Spatial Decision

8/19/2019 Spatial Decision

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Spatial Decision Support System

By

Dr.Umair bin Zamir


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What is Spatial Decision Support System


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Lets Discuss Spatial

Spatial is relating to Space….

For eg. Spatial distribution of Population

Spatial distribution of Crimes

Spatial distribution of Diseases

Spatial distribution of Languages

Spatial distribution of Religions

Spatial distribution of Fauna

Spatial distribution of Flora


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Lets Discuss Decision

Decision is a conclusion or resolution reached after consideration

OR

The action or process of deciding something or of resolving a question

OR

The ability or tendency to make decisions quickly; decisiveness


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Lets Discuss Support System

Support System Formal or informal network of

goods, services, personnel, and organizations that

sustains an entity in its survival and growth.

OR

A set of things working together as parts of a mechanism

or an interconnecting network; a complex whole

OR

A set of principles or procedures according to which

something is done; an organized scheme or method


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Now What is Spatial Decision Support System

A spatial decision support system (SDSS) is an interactive, computer-based system

designed to assist in decision making while solving a semi-structured spatial

problem. It is designed to assist the spatial planner with guidance in making land use

decisions.


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Course Outline


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Decision Support System

Decision Support Systems (DSS) are a class of computerizedinformation system that support decision-making activities. DSS

are interactive computer-based systems and subsystems intended

to help decision makers use communications technologies, data,

documents, knowledge and/or models to complete decisionprocess tasks.

A decision support system may present information graphically and

may include an expert system or artificial intelligence (AI). It may beaimed at business executives or some other group of knowledge

workers.


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• Accessing all information assets, including legacy and relational data sources.

• Comparative data figures

• Projected figures based on new data or assumptions

• Consequences of different decision alternatives, given past experience in a specific context

Typical information that a decision support application might gather and present would be


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Taxonomy of Decision Support System

There are a number of Decision Support Systems These can be categorized into five types:

• Communication driven DSS

•Data driven DSS

• Document driven DSS

• Knowledge driven DSS

• Model driven DSS


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• Communication driven DSS

A C-D DSS is a type of DSS that enhances decision-making by enabling communication and

sharing of information between groups of people. At its most basic level a C-D DSS could be a

simple threaded e-mail. At its most complex it could be a web-conferencing application or

interactive video.

Communication-Driven DSS will exhibit at least one of the following characteristics:

Supports coordination and collaboration between two or more people;

Facilitates information sharing;

Enables communication between groups of people;

Supports group decisions.


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Data driven DSS

Data-driven DSS are a form of support system that focuses on the provision of internal (and

sometimes external) data to aid decision making. Most often this will come in the form of a

data warehouse – a database designed to store data in such a way as to allow for its querying

and analysis by users.

Another example of a data-driven DSS would be a Geographic Information System (GIS), which

can be used to visually represent geographically dependent data using maps.


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Document driven DSS

Document-driven DSS are support systems designed to convert documents into valuable business data.

While data-driven DSS rely on data that is already in a standardized format that lends itself to database

storage and analysis, document-driven DSS makes use of data that cannot easily be standardized and

stored. The three primary forms of data used in document driven DSS are:

Oral (i.e. transcribed conversations);

Written (i.e. reports, memos, e-mail and other correspondence);

Video (i.e. TV commercials and news reports).

None of these formats lend themselves easily to standardized database storage and analysis, so managers

require DSS tools to convert them into data that can be valuable in the decision making process.

Document-driven DSS is the newest field of study in Decision Support Systems. Examples of document-

driven tools can be found in Internet search engines, designed to sift through vast volumes of unsorted

data through the use of keyword searches.


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Knowledge driven DSS

Knowledge-driven DSS are systems designed to recommend actions to users. Typically,

knowledge-driven systems are designed to sift through large volumes of data, identify hidden

patterns in that data and present recommendations based on those patterns.

Knowledge-driven DSS can store and apply knowledge for a variety of specific problems/tasks

that would otherwise be resolved by a human expert. The generic tasks include classification,

configuration, diagnosis, interpretation, planning and prediction.


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Model driven DSS

Model-driven support systems incorporate the ability to manipulate data to generate

statistical and financial reports, as well as simulation models, to aid decision-makers. Model-

based decision support systems can be extremely useful in forecasting the effects of changes

in business processes, as they can use past data to answer complex ‘what-if’ questions for

decision makers.

In general, model-driven DSS use more complex models, e.g., accounting, optimization and

simulation, to provide decision support. In most implementations, model-driven DSS use the

data and parameters provided by a decision maker to help in analyzing a situation.


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In addition to these basic types of DSS there are also two additional factors: whether the DSS

is spreadsheet-based, web-based or something else entirely.

• Spreadsheet-based DSS

Model- and Data-driven DS systems can be built using spreadsheets. Spreadsheets offer

decision-makers easy to understand representations of large amounts of data. Additionally,

spreadsheet data is arranged in such a way as to make it easy to convert the data into

visualizations to further aid decision-makers.

* Web-based DSS

Any type of DSS can be web-based. The term simply describes any decision support system

that is operated through the interface of a web browser, even if the data used for decision

support remains confined to a legacy system such as a data warehouse.


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Scope of DSS

In addition to these basic types of Decision Support System there are also two separate

categories used to define systems.

* Enterprise-wide DSS

Enterprise-wide DS systems are systems that are linked into large data warehouses, and offer

decision support to managers at all levels of an enterprise. Enterprise-wide systems willtypically be basic, general use systems that can perform a wide variety of functions.

* Desktop DSS

Desktop DS systems are much smaller applications designed to be run from a desktop PC.

While these systems may well be linked into a data warehouse or other large volume of data,they will typically be more limited in scope.

An example of a desktop DSS is Microsoft Excel, the desktop spreadsheet application.


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Historical Background

• Decision Support System (DSS) based on work by Herbert A. Simon in

1950s and 1960s (Simon 1960);

• DSS evolved during the 1970s and 80s

• SDSS concept has evolved in parallel

• IBM's Geodata Analysis and Display System 1970s earliest large DSS

• SDSS has been associated with the need to expand the GIS capabilities for

complex, ill-defined, spatial decision problems

• Major growth in research, development, and applications of SDSS in the

last 10 years

• Many threads with different, but related names, such as collaborative

SDSS, group SDSS, environmental DSS, spatial knowledge based and expert

systems, PPGIS


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The Decision-making Process

• Simon divides any decision-making process into the

phases of decision-making

– intelligence - is there a problem or an opportunity

for change? – design - what are the decision alternatives?

– choice - which alternative is best?


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Simon’s Model


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Planning Stages

• Problems

• Goals

• Objectives

• Alternatives

• Evaluations

• Choice

• Implementation

• Monitoring


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Planning Methods

• SWOT (Strength, weakness, opportunities threats)

• Bargaining

• Brainstorming

• Scenario writing

• Consensus building

• Public meeting support

• Charrette

• Consultants

• Stakeholder involvement

• Outreach


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Decision Making Process


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Characteristics of SDSS

1. Designed to solve ill- or semi-structured problems, i.e. where

objectives cannot be fully or precisely defined

2. Have an interface that is both powerful and easy to use.

3. Enable the user to combine models and data in a flexible manner.

4. Help the user explore the solution space (the options available to

them) by using the models in the system to generate a series of

feasible alternatives


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5. Support a variety of decision-making styles, and easily

adapted to provide new capabilities as the needs of the

user evolve .

6. Problem solving is an interactive and recursive process in

which decision making proceeds by multiple passes,

perhaps involving different routes, rather than a single

linear path


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These characteristics also define a SDSS

• In addition, in order to effectively support

decision- making for complex spatial problems, aSDSS will need to: provide for spatial data input

• allow storage of complex structures common in

spatial data

• include analytical techniques that are unique to

spatial analysis

• provide output in the form of maps and other

spatial forms


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Spatial decision making

• many spatial problems are complex and

require the use of analysis and models

• many spatial problems are semi-structured or

ill-defined because all of their aspects cannot

be measured or modeled


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Example: site selection for a retail store

objective is to pick the site which will maximize economic return to the company

•return is affected by:

•number of potential customers within market area•accessibility of the site (e.g. is it on a main street? is it possible to turn left into the site?)

•visibility, signage, appearance

•cost of site and construction

• some of these factors are difficult to evaluate or predict

• relative impacts of each of these factors on return may be unknown (except the last - direct

cost)

• impossible to structure the problem completely - i.e. define and precisely measure the

objective for every possible solution

• retail site selection problem is ill-structured

• a system to support retail site selection must be flexible allow new factors to be introduced

o allow the relative importance of factors to be changed to evaluate sensitivity or to reflect

differences of opinion

• display results of analysis in informative ways


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• solutions to this class of problems often are obtained by generatinga set of alternatives and selecting from among those that appear tobe viable

• thus, the decision-making process is iterative, integrative andparticipative iterative because a set of alternative solutions is

generated which the decision-maker evaluates, and insights gainedare input to, and used to define, further analyses

• participative because the decision-maker plays an active role indefining the problem, carrying out analyses and evaluating theoutcomes

• integrative because value judgements that materially affect the

final outcome are made by decision-makers who have expertknowledge that must be integrated with the quantitative data in themodels


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SDSS ARCHITECTURE

• Armstrong and Densham (1990) suggest that

five key modules are needed in a SDSS:

• a database management system (DBMS)

• analysis procedures in a model base

management system (MBMS)

• display generator

• a report generator

• a user interface

Documents

Spatial Decision