Site search and multicriteria evaluation

Geographic information systems (GIS) are potentially powerful collections of tools which planners can use in the manipulation and analysis of spatial information. One traditional area of interest in this context is site search. Here, the functionality of GIS is, however, limited to certain deterministic analyses which serve merely as a computerised automation of the manual sieve mapping approach. The integration of multicriteria evaluation (MCE) techniques with GIS, is forwarded as a means of providing the user with the means to evaluate sites identified by sieve mapping techniques on the basis of multiple and conflicting criteria and objectives. An example application based on the search for suitable radioactive waste disposal sites in Britain using the Arc/Info GIS is included. The potential use of a combined GIS/MCE approach in the development of spatial decision support systems (SDSS) is considered.     

Fuzzy multiple-criteria decision-making approach for industrial green engineering

This paper describes a fuzzy hierarchical analytic approach to determine the weighting of subjective judgments. In addition, it presents a nonadditive fuzzy integral technique to evaluate a green engineering industry case as a fuzzy multicriteria decision-making (FMCDM) problem. When the investment strategies are evaluated from various aspects, such as economic effectiveness, technical feasibility, and environmental regulation, it can be regarded as an FMCDM problem. Since stakeholders cannot clearly estimate each considered criterion in terms of numerical values for the anticipated alternatives/strategies, fuzziness is considered to be applicable. Consequently, this paper uses triangular fuzzy numbers to establish weights and anticipated achievement values. By ranking fuzzy weights and fuzzy synthetic utility values, we can determine the relative importance of criteria and decide the best strategies. This paper applies what is called a λ fuzzy measure and nonadditive fuzzy integral technique to evaluate the synthetic performance of green engineering strategies for aquatic products processors in Taiwan. In addition, we demonstrate that the nonadditive fuzzy integral is an effective evaluation and appears to be appropriate, especially when the criteria are not independent.     

Landfill site selection using spatial information technologies and AHP: A case study in Beijing,China

Site selection is an important and necessary issue for waste management in fast-growing regions. Because of the complexity of waste management systems, the selection of the appropriate solid waste landfill site requires consideration of multiple alternative solutions and evaluation criteria. Based on actual conditions of the study area, we considered economic factors, calculated criteria weights using the analytical hierarchy process (AHP), and built a hierarchy model for solving the solid waste landfill site-selection problem in Beijing, China. A geographic information system (GIS) was used to manipulate and present spatial data. All maps are graded from 1 (lowest suitability) to 5 (highest suitability) using spatial information technologies. The candidate sites were determined by aggregation based on the criteria weights. The candidate sites are divided by ‘best’, ‘good’ and ‘unsuitable’ landfill areas. Best landfill areas represent optimal sites; good landfill areas can be used as back-up candidate sites. Our work offers a siting methodology and provides essential support for decision-makers in the assessment of waste management problems in Beijing and other rapidly developing cities in developing countries.     

GIS and the Analytic Hierarchy Process for Regional Landfill Site Selection in Transitional Countries: A Case Study From Serbia

The Serbian National Waste Management Strategy for the Period 2010–2019, harmonized with the European Union Directives, mandates new and very strict requirements for landfill sites. To enable analysis of a number of required qualitative and quantitative factors for landfill site selection, the traditional method of site selection must be replaced with a new approach. The combination of GIS and the Analytic Hierarchy Process (AHP) was selected to solve this complex problem. The Srem region in northern Serbia, being one of the most environmentally sensitive areas, was chosen as a case study. Seventeen factors selected as criteria/sub-criteria were recognized as most important, divided into geo-natural, environmental, social and techno-economic factors, and were evaluated by experts from different fields using an AHP extension in Arc GIS. Weighted spatial layers were combined into a landfill suitability map which was then overlapped with four restriction maps, resulting in a final suitability map. According to the results, 82.65% of the territory of Srem is unsuitable for regional landfill siting. The most suitable areas cover 9.14%, suitable areas 5.24%, while areas with low and very low suitability cover 2.21 and 0.76% of the territory, respectively. Based on these findings, five sites close to two large urban agglomerations were suggested as possible locations for a regional landfill site in Srem. However, the final decision will require further field investigation, a public acceptance survey, and consideration of ownership status and price of the land.     

Hospital site selection using fuzzy AHP and its derivatives

Environmental managers are commonly faced with sophisticated decisions, such as choosing the location of a new facility subject to multiple conflicting criteria. This paper considers the specific problem of creating a well-distributed network of hospitals that delivers its services to the target population with minimal time, pollution and cost. We develop a Multi-Criteria Decision Analysis process that combines Geographical Information System (GIS) analysis with the Fuzzy Analytical Hierarchy Process (FAHP), and use this process to determine the optimum site for a new hospital in the Tehran urban area. The GIS was used to calculate and classify governing criteria, while FAHP was used to evaluate the decision factors and their impacts on alternative sites. Three methods were used to estimate the total weights and priorities of the candidate sites: fuzzy extent analysis, center-of-area defuzzification, and the α-cut method. The three methods yield identical priorities for the five alternatives considered. Fuzzy extent analysis provides less discriminating power, but is simpler to implement and compute than the other two methods. The α-cut method is more complicated, but integrates the uncertainty and overall attitude of the decision-maker. The usefulness of the new hospital site is evaluated by computing an accessibility index for each pixel in the GIS, defined as the ratio of population density to travel time. With the addition of a new hospital at the optimum site, this index improved over about 6.5 percent of the geographical area.     

Decision making under uncertainty using PEES–fuzzy AHP–fuzzy TOPSIS methodology for landfill location selection

The location selection for landfill municipal solid waste is an important issue in waste management. Selection of the optimal location requires consideration of multiple alternative solutions and evaluation factors because of system complexity. Further, ranking of the alternative locations and selection of the most optimal and efficient locations for landfill waste are an important multi-criteria decision-making problem. In this study, the candidate locations for landfill are determined based on Political, Economical, Environmental and Social factors are assessed through decision-makers’ opinion and by the methodology that incorporates fuzzy analytic hierarchy process (fuzzy AHP) and fuzzy technique for order preference by similarity to ideal solution (fuzzy TOPSIS). Specifically, the fuzzy AHP technique is applied to determine the weights of selected criteria impacting the location selection process, and the fuzzy AHP is adapted to model the linguistic vagueness and ambiguity, which can also be expressed as triangular fuzzy numbers. Furthermore, fuzzy TOPSIS technique is employed to rank the alternative locations. The applicability of this methodology is demonstrated by a case study of landfill waste location selection in the region of Casablanca, Morocco, and the results are compared with other techniques. Finally, to complete the treatment, a sensitivity analysis is performed to examine the impact of the preferences given by decision-makers to choose the best location.     

The optimal dam site selection using a group decision-making method through fuzzy TOPSIS model

The complex and controversial task of selecting a dam site in a river basin can be successfully achieved using science-informed multi-criteria decision-making (MCDM) techniques. In this paper, we describe the application of the group fuzzy TOPSIS model for optimal ranking of the case study of Kandoleh dam sites in Kermanshah province, Iran, involving 18 input criteria. In this study, decision-making committee was made up of 20 involved decision makers. The comments of four non-biased, external experts in dam site selection were also used. The triangular fuzzy numbers were used to apply experts’ opinions on the selection criteria. In total, four alternative sites were assessed based on the technical, economic, social and environmental considerations and the data were analyzed using fuzzy TOPSIS MCDM model. Ranking results were compared with multi-criteria decision-making models, including the ELimination and Choice Expressing the REality and simple additive weighting. This logical, open and transparent framework provides a science-informed decision-making approach for complex problems such as optimal dam site selection. Finally, using sensitivity analysis, local studies and group discussions, we demonstrated the multiple benefits of the proposed novel method for a science-informed, open and transparent method for optimal ranking of the dam site candidates.     

Multi-criteria risk management with the use of <Emphasis Type="Italic">DecernsMCDA</Emphasis>: methods and case studies

Emerging challenges of risk management, environmental protection, and land-use planning requires integration of stakeholder values and expert judgment. The process of decision making in situation of high uncertainty can be assisted through the use of decision support systems (DSSs). Such DSSs are often based on tools for spatial data representation (GIS) and environmental models that are integrated using multi-criteria decision analysis (MCDA). This paper presents DecernsMCDA implementing all major types of multi-criteria methods and tools (AHP, MAUT, Outranking) under the same user interface. In addition to providing ability for testing model uncertainty associated with selection of specific MCDA algorithms, DecernsMCDA implements new algorithms for parameter uncertainty analysis based on probabilistic approaches and fuzzy sets. The paper illustrates application of DecernsMCDA for selecting remedial alternative at radiologically contaminated sites.     

SELECTION OF WASTE DISPOSAL SITES USING GIS1

ABSTRACT: Geographic Information Systems (GIS) technology is used to identify candidate sites for a solid waste disposal facility in the Gölbasi region of Turkey that has suffered from the negative impact of a current but poorly-located open-dump site on the environment. The municipality of Gölbasi has noticed its deleterious effect on the environment, and has thus decided to dismiss this open-dump site and search for new landfill sites. In this study, the procedure followed under a GIS framework rejects the unacceptable sites considering environmental factors exclusively, other than economic and political issues, contained in the form of multiple layers of attribute information to select the candidate sites for landfilling wastes through an overlay analysis performed by GIS software, ARC/INFO V 7.1. For the spatial data requirements of GIS, a number of thematic map layers (ground water, wetlands and swamp areas, surface water, roads, topographic contours, ecological features, settlements, erosion susceptibility zones, and soil type) are prepared in digital form. In this application, GIS is considered as a screening tool in a site selection process to narrow the number of candidate sites, subsequently leading to one or more sites for detailed investigation. Preliminary ranking for a group of potential sites is done on the basis of simple calculations coupled with on-site field studies.     

An approach based on spatial multicriteria analysis to map the nature conservation value of agricultural land

Knowledge of the nature conservation value of agricultural land provides a useful input to land-use planning. However, the scarcity of suitable data causes this component to rarely play a role. The paper proposes a methodology based on commonly available data to assess the nature conservation value of agricultural landscapes, and to generate cartographic results to be used as decision variables in planning. The approach relies on landscape ecological indicators and on the application of multicriteria analysis in a Geographical Information System (GIS) context. Four criteria were selected: the agricultural landscape type, the cover of vegetation remnants and marginal features, the length of forest-agriculture ecotones, and the proximity to nature reserves. These criteria were assessed directly or by means of specific indicators, generating maps that were subsequently aggregated through spatial multicriteria analysis. The approach was tested in an alpine area located in Trentino (northern Italy).     

基于层次分析法的秦皇岛市垃圾填埋场选址评价

城市垃圾填埋场场址的选择，受到当地经济、交通、气候条件，自然地理条件，环境保护条件，水文地质工程地质条件等诸多因素影响，是一项十分复杂的工程。本文总结了秦皇岛市现有垃圾填埋场的基本情况、存在问题及其产生原因。鉴于层次分析法在多目标决策分析方面的成效，将其运用到秦皇岛市垃圾填埋场选址评价中，对研究区进行适宜性分区，依次划分为最佳场地区、适宜场地区、较适宜场地区、不适宜场地区。     

A SPATIAL DECISION SUPPORT SYSTEM FOR ASSESSING AGRICULTURAL NONPOINT SOURCE POLLUTION1

ABSTRACT: A spatial decision support system (SDSS) was developed to assess agricultural nonpoint source (NPS) pollution using an NPS pollution model and geographic information systems (GIS). With minimal user interaction, the SDSS assists with extracting the input parameters for a distributed parameter NPS pollution model from user-supplied GIS base layers. Thus, significant amounts of time, labor, and expertise can be saved. Further, the SDSS assists with visualizing and analyzing the output of the NPS pollution simulations. Capabilities of the visualization component include displays of sediment, nutrient, and runoff movement from a watershed. The input and output interface techniques/algorithms used to develop the SDSS, along with an example application of the SDSS, are described.     

An Analytic Network Process approach for siting a municipal solid waste plant in the Metropolitan Area of Valencia (Spain)

In this paper the Analytic Network Process (ANP) is applied to select the best location for the construction of a municipal solid waste (MSW) plant in the Metropolitan area of Valencia (Spain). Selection of the appropriate MSW facility location can be viewed as a complex multicriteria decision-making problem that requires an extensive evaluation process of the potential MSW plant locations and other factors as diverse as economic, technical, legal, social or environmental issues. The decision-making process includes the identification of six candidate MSW plant sites and 21 criteria grouped into clusters for the construction of a network. Two technicians of the Metropolitan Waste Disposal Agency acted as decision makers (DMs).The influences between the elements of the network were identified and analyzed using the ANP multicriteria decision method. Two different ANP models were used: one hierarchy model (that considers AHP as a particular case of ANP) and another network-based model. The results obtained in each model were compared and analyzed. The strengths and weaknesses of ANP as a multicriteria decision analysis tool are also described in the paper. The main findings of this research have proved that ANP is a useful tool to help technicians to make their decision process traceable and reliable. Moreover, this approach helps DMs undertake a sound reflection of the siting problem.     

INFORMATION TECHNOLOGY IN WATERSHED MANAGEMENT DECISION MAKING1

ABSTRACT: Watershed management decision making is a complex process. Cooperation and communication among federal, state, and local stakeholders is required while balancing biophysical and socioeconomic concerns. The public is taking part in environmental decisions, and the need for technology transfer from public agencies to stakeholders is increasing. Information technology has had a profound influence on watershed management over the past decade. Advances in data acquisition through remote sensing, data utilization through geographic information systems (GIS), and data sharing through the Internet have provided watershed managers access to more information for management decisions. In the future, applications incorporating hydrologic simulation models, GIS, and decision support systems will be deployed through the Internet. In addition to challenges in making complex modeling technology available to diverse audiences, new information technology issues, such as interoperability, Internet access, and security, are introduced when GIS, simulation models, and decision support systems are integrated in an Internet environment. This paper presents a review of current use of information technology in watershed management decision making and a discussion of issues created when developing Internet based, integrated watershed management decision support systems. A prototype spatial decision support system (SDSS) for rangeland watershed management was developed using web services, which are components that communicate using text based messages, thus eliminating proprietary protocols. This new framework provides an extensible, accessible, and interoperable approach for SDSS.     

DECISION SUPPORT FOR ALLOCATION OF WATERSHED POLLUTION LOAD USING GREY FUZZY MULTIOBJECTIVE PROGRAMMING1

ABSTRACT: This paper uses the grey fuzzy multiobjective programming to aid in decision making for the allocation of waste load in a river system under versatile uncertainties and risks. It differs from previous studies by considering a multicriteria objective function with combined grey and fuzzy messages under a cost benefit analysis framework. Such analysis technically integrates the prior information of water quality models, water quality standards, wastewater treatment costs, and potential benefits gained via in‐stream water quality improvement. While fuzzy sets are characterized based on semantic and cognitive vagueness in decision making, grey numbers can delineate measurement errors in data collection. By employing three distinct set theoretic fuzzy operators, the synergy of grey and fuzzy implications may smoothly characterize the prescribed management complexity. With the aid of genetic algorithm in the solution procedure, the modeling outputs contribute to the development of an effective waste load allocation and reduction scheme for tributaries in this subwatershed located in the lower Tseng‐Wen River Basin, South Taiwan. Research findings indicate that the inclusion of three fuzzy set theoretic operators in decision analysis may delineate different tradeoffs in decision making due to varying changes, transformations, and movements of waste load in association with land use pattern within the watershed.     

A distance-based uncertainty analysis approach to multi-criteria decision analysis for water resource decision making

The choice among alternative water supply sources is generally based on the fundamental objective of maximising the ratio of benefits to costs. There is, however, a need to consider sustainability, the environment and social implications in regional water resources planning, in addition to economics. In order to achieve this, multi-criteria decision analysis (MCDA) techniques can be used. Various sources of uncertainty exist in the application of MCDA methods, including the selection of the MCDA method, elicitation of criteria weights and assignment of criteria performance values. The focus of this paper is on the uncertainty in the criteria weights. Sensitivity analysis can be used to analyse the effects of uncertainties associated with the criteria weights. Two existing sensitivity methods are described in this paper and a new distance-based approach is proposed which overcomes limitations of these methods. The benefits of the proposed approach are the concurrent alteration of the criteria weights, the applicability of the method to a range of MCDA techniques and the identification of the most critical criteria weights. The existing and proposed methods are applied to three case studies and the results indicate that simultaneous consideration of the uncertainty in the criteria weights should be an integral part of the decision making process.     

Development and Integration of a Groundwater Simulation Model to an Open Geographic Information System

This study presents the implementation of a spatial decision support system (SDSS) named ARENA. The program has been developed based on object‐oriented concepts using the Java programming language. The SDSS is made up of a groundwater simulation tool coupled to an open geographic information system (open GIS). Both the open GIS and groundwater simulation package share common spatial and nonspatial entities during the modeling process. A dedicated interface provides direct access to the GIS data without the need of external files. The finite element method is used to solve the partial differential equation that governs groundwater flow. The system implementation is presented by depicting the main classes and coupling procedures. A study case demonstrates the applicability of the simulation tool.     

Spatially explicit sensitivity and uncertainty analysis for multicriteria-based vulnerability assessment

This research analyses the application of spatially explicit sensitivity and uncertainty analysis for GIS (Geographic Information System) multicriteria decision analysis (MCDA) within a multi-dimensional vulnerability assessment regarding flooding in the Salzach river catchment in Austria. The research methodology is based on a spatially explicit sensitivity and uncertainty analysis of GIS-CDA for an assessment of the social, economic, and environmental dimensions of vulnerability. The main objective of this research is to demonstrate how a unified approach of uncertainty and sensitivity analysis can be applied to minimise the associated uncertainty within each dimension of the vulnerability assessment. The methodology proposed for achieving this objective is composed of four main steps. The first step is computing criteria weights using the analytic hierarchy process (AHP). In the second step, Monte Carlo simulation is applied to calculate the uncertainties associated with AHP weights. In the third step, the global sensitivity analysis (GSA) is employed in the form of a model-independent method of output variance decomposition, in which the variability of the different vulnerability assessments is apportioned to every criterion weight, generating one first-order (S) and one total effect (ST) sensitivity index map per criterion weight. Finally, in the fourth step, an ordered weighted averaging method is applied to model the final vulnerability maps. The results of this research demonstrate the robustness of spatially explicit GSA for minimising the uncertainty associated with GIS-MCDA models. Based on these results, we conclude that applying the variance-based GSA enables assessment of the importance of each input factor for the results of the GIS-MCDA method, both spatially and statistically, thus allowing us to introduce and recommend GIS-based GSA as a useful methodology for minimising the uncertainty of GIS-MCDA.     

Rainwater harvesting planning using geospatial techniques and multicriteria decision analysis

Growing water scarcity and global climate change call for more efficient alternatives of water conservation; rainwater harvesting (RWH) is the most promising alternative among others. However, the assessment of RWH potential and the selection of suitable sites for RWH structures are very challenging for the water managers, especially on larger scales. This study addresses this challenge by presenting a fairly robust methodology for evaluating RWH potential and identifying sites/zones for different RWH structures using geospatial and multicriteria decision analysis (MCDA) techniques. The proposed methodology is demonstrated using a case study. The remote sensing data and conventional field data were used to prepare desired thematic layers using ArcGIS© software. Distributed Curve Number method was used to calculate event-based runoffs, based on which annual runoff potential and runoff coefficient maps were generated in the GIS (geographic information system) environment. Thematic layers such as slope, drainage density, and runoff coefficient and their features were assigned suitable weights and then they were integrated in a GIS to generate a RWH potential map of the study area. Zones suitable for different RWH structures were also identified, together with suitable sites for constructing recharge structures (check dams and percolation tanks along the streams). It was found that the study area can be classified into three RWH potential zones: (a) ‘good’ (241 km²), (b) ‘moderate’ (476 km²), and (c) ‘poor’ (287 km²). About 3% of the study area (30 km²) is suitable for constructing farm ponds, while percolation tanks (on the ground) can be constructed in about 2.7% of the area (27 km²). Of the 83 sites identified for the recharge structures, 32 recharge sites are specially suited to the inhabitants because of their proximity. It is concluded that the integrated geospatial and MCDA techniques offer a useful and powerful tool for the planning of rainwater harvesting at a basin or sub-basin scale.     

Fuzzy assessment of land suitability for scientific research reserves

Evaluating the characteristics of a set of sites as potential scientific research reserves is an example of land suitability assessment. Suitability in this case is based upon multiple criteria, many of which can be linguistically imprecise and often incompatible. Fuzzy logic is a useful method for characterizing imprecise suitability criteria and for combining criteria into an overall suitability rating. The Ecosystem Management Decision Support software combined a fuzzy logic knowledge base we developed to represent the assessment problem with a GIS database providing site-specific data for the assessment. Assessment of sites as a potential natural reserve for the new University of California campus at Merced demonstrates the benefits of fuzzy suitability assessment. The study was conducted in three stages of successively smaller assessment regions with increasingly fine spatial resolution and specificity of criteria. Several sites were identified that best satisfy the suitability criteria for a reserve to represent vernal pool habitat.