NO APPROXIMATE ERRORS FOR THE MEASURED QUANTITIES LIKE AREA, LENGTH AND PERIMETER.

POINTS, LINES, POLYGONS ARE NOT RECOGNISED AS OBJECTS IN THEIR OWN MERIT.

POINTS, LINES, POLYGONS ARE NOT RECOGNISED IN THEIR OWN MERIT (ACCURACY IS HIGH). COMPUTATION SLOW.

MULTI CRITERIA MODELLING IN GIS RASTER MODEL COMPUTATION FASTER

VECTOR MODEL COMPUTATION SLOW

MULTI CRITERIA MODELLING IN GIS DECISION MAKING It is a COGNITIVE PROCESS leading to the selection of a course of action among variations. Every decision making process produces a final choice. It can be an action or an opinion. It begins when we need to do something but know not what ? Decision making is a reasoning process which can be rational or irrational, and can be based on explicit assumptions or tacit assumptions.

MULTI CRITERIA MODELLING IN GIS DECISION MAKING Examples:

Where to go for SHOPPING ? What to EAT ? When to SLEEP ? Decide what or whom to VOTE ?

MULTI CRITERIA MODELLING IN GIS DECISION MAKING SWOT Analysis - Evaluation by the decision making individual or organization of Strengths, Weaknesses, Opportunities and Threats with respect to desired end state or objective. Analytic Hierarchy Process - procedure for multi-level goal hierarchy Buyer decision processes - transaction before, during, and after a purchase Complex systems - common behavioural and structural features that can be modelled Cost-benefit analysis - process of weighing the total expected costs vs. the total expected benefits Control-Ethics, a decision making framework that balances the tensions of accountability and 'best' outcome.

MULTI CRITERIA MODELLING IN GIS DECISION MAKING Decision trees Program Evaluation and Review Technique (PERT) critical path analysis critical chain analysis Force field analysis - analyzing forces that either drive or hinder movement toward a goal Grid Analysis - analysis done by comparing the weighted averages of ranked criteria to options. A way of comparing both objective and subjective data. Linear programming - optimization problems in which the objective function and the constraints are all linear Morphological analysis - all possible solutions to a multi-dimensional problem complex

MULTI CRITERIA MODELLING IN GIS  Optimization

DECISION MAKING

 Paired Comparison Analysis : Paired choice analysis  Pareto Analysis : selection of a limited of number of tasks that produce significant overall effect

 Robust decision : making the best possible choice when information is incomplete, uncertain, evolving and inconsistent

 Satisfying : In decision-making, satisfying explains the tendency to select the first option that meets a given need or select the option that seems to address most needs rather than the “optimal” solution.

 Scenario analysis : process of analyzing possible future events  Six Thinking Hats : symbolic process for parallel thinking

 Strategic planning process : applying the objectives, SWOTs, strategies, programs process

MULTI CRITERIA MODELLING IN GIS MULTIVARIATE TECHNIQUES Multivariate Technique

Purpose of Technique

1. Descriptive multivariate methods

Data exploration; identifying patterns and relationships

2. Principal Component Analysis

Dimension reduction by forming new variables (the principal components) as linear combinations of the variables in the multivariate set.

3. Cluster Analysis

Identification of natural groupings amongst cases or variables

4. Factor Analysis

Modeling the correlation structure among variables in the multivariate response set by relating them to a set of common factors.

5. Multivariate Analysis of Variance

Extending the univariate analysis of variance to the simultaneous study of several variates. The aim is to partition the total sum of squares and cross-products matrix amongst a set of variates according to the experimental design structure.

MULTI CRITERIA MODELLING IN GIS MULTIVARIATE TECHNIQUES 6. Discriminant Analysis

Determining a function that enables two or more groups of individuals to be separated on the basis of multiple responses on all individuals in the groups.

7. Canonical Correlation Analysis

Studying the relationship between two groups. It involves forming pairs of linear combinations of the variables in the multivariate set so that each pair in turn, produces the highest correlation between individuals in the two groups.

8. Multidimensional Scaling

Constructing a “map” showing a spatial relationship between a number of objects, starting from a table of distances between the objects.

Descriptive Models

Multivariate Models

Discriminant Models

Cluster Models

MULTI CRITERIA MODELLING IN GIS FUZZY MODEL Fuzzy logic is derived from ‘Fuzzy Set Theory’ dealing with reasoning that is approximate rather than precisely deduced from classical predicate logic. It can be thought of as the application side of fuzzy set theory dealing with well thought out real world expert values for a complex problem (Klir 1997). Degrees of truth are often confused with probabilities. However, they are conceptually distinct; fuzzy truth represents membership in vaguely defined sets, not likelihood of some event or condition.

MULTI CRITERIA MODELLING IN GIS FUZZY ANALYSIS Fuzzy logic is a superset of conventional (Boolean) logic that has been extended to handle the concept of partial truth - truth values between "completely true" and "completely false". It is the logic underlying modes of reasoning which are approximate rather than exact. In fuzzy logic, exact reasoning is viewed as a limiting case of approximate reasoning. In fuzzy logic everything is a matter of degree. Any logical system can be fuzzified In fuzzy logic, knowledge is interpreted as a collection of elastic or, equivalently , fuzzy constraint on a collection of variables Inference is viewed as a process of propagation of elastic constraints

MULTI CRITERIA MODELLING IN GIS FUZZY ANALYSIS

The Temp. of a Room

MULTI CRITERIA MODELLING IN GIS FUZZY ANALYSIS

Fuzzy Sets to Characterize the Temp. of a Room

MULTI CRITERIA MODELLING IN GIS FUZZY SET OPERATIONS UNION The membership function of the Union of two fuzzy sets A and B with membership functions µA and µB respectively is defined as the maximum of the two individual membership functions. This is called the maximum criterion.

The Union operation in Fuzzy set theory is the equivalent of the OR operation in Boolean algebra.

MULTI CRITERIA MODELLING IN GIS FUZZY ANALYSIS INTERSECTION The membership function of the Intersection of two fuzzy sets A and B with membership functions respectively is defined as the minimum of the two individual membership functions. This is called the minimum criterion.

The Intersection operation in Fuzzy set theory is the equivalent of the AND operation in Boolean algebra.

MULTI CRITERIA MODELLING IN GIS FUZZY ANALYSIS The membership function of the Complement of a Fuzzy set A with membership function is defined as the negation of the specified membership function. This is called the negation criterion.

The Complement operation in Fuzzy set theory is the equivalent of the NOT operation in Boolean algebra.

MULTI CRITERIA MODELLING IN GIS FUZZY ANALYSIS The common rules in classical set theory also apply to Fuzzy set theory. De Morgans law

, Associativity

, Commutativity

Distributivity

,

MULTI CRITERIA MODELLING IN GIS

INTERPOLATION MODELS I) II) III) IV) V) VI) VII)

LINEAR BI-LINEAR INVERSE DISTANCE WEIGHTED KRIGING QUITIC TREND SPLINE

MULTI CRITERIA MODELLING IN GIS

SPATIAL DECISION SUPPORT SYSTEM AND MULTI CRITERIA MODELS

D E C I S I O N M A K I N G

WHAT TO DO AND WHAT NOT DO WITH GEOINFORMTICS TECHNOLOGY ?

MULTI CRITERIA MODELLING IN GIS

SPATIAL DECISION SUPPORT SYSTEM AND MULTI CRITERIA MODELS

MULTI CRITERIA MODELLING IN GIS

SPATIAL DECISION SUPPORT SYSTEM AND MULTI CRITERIA MODELS

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