scholarly journals Collaborative spatial decision making in environmental restoration management: an experimental approach

2000 ◽  
Vol 2 (3) ◽  
pp. 197-206 ◽  
Author(s):  
Piotr Jankowski
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Spatial Data ◽  
Habitat Restoration ◽  
Spatial Information ◽  
Environmental Restoration ◽  
Spatial Decision Support ◽  
Restoration Management ◽  
Spatial Decision Making ◽  
Analytical Tools

This paper presents the results of an experimental study about the use of collaborative spatial decision support tools to aid environmental restoration management and decision making. Similar, but non-geographic tools were developed and successfully applied in the 1990s for the computerised support of group decision making aimed at solving business problems. Yet, there are significant differences between business applications and spatial applications including environmental management. These differences motivated the study of habitat restoration reported in this paper. The results demonstrate that maps—the most common representation structures of spatial data in geographic information systems—play only a limited support role. Development of new ways to visualise spatial information and novel integrations of maps with analytical tools including multiple criteria decision models may help develop more effective collaborative spatial decision support systems.

Flexible Spatial Decision-Making and Support

2011 ◽  
pp. 614-636
Author(s):  
Shan Gao ◽  
David Sundaram
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Decision Support Systems ◽  
Support Systems ◽  
Spatial Decision Support ◽  
Spatial Decision Support Systems ◽  
Location Allocation ◽  
Information Tools ◽  
Spatial Decision Making ◽  
Spatio Temporal

Spatial decision-making is a key aspect of human behaviour. Spatial decision support systems support spatial decision-making processes by integrating required information, tools, models and technology in a user-friendly manner. While current spatial decision support systems fulfil their specific objectives, they fail to address many of the requirements for effective spatial problem solving, as they are inflexible, complex to use and often domain-specific. This research blends together several relevant disciplines to overcome the problems identified in various areas of spatial decision support. We proposed a generic spatial decision-making process and a domain-independent spatial decision support system (SDSS) framework and architecture to support the process. We also developed a flexible SDSS to demonstrate an environment in which decision makers can utilize various tools and explore different scenarios to derive a decision. The use of the system is demonstrated in a number of real scenarios across location, allocation, routing, layout, and spatio-temporal problems.

Flexible Spatial Decision-Making and Support

2010 ◽  
pp. 532-555
Author(s):  
Shan Gao ◽  
David Sundaram
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Decision Support Systems ◽  
Support Systems ◽  
Spatial Decision Support ◽  
Spatial Decision Support Systems ◽  
Location Allocation ◽  
Information Tools ◽  
Spatial Decision Making ◽  
Spatio Temporal

Spatial decision-making is a key aspect of human behaviour. Spatial decision support systems support spatial decision-making processes by integrating required information, tools, models and technology in a user-friendly manner. While current spatial decision support systems fulfil their specific objectives, they fail to address many of the requirements for effective spatial problem solving, as they are inflexible, complex to use and often domain-specific. This research blends together several relevant disciplines to overcome the problems identified in various areas of spatial decision support. We proposed a generic spatial decision-making process and a domain-independent spatial decision support system (SDSS) framework and architecture to support the process. We also developed a flexible SDSS to demonstrate an environment in which decision makers can utilize various tools and explore different scenarios to derive a decision. The use of the system is demonstrated in a number of real scenarios across location, allocation, routing, layout, and spatio-temporal problems.

Flexible Spatial Decision-Making and Support

2011 ◽  
pp. 153-183 ◽  
Author(s):  
Shan Gao ◽  
David Sundaram
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Decision Support Systems ◽  
Support Systems ◽  
Spatial Decision Support ◽  
Spatial Decision Support Systems ◽  
Location Allocation ◽  
Information Tools ◽  
Spatial Decision Making ◽  
Spatio Temporal

Spatial decision-making is a key aspect of human behaviour. Spatial decision support systems support spatial decision-making processes by integrating required information, tools, models and technology in a user-friendly manner. While current spatial decision support systems fulfil their specific objectives, they fail to address many of the requirements for effective spatial problem solving, as they are inflexible, complex to use and often domain-specific. This research blends together several relevant disciplines to overcome the problems identified in various areas of spatial decision support. We proposed a generic spatial decision-making process and a domain-independent spatial decision support system (SDSS) framework and architecture to support the process. We also developed a flexible SDSS to demonstrate an environment in which decision makers can utilize various tools and explore different scenarios to derive a decision. The use of the system is demonstrated in a number of real scenarios across location, allocation, routing, layout, and spatio-temporal problems.

scholarly journals A new combination rule for Spatial Decision Support Systems for epidemiology

2019 ◽  
Vol 18 (1) ◽  
Author(s):  
Luciana Moura Mendes de Lima ◽  
Laísa Ribeiro de Sá ◽  
Ana Flávia Uzeda dos Santos Macambira ◽  
Jordana de Almeida Nogueira ◽  
Rodrigo Pinheiro de Toledo Vianna ◽  
...  
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Decision Support Systems ◽  
Spatial Information ◽  
Support Systems ◽  
Final Decision ◽  
Spatial Decision Support ◽  
Spatial Decision Support Systems ◽  
New Approach ◽  
Priority Levels

Abstract Background Decision making in the health area usually involves several factors, options and data. In addition, it should take into account technological, social and spatial aspects, among others. Decision making methodologies need to address this set of information , and there is a small group of them with focus on epidemiological purposes, in particular Spatial Decision Support Systems (SDSS). Methods Makes uses a Multiple Criteria Decision Making (MCDM) method as a combining rule of results from a set of SDSS, where each one of them analyzes specific aspects of a complex problem. Specifically, each geo-object of the geographic region is processed, according to its own spatial information, by an SDSS using spatial and non-spatial data, inferential statistics and spatial and spatio-temporal analysis, which are then grouped together by a fuzzy rule-based system that will produce a georeferenced map. This means that, each SDSS provides an initial evaluation for each variable of the problem. The results are combined by the weighted linear combination (WLC) as a criterion in a MCDM problem, producing a final decision map about the priority levels for fight against a disease. In fact, the WLC works as a combining rule for those initial evaluations in a weighted manner, more than a MCDM, i.e., it combines those initial evaluations in order to build the final decision map. Results An example of using this new approach with real epidemiological data of tuberculosis in a Brazilian municipality is provided. As a result, the new approach provides a final map with four priority levels: “non-priority”, “non-priority tendency”, “priority tendency” and “priority”, for the fight against diseases. Conclusion The new approach may help public managers in the planning and direction of health actions, in the reorganization of public services, especially with regard to their levels of priorities.

scholarly journals Argumentation Mapping in Collaborative Spatial Decision Making

2021 ◽  
Author(s):  
Claus Rinner
Keyword(s):  
Decision Making ◽  
Spatial Information ◽  
Collaborative Work ◽  
Spatial Decision Support ◽  
Application Development ◽  
Geographic Visualization ◽  
Current State ◽  
Visual Access ◽  
Spatial Decision Making ◽  
Collaborative Gis

Collaboration and decision-making of humans usually entails logical reasoning that is expressed through discussions and individual arguments. Where collaborative work uses geo-spatial information and where decision-making has a spatial connotation, argumentation will include geographical references. Argumentation maps have been developed to support geographically referenced discussions and provide a visual access to debates in domains such as urban planning. The concept of argumentation maps provides for explicit links between arguments and the geographic objects they refer to. These geo-argumentative relations do not only allow for cartographic representation of arguments, but also support the querying of both, space and discussion. Combinations of spatial queries and retrieval of linked arguments provide a powerful way of analyzing and summarizing the current state of a debate. In this chapter, we provide an overview of the original argumentation model and we discuss related research and application development. We also link argumentation mapping to related concepts in geographic visualization, spatial decision support systems, and public participation GIS under the umbrella of collaborative GIS.

Spatially Enabled Pipeline Route Optimization Model

2004 ◽  
Author(s):  
S. Raza Wasi ◽  
J. Darren Bender
Keyword(s):  
Decision Making ◽  
Optimization Problem ◽  
Environmental Design ◽  
Route Optimization ◽  
Design Criteria ◽  
Least Cost Path ◽  
Ahp Model ◽  
Spatial Decision Making ◽  
Pipeline Route ◽  
Analytical Tools

An interesting, potentially useful, and fully replicable application of a spatially enabled decision model is presented for pipeline route optimization. This paper models the pipeline route optimization problem as a function of engineering and environmental design criteria. The engineering requirements mostly deal with capital, operational and maintenance costs, whereas environmental considerations ensure preservation of nature, natural resources and social integration. Typically, pipelines are routed in straight lines, to the extent possible, to minimize the capital construction costs. In contrast, longer pipelines and relatively higher costs may occur when environmental and social considerations are part of the design criteria. Similarly, much longer pipelines are less attractive in terms of capital costs and the environmental hazard associated with longer construction area. The pipeline route optimization problem is potentially a complex decision that is most often undertaken in an unstructured, qualitative fashion based on human experience and judgement. However, quantitative methods such as spatial analytical techniques, particularly the least-cost path algorithms, have greatly facilitated automation of the pipeline routing process. In the past several interesting studies have been conducted using quantitative spatial analytical tools for finding the best pipeline route or using non-spatial decision making tools to evaluate several alternates derived through conventional route reconnaissance methods. Most of these studies (that the authors are familiar with) have concentrated on integrating multiple sources of spatial data and performing quantitative least-cost path analysis or have attempted to make use of non-spatial decision making tools to select the best route. In this paper, the authors present a new framework that incorporates quantitative spatial analytical tools with an Analytical Hierarchical Process (AHP) model to provide a loosely integrated but efficient spatial Decision Support System (DSS). Specifically, the goal is to introduce a fully replicable spatial DSS that processes both quantitative and qualitative information, balances between lowest-cost and lowest-impact routes. The model presented in this paper is implemented in a four step process: first, integration of multiple source data that provide basis for engineering and environmental design criteria; second, creation of several alternate routes; third, building a comprehensive decision matrix using spatial analysis techniques; and fourth, testing the alternative and opinions of the stakeholder groups on imperatives of AHP model to simplify the route optimization decision. The final output of the model is then used to carry out sensitivity analysis, quantify the risk, generate “several what and if scenarios” and test stability of the route optimization decision.

scholarly journals TRANSFORMATION OF THE DECISION SUPPORT SYSTEM MODEL FOR STANDARD SITUATIONS USING INTELLECTUAL AND ANALYTICAL METHODS

2021 ◽  
Vol 21 (3) ◽  
pp. 14-25
Author(s):  
V.V. Antonov ◽  
◽  
K.A. Konev ◽  
G.G. Kulikov ◽  
◽  
...  
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Decision Makers ◽  
Information Support ◽  
Accurate Identification ◽  
Interaction Structure ◽  
Typical Situation ◽  
Analytical Tools

The article discusses the issues of improving the efficiency of decision support activities on a relatively large amount of information. The research relevance is associated with the increasing complexity of control objects, which leads to a decrease in the efficiency of decision-making based on the personal experience of decision-makers, up to complete impossibility. The purpose of the ar-ticle is to analyze the problems faced by decision-makers and the creation of methods to improve the effectiveness of decision-making in typical situations. The article examines the main compo-nents of the intelligent subsystem of the decision support system, which require the use of analytical tools, and also forms the methods interaction structure necessary for the effective formation of sce-narios of information support for decision making. To achieve the goals, a decision support method based on an intelligent component was used, which is aimed at creating an effective infrastructure to sup-port decision-making; methods of identification and categorization, designed to implement the most accurate and correct comparison of the characteristics (state) of the observed situation and the characteristics of a typical situation stored in the knowledge base; correlation methods aimed at finding dependencies between the characteristics of situations and scenarios to solve problems associated with these situa-tions; a method for constructing subject qualimetry, used to form a predictive model to assess the degree of compliance of the selected scenario for solving the current situation. As a result, it was de-termined that an important aspect of decision-making in typical situations is the most accurate identification of the state of the situation, the choice of the best scenario for implementing the solu-tion for this situation and the analysis of the consequences of the selected set of measures. To solve these problems, a method for identifying a situation, a method for finding solution scenarios and a qualimetric method for predicting the effectiveness of the selected scenario have been formed. The article concludes that decision-making activities based on the accumulated experience can be im-proved by using the proposed methods and implementing a decision support system with an intelli-gent component.

Multi-Criteria Spatial Decision Support System DECERNS

2012 ◽  
pp. 255-273
Author(s):  
B. Yatsalo ◽  
V. Didenko ◽  
A. Tkachuk ◽  
S. Gritsyuk ◽  
O. Mirzeabasov ◽  
...  
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Land Use Planning ◽  
Spatial Information ◽  
Spatial Decision Support System ◽  
Spatial Decision Support ◽  
Network Systems ◽  
Web Based ◽  
Management Alternatives

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.

GIS Technique for Territorial Analysis

2011 ◽  
pp. 425-445
Author(s):  
Francesco Riccioli ◽  
Toufic El Asmar
Keyword(s):  
Decision Making ◽  
Spatial Data ◽  
Human Activities ◽  
Spatial Decision Support System ◽  
Complex Data ◽  
Spatial Decision Support ◽  
Territorial Planning ◽  
Analysis Process ◽  
Gis Technique ◽  
Territorial Analysis

Territorial analysis is related to the complexity of an area where human activities and environmental characteristics are the main development factors. Human activities have a direct (e.g. farm activities) and indirect (e.g. urban development/sprawl) influence on a territory and its environment, which gives an important function to such activities when strategies for territorial planning have to be defined. Several actors are involved in the assessment of a territory, which is a complicated feature of decision making to be achieved with the use of complex data-analysis process. The evolution of personal computer and specific software for the analysis of spatial data is giving important contribution to “Territorial Planning Strategies.” Spatial Decision Support System is an example of how problems occurred during a decision making process can be solved using methodologies that combine “Multicriteria Approach” and “Geographic Information System.” One of these methodologies is represented by “Spatial Multicriteria Decision Analysis.”

From CAD to GIS to the Geoweb: A Natural Evolution

2010 ◽  
Author(s):  
Steve Adam
Keyword(s):  
Decision Making ◽  
Spatial Data ◽  
Oil And Gas ◽  
Spatial Information ◽  
Digital Data ◽  
Computer Hardware ◽  
Disruptive Technology ◽  
Data Sets ◽  
Spatial Data Sets ◽  
Pipeline Design

Computer hardware and software have played a significant role in supporting the design and maintenance of pipeline systems. CAD systems allowed designers and drafters to compile drawings and make edits at a pace unmatched by manual pen drawings. Although CAD continues to provide the environment for a lot of pipeline design, Geographic Information Systems (GIS) are also innovating pipeline design through routines such as automated alignment sheet generation. What we have seen over the past two or three decades is an evolution in how we manage the data and information required for decision making in pipeline design and system operation. CAD provided designers and engineers a rapid electronic method for capturing information in a drawing, editing it, and sharing it. As the amount of digital data available to users grows rapidly, CAD has been unable to adequately exploit data’s abundance and managing change in a CAD environment is cumbersome. GIS and spatial data management have proven to be the next evolution in situations where engineering, integrity, environmental, and other spatial data sets dominate the information required for design and operational decision making. It is conceivable that GIS too will crumble under the weight of its own data usage as centralized databases become larger and larger. The Geoweb is likely to emerge as the geospatial world’s evolution. The Geoweb implies the merging of spatial information with the abstract information that currently dominates the Internet. This paper and presentation will discuss this fascinating innovation, it’s force as a disruptive technology, and oil and gas applications.

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