A Multidisciplinary Decision Support System for Forest Fire Crisis Management

A wildland fire is a serious threat for forest ecosystems in Southern Europe affecting severely and irreversibly regions of significant ecological value as well as human communities. To support decision makers during large-scale forest fire incidents, a multidisciplinary system has been developed that provides rational and quantitative information based on the site-specific circumstances and the possible consequences. The systems architecture consists of several distinct supplementary modules of near real-time satellite monitoring and fire forecast using an integrated framework of satellite Remote Sensing, GIS, and RDBMS technologies equipped with interactive communication capabilities. The system may handle multiple fire ignitions and support decisions regarding dispatching of utilities, equipment, and personnel that would appropriately attack the fire front. The operational system was developed for the region of Penteli Mountain in Attika, Greece, one of the mountain areas in the country most hit by fires. Starting from a real fire incident in August 2000, a scenario is presented to illustrate the effectiveness of the proposed approach.     

决策支持系统应用于城市环境管理

南宁市环境决策支持系统集环境管理办公自动化、环境管理系统(MIS)、环境地理信息系统(GIS)、多媒体环境管理信息应用和环境管理信息辅助决策等多功能一体集成的综合性环境信息系统，为南宁市环境管理、经济发展决策提供环境信息支撑与服务。     

Decision Support for Road System Analysis and Modification on the Tahoe National Forest

The United States Forest Service is required to analyze road systems on each of the national forests for potential environmental impacts. We have developed a novel and inexpensive way to do this using the Ecosystem Management Decision Support program (EMDS). We used EMDS to integrate a user-developed fuzzy logic knowledge base with a grid-based geographic information system to evaluate the degree of truth for assertions about a roads environmental impact. Using spatial data for natural and human processes in the Tahoc National Forest (TNF, California, USA), we evaluated the assertion the road has a high potential for impacting the environment. We found a high level of agreement between the products of this evaluation and ground observations of a TNF transportation engineer, as well as occurrences of road failures. We used the modeled potential environmental impact to negatively weight roads for a least-cost path network analysis to 1573 points of interest in the forest. The network analysis showed that out of 8233 km of road analyzed in the forest, 3483 km (42%) must be kept in a modified road network to ensure access to these points. We found that the modified network had improved patch characteristics, such as significantly fewer cherry stem roads intruding into patches, an improved area-weighted mean shape index, and larger mean patch sizes, as compared to the original network. This analysis system could be used by any public agency to analyze infrastructure for environmental or other risk and included in other mandated analyses such as risks to watersheds.     

Degradation Model: A Quantitative EIA Instrument,Acting as a Decision Support System (DSS) for Environmental Management

Environmental assessment of alternative development plans, programs, and policies may bring conflict among decision-makers, particularly when some quantitative measures for decision-making are needed and where cumulative impacts are neglected. Environmental impact assessment (EIA) and environmental economics theories, despite their usefulness, are not capable of addressing those issues and problems alone. In recent years, the decision support system (DSS) has provided some solutions, but mathematical analysis of the system to show the internal structure of the problem is not always possible. To addres the above shortcomings and ongoing problems of decision-making in Iran, a degradation model (DM) was introduced as an instrument of EIA, to act as a DSS for managers. The model is a compromise between knowledge-based decision support systems, detailed models, digested information models, and the basic theorem of environmental economics. In the present study (1996–2000), the model was applied in three provinces of Iran, representing three of four biogeographical regions of Iran. The study area was divided into a set of grids (100 km²). The degradation coefficient (H) was computed for all grids (1333), representing the degree of degradation in the grid. It is obvious that the higher the coefficient the more area is degraded and less prone to further development, and vice versa. In order to provide decision-makers with a set of quantitative measures to observe impacted areas (critical and noncritical) for resource allocation and further development, the degradation coefficients of all grids were classified into categories and criteria, using a fuzzy set theoretic approach. Accordingly, only 24% of study areas are prone to further development. The degradation model as a knowledge-based decision support system has its strengths and weaknesses, but it has solved managers' ongoing problems in Iran and it could be used elsewhere.     

Identifying Opportunities for Decision Support Systems in Support of Regional Resource Use Planning: An Approach Through Soft Systems Methodology

/ Regional resource use planning relies on key regional stakeholder groups using and having equitable access to appropriate social, economic, and environmental information and assessment tools. Decision support systems (DSS) can improve stakeholder access to such information and analysis tools. Regional resource use planning, however, is a complex process involving multiple issues, multiple assessment criteria, multiple stakeholders, and multiple values. There is a need for an approach to DSS development that can assist in understanding and modeling complex problem situations in regional resource use so that areas where DSSs could provide effective support can be identified, and the user requirements can be well established. This paper presents an approach based on the soft systems methodology for identifying DSS opportunities for regional resource use planning, taking the Central Highlands Region of Queensland, Australia, as a case study.     

Land Resource Sustainability for Urban Development: Spatial Decision Support System Prototype

Land resource sustainability for urban development characterizes the problem of decision-making with multiplicity and uncertainty. A decision support system prototype aids in the assessment of incremental land development plan proposals put forth within the long-term community priority of a sustainable growth. Facilitating this assessment is the analytic hierarchy process (AHP), a multicriteria evaluation and decision support system. The decision support system incorporates multiple sustainability criteria, weighted strategically responsive to local public policy priorities and community–specific situations and values, while gauging and directing desirable future courses of development. Furthermore, the decision support system uses a GIS, which facilitates an assessment of urban form with multiple indicators of sustainability as spatial criteria thematically. The resultant land-use sustainability scores indicate, on the ratio-scale of AHP, whether or not a desirable urban form is likely in the long run, and if so, to what degree. The two alternative modes of synthesis in AHP—ideal and distributive—provide assessments of a land development plan incrementally (short-term) and city-wide pattern comprehensively (long-term), respectively. Thus, the spatial decision support system facilitates proactive and collective public policy determination of land resource for future sustainable urban development.     

Development of a Decision Support System for Assessing Farm Animal Welfare in Relation to Husbandry Systems: Strategy and Prototype

Due to increasing empiricalinformation on farm animal welfare since the1960s, the prospects for sound decisionmakingconcerning welfare have improved. This paperdescribes a strategy to develop adecision-making aid, a decision support system,for assessment of farm-animal welfare based onavailable scientific knowledge. Such a decisionsupport system allows many factors to be takeninto account. It is to be developed accordingto the Evolutionary Prototyping Method, inwhich an initial prototype is improved inreiterative updating cycles. This initialprototype has been constructed. It useshierarchical representations to analysescientific statements and statements describingthe housing system. Welfare is assessed fromwhat is known about the biological needs of theanimals, using a welfare model in the form of atree that contains these needs as welfarecomponents. Each state of need is assessedusing welfare relevant attributes of thehousing system and weighting factors.Attributes are measurable properties of thehousing system. Weighting factors are assignedaccording to heuristic rules based on theprinciple of weighting all components(attributes and needs) equally, unless thereare strong reasons to do otherwise. Preliminarytests of the prototype indicate that it may bepossible to perform assessment of farm-animalwelfare in an explicit way and based onempirical findings. The procedure needs to berefined, but its prospects are promising.     

构建与设计化学矿业可持续发展决策支持系统

本文讨论了化学矿业可持续发展的内涵和实现可持续发展战略的最佳技术手段之一,即建立化学矿业可持续发展空间决策支持系统的重要性,提出了化学矿业可持续发展决策支持系统的构建理论依据和方法,探讨了化学矿业可持续发展空间决策支持系统总体设计、系统分析的数学模型以及系统的方法库和模型库的设计。     

A Hierarchical Fuzzy Decision Support System for the Environmental Rehabilitation of Lake Koronia,Greece

This article presents the design of a fuzzy decision support system (DSS) for the assessment of alternative strategies proposed for the restoration of Lake Koronia, Greece. Fuzzy estimates for the critical characteristics of the possible strategies, such as feasibility, environmental impact, implementation time, and costs are evaluated and supplied to the fuzzy DSS. Different weighting factors are assigned to the critical characteristics and the proposed strategies are ordered with respect to the system responses. The best strategies are selected and their expected impact on the ecosystem is evaluated with the aid of a fuzzy model of the lake. Sensitivity analysis and simulation results have shown that the proposed fuzzy DSS can serve as a valuable tool for the selection and evaluation of appropriate management actions. Note: This version was published online in June 2005 with the cover date of August 2004.     

Linking Multiple Accounts with GIS as Decision Support System to Resolve Forestry/Wildlife Conflicts

With shrinking forest resources and increasing demands for timber, conflicts between forestry and wildlife become more contentious and more frequent. New decision support methods are needed to address complex multiple land use conflicts. Multiple accounts methods linked with GIS and production models enable us to address trade-offs between timber and non-timber values, thus facilitating the evaluation and comparison of different management scenarios in a rapid and spatially referenced manner. The approach is documented in a case study in the trans-boundary zone between two national parks in British Columbia, where caribou/logging conflicts are widespread.     

An erosion-based land classification system for military installations

The universal soil loss equation (USLE) has been integrated with a geographic information system known as the geographical resources analysis support system (GRASS) to create a land classification system for use by military trainers and land managers to minimize the environmental impacts of military training activities. The USLE provides an estimate of current average annual sheet and rill erosion based upon factors representing climate, soil erodibility, topography, cover, and conservation support practices. The erosion estimate is compared to erosion tolerance values to produce an expression of the current erosion status. An index of inherent site erodibility is also achieved through manipulation of the USLE. Based on published soil surveys, satellite imagery, and ground-truth vegetation transects, data layers are created within GRASS for each of the component factors of the USLE. Appropriate mathematical operations are performed with the data layers, and color-coded maps are produced that represent the erosion status and erodibility index for each 50-m × 50-m area of soil surface. These maps aid military trainers and land managers in scheduling appropriate kinds and intensities of military training activities.     

A Web‐Based Decision Support System for Assessing Regional Water‐Quality Conditions and Management Actions1

Booth, Nathaniel L., Eric J. Everman, I‐Lin Kuo, Lori Sprague, and Lorraine Murphy, 2011. A Web‐Based Decision Support System for Assessing Regional Water‐Quality Conditions and Management Actions. Journal of the American Water Resources Association (JAWRA) 47(5):1136‐1150. DOI: 10.1111/j.1752‐1688.2011.00573.x Abstract: The U.S. Geological Survey National Water Quality Assessment Program has completed a number of water‐quality prediction models for nitrogen and phosphorus for the conterminous United States as well as for regional areas of the nation. In addition to estimating water‐quality conditions at unmonitored streams, the calibrated SPAtially Referenced Regressions On Watershed attributes (SPARROW) models can be used to produce estimates of yield, flow‐weighted concentration, or load of constituents in water under various land‐use condition, change, or resource management scenarios. A web‐based decision support infrastructure has been developed to provide access to SPARROW simulation results on stream water‐quality conditions and to offer sophisticated scenario testing capabilities for research and water‐quality planning via a graphical user interface with familiar controls. The SPARROW decision support system (DSS) is delivered through a web browser over an Internet connection, making it widely accessible to the public in a format that allows users to easily display water‐quality conditions and to describe, test, and share modeled scenarios of future conditions. SPARROW models currently supported by the DSS are based on the modified digital versions of the 1:500,000‐scale River Reach File (RF1) and 1:100,000‐scale National Hydrography Dataset (medium‐resolution, NHDPlus) stream networks.