GIS-based Decision Support System Research Articles

Spatial ordered weighted averaging: incorporating spatially variable attitude towards risk in spatial multi-criteria decision-making

The paper discusses a decomposition–analysis–aggregation approach to multi-criteria spatial decision-making and proposes a novel aggregation method applicable to problems of the object-location or suitability for application type, concentrating on methodological rather than software development aspects. The approach allows the decision maker to: (a) break the problem down into a series of elementary (easier to understand) problems, (b) analyse them (in the broad sense of the word), and then (c) produce an answer for the complex problem by aggregating the answers derived for the elementary problems. The choice of methodology used for this aggregation is very important as different aggregating techniques may yield different results to the (same) original problem. The method presented here, which is in effect an extension of the ordered weighted averaging (OWA) method into a spatial decision-making technique, is termed spatial ordered weighted averaging (SOWA). The main advantage of the method proposed is the incorporation of spatially variable attitude to risk into the decision-making process. The mathematical background of the method and an example of its application in urban water management are presented and discussed. The authors suggest that the method could be useful as an analytical and decision-making tool for the incorporation of spatially variable risk perception in GIS-based decision support systems.

GIS-based decision support system for wood logistics

A wood logistics system was combined with a linear programming (LP) method utilizing GIS-based techniques on the platform of GIS software-ARC/INFO. The combined costs of road and off-road transport were taken as the objective function to find the least cost route and the optimal landing locations of wood transportation. Then transport costs and allowable wood volume of stands were calculated. An LP model was developed to allocate timber resources among mills in order to minimize the wood logistics costs from harvesting sites to mills. The parameters of the LP model, including the transport costs, allowable wood volume and wood orders, were written into a text file in MPS format which were then accessed by LINDO to solve the LP problem. The system is an effective tool to manage logistics, information and funds together in order to increase the speed of wood logistics and reduce the cost. The benefits and efficiency of mill cluster can be improved. The focal firm in the cluster can be competitive.

Beyond Modelling: Linking Models with GIS for Flood Risk Management

Spatially explicit hydrodynamic flood models can play animportant role in natural hazard risk reduction. A key element of these models that make them suitable for riskreduction is the ability to provide time-series inundation information about the onset, duration and passingof a hazard event. Such information can be critical for landuse planning, for mapping evacuation egress routes,and for locating suitable emergency shelters to name only a few risk treatments. This research contends that abarrier to effective risk reduction is providing disaster managers with access to model results in a structured andflexible framework that allows consequences of different hazard scenarios to be assessed and mapped. Toaddress these limitations, a framework has been developed that links a commercial relational databasemanagement system with a GIS-based decision support system. The framework utilises industry standard dataexchange protocols and results in efficient time-series hazard data management. A case study based in Cairns,in far-north coastal Australia is presented to illustrate how the system has been developed. Results show that theframework reduces data volumes significantly, while making pre-run modelled inundation results rapidly accessibleto disaster managers. Of note is the ability of the framework to present results in terms of risk to buildings,roads and other spatial features in urban regions, and to provide answers to relatively complex risk questions.

A GIS-enabled comparison of fixed and discriminatory pricing strategies for potential switchgrass-to-ethanol conversion facilities in Alabama

Ethanol is produced from organic material and is important as a strategic and cleaner alternative to fossil fuels. The cost of producing ethanol, which ultimately affects its price and demand, depends to a large extent on the delivered cost of raw materials. For a planned ethanol production facility, the cost of raw material is a function of (1) the facility location, (2) the facility size, and (3) the method of procurement. In a previous paper, two of the authors provided a methodology for computing a marginal price “surface” to better understand the location decision under several facility size scenarios. The methodology was implemented in a GIS-based decision support system to investigate the economic feasibility of locating a switchgrass-to-ethanol conversion facility in Alabama. In this paper, we use the methodology to construct delivered cost surfaces in order to evaluate two methods of procurement pricing; fixed and discriminatory. In the fixed pricing method of procurement, the facility pays one fixed price per delivered tonne. In the discriminatory pricing method of procurement, the facility pays a source-specific price per tonne before delivery and then pays the cost of delivery transportation. The results from the current study confirm the cost advantage of discriminatory over fixed pricing. However, it was observed that the relative cost advantage showed considerable variation as a function of location and facility size.

A GIS based decision support system for estimation, visualization and analysis of air pollution for large Turkish cities

A decision support system has been developed to support local authorities in air quality management for big Turkish cities. The system is based on CALPUFF dispersion model, digital maps and related databases to estimate the emissions and spatial distribution of air pollutants. It applies a geographical information system. The system estimates ambient air pollution levels at high temporal and spatial resolutions. The system enables mapping of emissions and air quality levels. Mapping and scenario results can be compared with air quality limits. Impact assessment of air pollution abatement measures can also be carried out.

DRIPS - a decision support system estimating the quantity of diffuse pesticide pollution in German river basins

The GIS based decision support system DRIPS--Drainage Spraydrift and Runoff Input of Pesticides in Surface Waters--has been developed to estimate the predicted environmental concentration (PECsw) of pesticides in surface waters resulting from diffuse sources. PECsw can be calculated on a catchment scale by quantifying the expected mean daily inputs of pesticides via surface runoff, tile drainage and spraydrift for various types of river basins characterized by their daily discharges. DRIPS is fitted with a Graphical User Interface (GUI) to provide easy access to the model algorithms. Model parameters like dose rate, DT50, Koc and date of pesticides application, etc. can be modified by the user in order to generate customized scenarios predicting PECsw for a choice of field crops, orchards and vineyards. Results are available as grid cell maps for the territory of Germany with high temporal and spatial resolution featuring distinct PECsw values for approximately 400 catchments.

DRIPS—a DSS for estimating the input quantity of pesticides for German river basins

The GIS-based decision support system (DSS)—drainage runoff input of pesticides in surface water, DRIPS—has been developed on behalf of the German EPA (UBA) for exposure assessment of agriculturally used pesticides in surface waters. The tool estimates the quantity of pesticide input from non-point sources via surface runoff, tile drainage and spraydrift. Furthermore, the resulting predicted environmental concentration of pesticides in surface waters (PEC sw) can be calculated considering the mean daily inputs of substances into river basins, characterized by their daily discharge. A graphical user interface (GUI) was created to provide users of the DSS with easy access to the model algorithms. Model parameters such as sorption ( K oc), half-life (DT50), dose rate and application date of pesticides can be modified by the user in order to generate customized scenarios predicting PEC sw for a choice of field crops, orchards or vineyards. Results are available as grid cell maps for the territory of Germany, featuring monthly catchment specific PEC sw values.

A heuristic algorithm for solving hazardous materials distribution problems

A type of decision of major importance that directly affects the performance of a distribution system is the routing and scheduling of delivery trucks. The determination of hazardous materials distribution routes can be defined as a bi-objective vehicle routing problem with time windows since risk minimization accompanies the cost minimization in the objective function. The objective of this paper is to present a new heuristic algorithm for solving the bi-objective vehicle routing and scheduling problem. The proposed algorithm has been applied to several benchmark problems. The results of these applications seem to be quite encouraging. Furthermore, the proposed algorithm has been integrated within a GIS based decision support system for hazardous materials logistics operations providing valid preliminary results on a set of case studies.

A GIS-based decision support system for planning urban transportation policies

A decision support system (DSS) integrated in a geographical information system (GIS) for the analysis and evaluation of different transport policies is presented. The objective of the tool is to assist transport administrators enhance the efficiency of the transportation supply while improving environmental and energy indicators. The DDS works on three levels. The first performs the transport network analysis, the second assesses the energy consumption and pollutant emissions and the third evaluates the several policies selected. Road traffic is simulated using a deterministic, multi-modal traffic assignment model with capacity constraints. The model allows the estimation of traffic flow patterns within each link of the road network starting from the knowledge of the network characteristics and traffic demand. Energy consumption and pollutant emission calculations are based on the methodology developed by the CORINAIR working group. The evaluation of each policy scenario is based on a number of traffic, environmental and energy indicators. A multi-criteria analysis, where decision is based upon judging over appropriate weighted criteria, is adopted. Models are integrated in a GIS environment, which serves as the repository of the data as well as the user interface of the tool. The use of the tool is demonstrated through characteristic case studies on the Greater Athens Area in Greece. Two policy measures, one concerning the extension of the region where half of the private cars are prohibited from entering to the Municipality of Athens and the other the reduction of parking places in the same region by 50% are evaluated.

Development of a GIS-based decision support system for assessing land use status

The objectives of this study are to assess land suitability and to predict the spatial and temporal changes in land use types (LUTs) by using GIS-based land use management decision support system. A GIS database with data on climate, topography, soil characteristic, irrigation condition, fertilizer application, and special socioeconomic activities has been developed and used for the evaluation of land productivity for different crops by integrating with a crop growth model—the erosion productivity impact calculator (EPIC). International food policy simulation model (IFPSIM) is also embedded into GIS for the predictions of how crop demands and crop market prices will change under alternative policy scenarios. An inference engine (IE) including land use choice model is developed to illustrate land use choice behavior based on logit models, which allows to analyze how diversified factors ranging from climate changes, crop price changes to land management changes can effect the distribution of agricultural land use. A test for integrated simulation is taken in each 0.1o by 0.1o grid cell to predict the change of agricultural land use types at global level. Global land use changes are simulated from 1992 to 2050.

A GIS-based decision support system to identify nature conservation priorities in an alpine valley

This paper describes a methodological approach based on the integrated use of Geographical Information Systems (GIS) and Decision Support Systems (DSS) to identify nature conservation priorities among the remnant ecosystems within an alpine valley. The ecosystems are first assessed by means of landscape ecological indicators, and then ranked by using multicriteria analysis (MCA) techniques. Several conservation scenarios are generated so as to simulate different evaluation perspectives. The scenarios are then compared to highlight the most conflicting sites and to propose a conservation strategy for the area under evaluation. The paper aims at exemplifying and discussing the effectiveness of spatial decision-support techniques in land-use planning for nature conservation.

Analytical and Environmental Chemistry in the Framework of Risk Assessment and Management: The Lagoon of Venice as a Case Study

Prevention of toxic pollutant discharge and remediation of contaminated sediments and soils are topics increasingly addressed by the scientific community and the stakeholders. The research activity carried out on the lagoon of Venice highlights the crucial role played by analytical and environmental chemistry in assessing the environmental behavior of chemicals (i.e. occurrence level, transformation, ultimate fate) and exposure of human and environmental targets to pollutants. The extrapolation from analytical data to decisional steps was accomplished by data treatment (descriptive and multivariate statistics, spatial statistics), environmental modeling (e.g. partitioning bioaccumulation models and linear regression models), environmental risk assessment (ERA), and a GIS-based Decision Support System (DSS). Results obtained by this integrated approach supported analytical and environmental chemistry by improving the selection of priority pollutants, optimizing sampling design, and identifying critical environmental pathways. Both uncertainty minimization and cost saving of the overall decision process could be achieved. Selected results are presented here on the application of the proposed approach to the contaminated sediments of the lagoon of Venice and to the brownfield of the Porto Marghera industrial district. Both well-known persistent pollutants (e.g. polychlorinated dioxins/furans (PCDD/Fs), polychlorinated biphenyls (PCBs), polycyclic aromatic hydrocarbons (PAHs), metals and metalloids, and aromatic surfactants and their metabolites), as well as new classes of pollutants (e.g. endocrine disrupting compounds, EDCs) were investigated. The analytical data indicated that the most persistent and toxic organic and inorganic chemicals were found mainly in bottom sediments (especially those near the Porto Marghera industrial district), while substances such as surfactants and their metabolites and EDCs occurred mainly in water and were redistributed over the whole lagoon. Exposure characterization allowed Environmental Risk Assessment (ERA) to be undertaken, including the estimation of risk for both human and environmental health. The ERA procedure, developed according to a tiered approach, was applied to contaminated soils of the Porto Marghera industrial district. The ecological risk associated with contaminated lagoon sediments for the benthic community and aquatic food web was also assessed, resulting in a significant risk posed especially by mercury, cadmium and PAHs. Finally, a risk-based decision support system (DSS) for the rehabilitation of the Porto Marghera contaminated site was developed, which included environmental risk and remediation technologies.

A GIS-based Decision Support System for Neighbourhood Greening

A prototype decision support tool is described which provides options for the management of existing green spaces and for the establishment of new green space in suburban neighbourhoods. Suggested neighbourhood greening techniques include the naturalization of existing parks and increased foliage along streets and rights of way. The naturalization approach involves less frequent cutting in grassy fields, the introduction of native species, and the cessation of pesticide and herbicide applications. Increased plantings along streets and boulevards would improve the aesthetics of neighbourhoods, and may provide some relief from climatic extremes and urban heat island effects. The creation of new green space in already-built suburban neighbourhoods provides a longer term challenge to neighbourhood planners. Potential strategies include the introduction of small pocket parks and community gardens in vacant lots and school yards. Modelled outcomes from such neighbourhood greening strategies could be used in public meetings both to incorporate attitudes of the impacted community and to demonstrate benefits to a wider community. In particular, strategies should take into account issues of safety and perceived safety that commonly arise with the greater use of naturalization in green space management. The developed prototype decision support tool has been coded as an ArcView GIS extension and provides the opportunity to model and evaluate future scenarios better aligned to principles of sustainable community development. Three applications of this tool are discussed to illustrate some of the benefits of undertaking a range of neighbourhood greening strategies.

GIS-based decision support system for groundwater assessment in large irrigation project areas

In large canal irrigation project areas, integrated management of surface and groundwater resources can improve water use efficiencies and agricultural productivity and also control water logging. Such integrated management requires an estimation of spatial distribution of recharge and ground water flow in the underlying aquifer. Recharge occurs both as percolation losses from fields and seepage losses from the water distribution network. Percolation losses are influenced by weather, soil properties, land use, and canal water and groundwater use. Seepage losses depend on the conditions of flow in the water distribution system. In large irrigation project areas all the factors influencing the recharge of groundwater vary spatially. In this study, a geographical information systems (GIS) is used to map the spatial distribution of recharge which then serves as input to a regional groundwater flow model for simulating the behavior of the underlying aquifer. The basis is that the project area can be divided into a set of basic simulation units (BSUs) that are homogenous with respect to the conditions that influence the recharge processes. A daily field soil water balance model and a simple canal flow model are used to estimate the percolation and seepage losses, respectively. The combination of models and GIS can be used as an integrated decision support system to assess the groundwater resources and derive strategies for integrated management of canal and groundwater resources in the project area.

THE OPERATION OF A GIS‐BASED DECISION SUPPORT SYSTEM FOR AUSTRALIAN LOCUST MANAGEMENT

Abstract The Australian Plague Locust Commission (APLC) is responsible for the monitoring and control of locust populations that pose a threat to agriculture in the inland areas of four Australian States, a total area of 2 million km2. A GIS‐based decision support system (DSS) is used to co‐ordinate the collection, processing, analysis and display of a range of spatial data for the forecasting of locust population development and to assist control operations. The resultant forecasts are used to help locate population aggregations early in a breeding sequence so as to enable effective preventive control. The data collection components of the DSS include wireless direct transfer of locust survey data from the field and daily internet collections of weather data. Locust distribution and age information is collected by APLC officers on regular vehicle surveys using GPS‐connected palmtop computers, and sent directly to a GIS server via high frequency (HF) radio modems. Locust reports from landholders and state extension staff are also incorporated into the system. The current survey data are used to estimate broad distributions, and to seed spatially‐explicit development models that can identify the timing of life stages that can be effectively managed. Information on the distribution of rainfall, temperature and wind‐fields is collected automatically from the internet and integrated with habitat information and locust distributions. Online weather data products from the Bureau of Meterology are also accessed regularly to assist in operational decision making.

Map-Route: a GIS-based decision support system for intra-city vehicle routing with time windows

This paper presents a Decision Support System (DSS) that enables dispatchers–schedulers to approach intra-city vehicle routing problems with time windows interactively, using appropriate computational methods and exploiting a custom knowledge base that contains information about traffic and spatial data. The DSS, named Map-Route, generates routes that satisfy time and vehicle capacity constraints. Its computational engine is based on an effective heuristic method for solving the underlying optimization problem, while its implementation is developed using MapInfo, a popular Geographical Information System (GIS) platform. Map-Route provides very efficient solutions, is particularly user-friendly, and can reach answers for a wide variety of ‘what if’ scenarios with potentially significant cost implications. We have implemented Map-Route in an actual industrial environment and we report on the experience gained from this real-life application.

Potential uses for geographic information system-based planning and decision support technology in intensive food animal production.

Although geographic information systems (GIS) have been used in many disciplines, the available technology in planning and decision support has only recently begun to be used in intensive animal production, in areas such as confined animal feeding operations. GIS-based planning and decision support systems have the potential to enhance many aspects of intensive animal production, such as disease monitoring and prevention, emergency management and nutrient waste disposal. Current uses of GIS in animal production are reviewed. Potential uses are illustrated using the example of the poultry industry on the Delmarva Peninsula, USA.

Metadata as a knowledge management tool: supporting intelligent agent and end user access to spatial data

Many factors have led to explosive growth in the use of geographic information system (GIS) technology to support managerial decision making. Despite their power, utility, and popularity, however, GIS require a significant amount of specialized knowledge for effective use. This paper describes a GIS-based decision support system (DSS) design approach that embeds much of this knowledge in well-structured metadata and presents it to the decision maker through an appropriate interface or software agents, thereby decreasing system learning costs and improving effectiveness. The metadata design from a spatial decision support system (SDSS) is presented along with illustrations showing how the design addresses specific knowledge management (KM) problems. The paper then discusses how the knowledge management design approach can be generalized to other SDSS, to DSS in general, and to data warehouses.

A GIS-based decision support system for brownfield redevelopment

Rapid growth in regions surrounding large metropolitan areas leads to the phenomenon of urban sprawl. In states like Michigan, land is being converted at a rate seven times greater than formerly used (and potentially contaminated) sites are being redeveloped. City governments now see these unused or abandoned areas as important assets in realizing the goal of urban revitalization. New legislation in Michigan provides economic (e.g. tax recapture) and legal (e.g. suspension of retroactive liability) incentives for local governments and prospective developers who are now seeking these brownfields instead of farmland and open space. To evaluate land use options with respect to brownfields inventory, characterization, and potential for redevelopment, both government and private decision-makers need access to information regarding land capability; development incentives; public goals, interests, and preferences; and environmental concerns such as site contamination and environmental quality. This paper discusses a decision support system that provides access to state, regional, and local geospatial databases, several informational and visualization tools, and assumptions useful in providing a better understanding of issues, options, and alternatives in redeveloping brownfields. The resultant decision support system is augmented by a unique geographic information systems (GIS)-based land use modeling application called Smart Places ® as an integrated expert system. The decision support system is being tested in a city- and county-level brownfield identification, screening, and marketing effort in Jackson County, Michigan. This project represents a testbed for decision-makers and policy analysts at all levels of government to establish urban land use policy and development guidelines that may be applicable to related land use issues in a variety of urban and urbanizing settings. While this project was conducted in Michigan, the tools and procedures used are seen as readily adaptable to other locations.

A GIS-based decision support system for analysis of route choice in congested urban road networks

Urban congestion patterns have become ubiquitous and complex. Traditional, “static” approaches are no longer adequate for analyzing network flows and conducting minimum cost routing. This paper reports on a GIS-based decision support tool for modeling dynamic network congestion and conducting minimum cost routing. The system predicts network flows at a detailed level of temporal resolution, capturing dynamic congestion propagation effects. A Route Planner module solves for the combined departure time and minimum cost routing required for a trip to reach its destination by a given deadline. The GIS provides effective decision support through its database management capabilities, graphical user interfaces and cartographic visualization. This supports analyses of “what-if?” scenarios for strategic planning and tactical management subject to unplanned network disturbances.