Spatial Decision Support Systems: Principles and Practices, 1st Edition (Hardback) book cover

Spatial Decision Support Systems

Principles and Practices, 1st Edition

By Ramanathan Sugumaran, John Degroote

CRC Press

508 pages | 184 B/W Illus.

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Although interest in Spatial Decision Support Systems (SDSS) continues to grow rapidly in a wide range of disciplines, students, planners, managers, and the research community have lacked a book that covers the fundamentals of SDSS along with the advanced design concepts required for building SDSS.

Filling this need, Spatial Decision Support Systems: Principles and Practices provides a comprehensive examination of the various aspects of SDSS evolution, components, architecture, and implementation. It integrates research from a variety of disciplines, including the geosciences, to supply a complete overview of SDSS technologies and their application from an interdisciplinary perspective.

This groundbreaking reference provides thorough coverage of the roots of SDSS. It explains the core principles of SDSS, how to use them in various decision making contexts, and how to design and develop them using readily available enabling technologies and commercial tools. The book consists of four major parts, each addressing different topic areas in SDSS:

  1. Presents an introduction to SDSS and the evolution of SDSS
  2. Covers the essential and optional components of SDSS
  3. Focuses on the design and implementation of SDSS
  4. Reviews SDSS applications from various domains and disciplines—investigating current challenges and future directions

The text includes numerous detailed case studies, example applications, and methods for tailoring SDSS to your work environment. It also integrates sample code segments throughout. Addressing the technical and organizational challenges that affect the success or failure of SDSS, the book concludes by considering future directions of this rapidly emerging field of study.


This timely book begins with coverage of basic geospatial data handling concepts, methods, and materials. … places the development of SDSS concepts within a historical framework of development and treats important system components with a level of detail that is appropriate for students who may have different backgrounds or be at different stages of intellectual development. Coverage then moves on to demonstrate how these components can be assembled into flexible collections that are used to address particular types of applications. It is here, with the illustration of different component assemblages, that the book coheres by demonstrating how an SDSS can be implemented in the form of a traditional desktop system or using distributed, web-based services. This is done in a way that should prove instructive to both students and their teachers. I sincerely hope that you enjoy reading and learning from this book and that it will lead you to contribute new insights. I came away from it wishing that the book had been available to me many years ago when I was beginning to struggle with the SDSS concepts that now seem rather straightforward after having read these chapters.

—Marc P. Armstrong, Professor and Chair, Department of Geography, University of Iowa

Sugumaran (geography) and DeGroote (geo-informatics, both U. of Northern Iowa) explain systems that are designed to help decision makers solve complex spatially related problems and provide a framework for integrating analytical and spatial modeling capabilities, spatial and non-spatial data management, domain knowledge, spatial display capabilities, and reporting capabilities. They cover evolution and trends in spatial decision support systems, geographical information systems and other components, software and building it, building a desktop system and a web-based system, applications, and challenges and future directions.

—In Research Book News,, February 2011

The major strength of this book is the wide range of references cited, and every part of the text is supported by references to a wide literature. … [The book] provides readers with several relevant building frameworks and food for thought, especially in the fields of public engagement, planning, and GIS development.

—Cindy Regalado, Department of Civil, Environmental, and Geomatic Engineering, University College London, in Environment and Planning

Table of Contents


Spatial Decision Making

What Are Spatial Decisions?

Types of Spatial Decisions

Spatial Decision-Making Problems

Spatial Decision-Making Process

Need for Decision Support Systems

Definition of SDSS

SDSS Characteristics

Types or Flavors of SDSS

Evolution and Trends in SDSS

Origins of SDSS

Core Drivers for the Development of Spatial Decision Support Technology

Information and Communication Technology

Spatial Data Availability


Users, Developers, and User Interfaces

Spatially Explicit Modeling

Expert Domain Knowledge

DSS-Based Evolution


GIS-Based Evolution


SDSS Progression

Introduction Phase (1976–1989)

Integration Phase (1990–2000)

Implementation Phase (2000s)

Related and Important Literature

Important Contributors to SDSS Development

Suggested Readings




Components of SDSS I: Geographic Information Systems

Components of Traditional DSS and GIS

Components of SDSS

Geographical Information Systems (GIS) Overview

History of Spatial Information and Data Use

Definitions of GIS

Coordinate Systems

Data Models

Vector Data Model

Raster Data Model

Raster versus Vector

Spatial Data Collection

Database Management

Data Considerations

Spatial Data Exploration, Processing, and Analysis

Map Data Exploration

Data Identification, Examination, and Query

Vector Processing and Analysis


Spatial Overlay

Pattern Analysis and Spatial Statistics

Routing and Network Analysis

Raster Data Analysis

Local Operations

Neighborhood Operations

Zonal Operations

Data Visualization and Cartography

GIS Software

Appendix A: Spatial Data Sources for the United States

Appendix B: Global Spatial Data Sources

Appendix C: Links for Lists of Commercial and Open Source GIS Software

Components of SDSS II

Model Management Component

Modeling Techniques in SDSS

Generic Models

Boolean Overlays

Weighted Linear Combination

Analytical Hierarchy Process

Ordered Weighted Approach

Artificial Neural Networks

Cellular Automata

Genetic Algorithms

Agent-Based Models

Fuzzy Modeling Techniques

Application-Specific Models

Dialog Management Component

Stakeholders Component (SC)

Knowledge Management Component

SDSS Software

Existing SDSS Software

GIS Software Used in SDSS

Problem-Specific SDSS

Domain-Level SDSS

Generic SDSS

IDRISI Macro Modeler

ArcGIS ModelBuilder


Open Source Software


Building SDSS Software

SDSS Software Components

Common Software for Utilization in SDSS Development

Spatial Data Collection, Management, Analysis, and Visualization Software

Relational Database Management Software

Modeling Software

Knowledge Management Software

SDSS Development by Software Integration

Integration Technologies

Integration Strategies

Integration Issues

Design and Development of SDSS from Scratch

Enabling Technologies for the Development of Desktop SDSS

Programming Languages

Application Development Environments

Spatial Libraries

SDSS Generator—Geonamica

Web-Based SDSS Development and Architecture

Cloud Computing

Building Desktop SDSS

SDSS Development Considerations

SDSS Development Process

SDSS Development Examples

Spreadsheet-Based AHP SDSS (Microsoft Excel)

SpreadsheetSDSS Plug-in

Customizing Existing Desktop GIS (ArcGIS)

Creation of a New Generic SDSS Program

Building Web-Based SDSS

Web-Based SDSS Developed with ArcGIS Server

Web-Based SDSS for Environmentally Sensitive Areas

Web-Based SDSS Development with Open Source Software

Software Installation

Software Used

Architecture Used and Implementation

Open Source SDSS Download and Execution

Detailed Explanation and Code

Python Modules

View Templates

SDSS Applications

Reference Collection, Database Creation, and Web-Portal Development

Literature Compilation

SDSS Database Development

Web Portal Development

Publication Sources

SDSS Application Domains

Natural Resources Management




Utility/Communication/Energy and Transportation


Other Major Application Domains

SDSS Challenges and Future Directions

Technical Challenges

Spatial Data Management Component Challenges

Model Management Component

Model Selection or Development

Model Integration

Model Usability and Interpretation of Results

Dialog Management Component Challenges

User Interfaces

Output Presentation and Evaluation

Technological Challenges

Social, Policy, and Organizational Challenges

Educational Challenges

Future Trends and Directions

Each chapter starts with Learning Objectives and an Introduction, and concludes with a Summary and References

About the Authors

Dr. Ramanathan Sugumaran is Professor of Geography and Director of GeoTREE Center at the University of Northern Iowa. He has over nineteen years of research experience in remote sensing, geographic information systems (GIS), Global Positioning Systems (GPS), and spatial decision support systems (SDSS) with applications for natural resources and environmental planning and management.

Dr. Sugumaran has served as PI or Co-PI on over $5 million worth of research grants funded by the National Aeronautics and Space Administration (NASA), Raytheon Corp., the National Oceanic and Atmospheric Administration (NOAA), the U.S. Department of Defense (DOD), the U.S. Department of Agriculture (USDA), Missouri Department of Natural Resources (MDNR), the U.S. Department of Transportation (DOT), and the U.S. Fish and Wildlife Service. He has also published numerous journal articles and presented more than one hundred papers at national and international conferences. Dr. Sugumaran has two PhDs—a PhD in geography from the University of Edinburgh in the United Kingdom and one from the University of Baroda, India. For the past ten years, he has developed and taught several courses and advised more than twenty students on their masters theses. Dr. Sugumaran has also been a recipient of several academic awards that include the outstanding graduate faculty teaching award, Outstanding Scholar award, and Veridian Community Engagement Award.

John DeGroote is a GeoInformatics Scientist at the GeoTREE Center at the University of Northern Iowa. He has been actively applying geospatial technologies for environmental and natural resource applications for nine years. He has experience working on a wide range of issues with a diverse set of investigators including hydrologists, soil scientists, ecologists, and economists. He has extensive experience in developing custom GIS and SDSS applications, using programming and database development, for use by researchers and environmental managers. John has authored or co-authored numerous peer-reviewed articles concerning the use of geospatial technologies for a variety of application domains. He has also presented research at numerous national and international conferences.

Subject Categories

BISAC Subject Codes/Headings:
BUSINESS & ECONOMICS / Information Management
COMPUTERS / Computer Engineering
TECHNOLOGY & ENGINEERING / Environmental / General
TECHNOLOGY & ENGINEERING / Remote Sensing & Geographic Information Systems