2011 ◽  
Vol 02 (03) ◽  
pp. 195-203 ◽  
Author(s):  
Yanli Zhang ◽  
Ramanathan Sugumaran ◽  
Matthew McBroom ◽  
John DeGroote ◽  
Rebecca L Kauten ◽  
...  

Author(s):  
B. Yatsalo ◽  
V. Didenko ◽  
A. Tkachuk ◽  
S. Gritsyuk ◽  
O. Mirzeabasov ◽  
...  

Land-use planning and environmental management often requires an implementation of both geo- spatial information analysis and value-driven criteria within the decision-making process. DECERNS (Decision Evaluation in Complex Risk Network Systems) is a web-based distributed decision support system for multi-criteria analysis of a wide range of spatially-explicit land management alternatives. It integrates mainly basic and some advanced GIS functions and implements several Multi-Criteria Decision Analysis (MCDA) methods and tools. DECERNS can also be integrated with a model server containing generic and site specific models for in-depth analysis of project and environmental risks as well as other decision criteria under consideration. This paper provides an overview of the modeling approaches as well as methods and tools used in DECERNS. Application of the DECERNS WebSDSS (Web-based Spatial Decision Support System) for a housing site selection case study is presented.


Author(s):  
Ramanathan Sugumaran ◽  
Shriram Ilavajhala ◽  
Vijayan Sugumaran

A SDSS combines database storage technologies, geographic information systems (GIS) and decision modeling into tools which can be used to address a wide variety of decision support areas (Eklund, Kirkby, and Pollitt, 1996). Recently, various emerging technologies in computer hardware and software such as speedy microprocessors, gigabit network connections, fast internet mapping servers along with Web-based technologies like extensible markup language (XML), Web services, etc provide promising opportunities to take the traditional spatial decision support systems one step further to provide easy-to-use, round-the-clock access to spatial data and decision support over the Web. Traditional DSS and Web-based spatial DSS can be further improved by integrating expert knowledge and utilizing intelligent software components (such as expert systems and intelligent agents) to emulate the human intelligence and decision making. These kinds of decision support systems are classified as intelligent decision support systems. The objective of this chapter is to discuss the development of an intelligent web-based spatial decision support system and demonstrate it with a case study for planning snow removal operations.


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