Spatial Decision Support Systems: Principles and Practices

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:



Presents an introduction to SDSS and the evolution of SDSS
Covers the essential and optional components of SDSS
Focuses on the design and implementation of SDSS
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.

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.

IntroductionSpatial Decision Making What Are Spatial Decisions? Types of Spatial Decisions Spatial Decision-Making ProblemsSpatial Decision-Making ProcessNeed for Decision Support SystemsDefinition of SDSSSDSS CharacteristicsTypes or Flavors of SDSS
Evolution and Trends in SDSSOrigins of SDSSCore Drivers for the Development of Spatial Decision Support Technology Information and Communication Technology Spatial Data Availability Applications Users, Developers, and User Interfaces Spatially Explicit Modeling Expert Domain KnowledgeDSS-Based Evolution DSS to SDSSGIS-Based Evolution GIS to SDSSSDSS Progression Introduction Phase (1976–1989) Integration Phase (1990–2000) Implementation Phase (2000s)Related and Important LiteratureImportant Contributors to SDSS DevelopmentSuggested ReadingsDSS GIS SDSS


Components of SDSS I: Geographic Information SystemsComponents of Traditional DSS and GISComponents of SDSSGeographical 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 Buffering 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 SoftwareAppendix A: Spatial Data Sources for the United StatesAppendix B: Global Spatial Data SourcesAppendix C: Links for Lists of Commercial and Open Source GIS Software

Components of SDSS IIModel Management ComponentModeling 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 ModelsDialog Management ComponentStakeholders Component (SC)Knowledge Management Component

SDSS SoftwareExisting SDSS Software GIS Software Used in SDSS Problem-Specific SDSS Domain-Level SDSS Generic SDSS IDRISI Macro Modeler ArcGIS ModelBuilder ERDAS IMAGINE Open Source Software Open-SDSS

Building SDSS SoftwareSDSS 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 IssuesDesign and Development of SDSS from ScratchEnabling Technologies for the Development of Desktop SDSS Programming Languages Application Development Environments Spatial Libraries SDSS Generator—GeonamicaWeb-Based SDSS Development and Architecture Cloud Computing

Building Desktop SDSSSDSS Development ConsiderationsSDSS Development ProcessSDSS 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 SDSSWeb-Based SDSS Developed with ArcGIS Server Web-Based SDSS for Environmentally Sensitive AreasWeb-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 ApplicationsReference Collection, Database Creation, and Web-Portal Development Literature Compilation SDSS Database Development Web Portal DevelopmentPublication SourcesSDSS Application Domains Natural Resources Management Environmental Urban Agriculture Utility/Communication/Energy and Transportation Business Other Major Application Domains

SDSS Challenges and Future DirectionsTechnical 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 EvaluationTechnological ChallengesSocial, Policy, and Organizational ChallengesEducational ChallengesFuture Trends and Directions
Each chapter starts with Learning Objectives and an Introduction, and concludes with a Summary and References