Multicriteria Spatial Decision Support System Research Articles

An Online Multicriteria—Spatial Decision Support System for Public Services Planning

Dynamic processes in society and demographics require a rapid response and adaptation of the existing public service infrastructure. Responsible planners must be able to analyse the situation, identify gaps in provision and derive decisions. The paper presents a web application that supports finding answers to various questions and planning decisions in the context of public service infrastructures (e.g., schools, pharmacies, supermarkets). Due to the high complexity, the combination of multi-criteria decision analysis and geographical information systems, especially in the web context, is still rarely implemented. With this spatial decision support system, we are pursuing an approach that makes multi-criteria analyses with spatially explicit methods available to the planning domain. By using this application, the user can select and adjust input parameters independently and thus strongly influence the analysis process and results—without a deep knowledge of decision-making methods or software skills. With such a centrally provided online multi-criteria spatial decision support system, the transparency and the quality of the analysis increase, while the workload for the planners is reduced, since they no longer have to spend time on preliminary data search and integration or on building complex methods and models themselves.

Showcasing New Tourism Destination by Using Gis: a Study of Sikkim

Purpose: The main purpose of this research is to find out new tourist destinations and suggest developmental strategies through scientific ways for solving overtourism-related problems. Theoretical framework: In this research paper, the researchers emphasized finding new tourist spots and analyzing their potential both in touristic and infrastructural value was assessed by the researcher with the help of a most modern tool like Geographic Information System. The researchers have explained a scientific process of exploring new tourist destinations or tourist spots by using GIS and have shown how to develop proper infrastructure around those spots. Design/methodology/approach: A “Multicriteria Spatial Decision Support System modeling” was used to find out and validate the existing and new tourist spots. In the pair-wise comparison method, a criterion versus criteria was created to compare each pair of criteria and assign relative ratings using the scale of pair-wise comparison. In this research, the Simple Additive Weighting (SAW) method is used because it gives the “most acceptable results for majority of single-dimensional problems”. The researcher has created this map to support the ‘Destination Fetching Model’, and it can also be used for promoting sustainable tourism in the area. If the entire land cover is visible to the planners with an aerial view, they can plan for tourism infrastructure and superstructures from anywhere. GIS-based layer data has created an "all covered" aerial map with the help of advanced GIS technology, which not helped the planners to understand the current land condition, but also showed the open area which can be utilized for new tourism set-up. Manmade and natural resources are also classified through this LULC model. Findings: These new tourist spots will help planners and stakeholders to distribute excessive crowds to comparatively new destinations. It is observed that most of the Indian tourism destinations suffer from “over Tourism” in peak season. This research will help spread the flow of tourists to the nearest newly added destinations. Research, Practical & Social implications: Scientific tourism planning through GIS will also help tourism service providers and planners to add infrastructure to the new destinations, and would also help local people to generate income through tourism. Originality/value: This research will solve the “over tourism” problem of any destination or state, and help generate more visitor’s day at the destination which is proportionate to extra revenue generation for the local, regional and national tourism stakeholders.

Modeling wetland restoration scenarios in Gavkhooni International Wetland

One of the challenges for managers is to ensure the long‐term sustainability of wetlands by protecting their ecological values against natural and human pressures. This study has evaluated the past vulnerability status of Gavkhooni International Wetland, Isfahan, Iran, using a combination of GIS and multicriteria spatial decision support systems (MC‐SDSS) processes, to propose restoration scenarios. Three scenarios were developed from criteria established using field studies and expert opinion: (1) wetland restoration to preserve existing water bodies, (2) determination of susceptible regions as habitat replacement for aquatic communities, and (3) a combination of the two previous scenarios. Finally, a map was developed classifying the regions into five categories by area of priority. The northern regions of the wetland were prioritized based on the results of the first and the second scenarios. The third scenario provided the highest opportunity to obtain an optimistic state, that is, normal conditions, for the wetland marginal regions, especially in the central region (between the east and west). In a pessimistic state and optimistic state of the third scenario, almost all parts of the center to the south of the wetland show the lowest priority restoration scenarios. According to the different scenarios, the central regions of the wetland are less affected by agricultural activities and human settlements. In general, the results show that the Gavkhooni Wetland is unstable based on functional, environmental, social and economic conditions. According to the criteria and the MC‐SDSS model, the government can adopt and implement the necessary policies and programs to improve the condition of the wetland.

From Traditional to Electrified Urban Road Networks: The Integration of Fuzzy Analytic Hierarchy Process and GIS as a Tool to Define a Feasibility Index—An Italian Case Study

To achieve sustainable development in the road sector, the use of Electric Vehicles (EVs) appears as a positive response to transport emissions. Among the available technologies, dynamic charging seems to overcome the main weakness points of EVs, even if it requires that traditional roads (t-roads) be equipped with a system providing electricity for EVs. Thus, so-called electrified roads (e-roads) must be implemented into the urban road networks. Since it is not possible to electrify all roads simultaneously, and also to consider the demand needs of citizens, a selection criterion is essential. This research describes and develops a simple, self-explanatory, repeatable, and adaptable selection criterion aimed at helping city managers in prioritizing the roads of an urban network to be upgraded from t-road to e-road status. This method belongs to the so-called Multicriteria Spatial Decision Support Systems (MC-SDSS)—processes useful for solving spatial problems through the integration of multicriteria analysis (Fuzzy Analytic Hierarchy Process, F-AHP) with a geo-referenced data management and analysis tool (GIS). The developed algorithm is based on several criteria related to the infrastructure/transport, social and environmental areas. The result of the implemented method is a Feasibility Index (FI), able to prioritize the roads most eligible to be upgraded as e-roads, as also verified by its application on the urban area of Milan (Italy).

A Participatory and Spatial Multicriteria Decision Approach to Prioritize the Allocation of Ecosystem Services to Management Units

Forest management planning can be challenging when allocating multiple ecosystem services (ESs) to management units (MUs), given the potentially conflicting management priorities of actors. We developed a methodology to spatially allocate ESs to MUs, according to the objectives of four interest groups—civil society, forest owners, market agents, and public administration. We applied a Group Multicriteria Spatial Decision Support System approach, combining (a) Multicriteria Decision Analysis to weight the decision models; (b) a focus group and a multicriteria Pareto frontier method to negotiate a consensual solution for seven ESs; and (c) the Ecosystem Management Decision Support (EMDS) system to prioritize the allocation of ESs to MUs. We report findings from an application to a joint collaborative management area (ZIF of Vale do Sousa) in northwestern Portugal. The forest owners selected wood production as the first ES allocation priority, with lower priorities for other ESs. In opposition, the civil society assigned the highest allocation priorities to biodiversity, cork, and carbon stock, with the lowest priority being assigned to wood production. The civil society had the highest mean rank of allocation priority scores. We found significant differences in priority scores between the civil society and the other three groups, highlighting the civil society and market agents as the most discordant groups. We spatially evaluated potential for conflicts among group ESs allocation priorities. The findings suggest that this approach can be helpful to decision makers, increasing the effectiveness of forest management plan implementation.

Multicriteria Spatial Decision Support System for Soil Fertility Assessment in Agriculture

Multicriteria Spatial Decision Support System for Soil Fertility Assessment in Agriculture

Planning and Managing the Integrated Water System: A Spatial Decision Support System to Analyze the Infrastructure Performances

The demand for water is constantly increasing, while there are factors related to climate change and pollution that make it less and less available. Addressing this problem means being able to face it with a global approach, which takes into account that human beings need water to survive, as well as all the systems on which they rely, namely sanitation, health, education, business, and industry. While human behavior is influenced by the growing awareness on this topic promoted by organizations specifically targeting this mission, the need to protect water resources in operational terms has led mainly to the need for smart urban infrastructure planning, consistent with the objective of promoting sustainable development. To this aim, the authorities in charge of monitoring the implementation of the investment plans by operators need to perform accurate evaluations of the technical quality of the services provided. The present paper introduces a framework to design a Multi-criteria Spatial Decision Support System, conceived to help decision-makers define and analyze the investment priorities of the individual service operators. By building a knowledge model of the network under investigation, decision-makers are aware of physical components of the whole system and are provided with an intervention priority index related to the network objects that could be affected by the planning action to be implemented.

The reintroduction of Castor fiber in Piedmont (Italy): An integrated SWOT-spatial multicriteria based approach for the analysis of suitability scenarios

The Castor fiber or Eurasian beaver can change its habitat by building dams and creating ponds. For this reason, Castor fiber is known as an “ecosystem engineer” for aquatic and riparian environments. Despite its ecological importance, at the beginning of the 20th century the population was reduced to only 1200 beavers in Europe and Asia, due to uncontrolled hunting. Recently, some reintroductions and translocations have partly re-established the population. In Italy, however, the beaver disappeared in the 16th century and no action has been taken despite the recommendation of the Council of Europe to perform a feasibility study.This research evaluates beaver reintroduction and identifies suitable areas in Italy and, in particular, in the Piedmont region. In order to achieve this, a SWOT analysis combined with a Spatial Multicriteria Analysis was performed. Firstly, the zoological and ethological aspects concerning this rodent were studied, as well as the historical reasons that led to its disappearance in Italy and near extinction in Eurasia. Secondly, Strengths, Weaknesses, Opportunities and Threats (SWOT) of the territory were identified for beaver reintroduction. The SWOT analysis was implemented, as the starting point for the spatial multicriteria analysis. Thirdly, the Multicriteria Spatial Decision Support System (MC-SDSS) was structured into two criteria, i.e. Potentials and Criticalities, representing the spatialization of strengths and weaknesses. The final result of the MC-SDSS is a map showing suitable areas for beaver reintroduction in Piedmont. This map is the weighted sum of the maps of criticalities and potentialities, performed through a set of GIS operations and weighted through a pairwise comparison of criteria by experts.The analysis was conducted for the Piedmont region, but the integrated approach and the set of criteria can also be applied in other regions. Moreover, this mixed-method approach takes into account the characteristics necessary for the choice of suitable beaver habitats and also includes economic and social aspects. Therefore, it is an improvement on the Habitat Suitability Index (HIS), generally used in reintroductions. The aspects considered in the analysis are fundamental for the future development of a shared action plan, which considers both technical and social motivations and acts for the long-term on a wide area.

Environmental, economic and socio-institutional context of the sustainability index: Evidence from Italy

The aim of this study is to define a methodology for assessing sustainability at different levels of detail. For the definition of the conditions of sustainability, the approach known as the triple bottom line was used. The study developed concerns the identification of a set of environmental, economic, and socio-institutional indicators and the elaboration of the same in a synthetic analysis index, organized in a hierarchical structure. An index for measuring irrigation sustainability has been built. This index, called the Sustainable Irrigation Index (SII), allows monitoring and assessment of the sustainability of irrigation activities and policies, at various territorial analysis scales, varying from the regional to the agricultural company. We proceeded with the creation of a multi-criteria spatial decision support system (GIS-based). The implementation of the index took place using the GIS IDRISI software. Finally, the index was applied to the concrete case of a Province of the Calabria region

A web-based tool framing a collective method for optimizing the location of a renewable energy facility and its possible application to sustainable STEM education

Abstract In this study, a prototype web-based tool is introduced for the estimation of the Location Suitability Assessment of a Biomass Plant (LSABP): input demands, inner procedures, and output results in response to various levels of government strategies. A collective methodology of Geographic Information System-Multi-Criteria Decision Analysis (GIS-MCDA) and the Fuzzy-DEcision-MAking Trial and Evaluation Laboratory (F-DEMATEL) is presented. After implementing the Weighted Linear Combination (WLC) and two-way sensitivity analysis, we accomplish the most suitable biomass plants’ locations. The developed web-based tool framing the collective method targets and generates Multi-Criteria-Spatial Decision Support System (MC-SDSS). Precisely, four main sections are described as general overview, MC-SDSS, two-way sensitivity analysis, and final result section for the LSABP. In final result section, users particularly test the location suitability option for five biomass plants with the chosen criteria. The results confirm that the suitable locations of biomass plants are situated near forests and in zones with low transport costs, which comprise only 9.25% highly suitable area. Five plants are not located in the highly suitable areas. The most influential criteria of the LSABP are the vegetation cover, agricultural area, transport cost, and potential demand criteria. By assessing diverse alternatives, the LSABP assists certain decisions for adjusting and analyzing the setting of biomass facilities on a strategic, tactical, and operational level. Therefore, this work demonstrates the novelty of framework development as a cleaner production for integrating globally accessible spatial and environmental algorithms and datasets in computing with newly designed and implemented an interactive web-based tool for the evaluation purpose of various personal and government levels. Particularly, it is necessary to apply its experience to the possible sustainable Science, Technology, Engineering, and Mathematics (STEM) education, which requires constant acquisition of knowledge and its dissemination.

Suitability assessment using multicriteria spatial decision support system for the existing landfill sites of Chittagong City, Bangladesh

Solid waste management is a great concern in the urban areas of the developing countries. A sanitary landfill is an essential facility for efficient management of solid waste to control unpleasant odor, disease-spreading pathogens, and disposable mass. Chittagong, the second largest city in Bangladesh with an ever-increasing population, has three landfill sites within the metropolitan area. The sites are near the residential areas. The waste collection, transportation, and disposal techniques for landfilling are not well established in the city. As a result, solid wastes are randomly thrown into lowlands, rivers, streets, and open drains in an uncontrolled manner. Consequently, these waste deposits act as breeding ground of various disease vectors, such as rats, mosquitoes, flies, cockroaches, and pathogenic microorganisms. The leachate also contaminates groundwater due to improper linear design of the landfills. Therefore, the human health of the city dwellers is at risk due to the contaminated environment of the city. In the present study, the suitability of the existing landfill sites of the city has been evaluated using GIS-based multicriteria analysis technique. The importance of relevant parameters required for landfill site selection has been determined using multicriteria weighted average method. Then, the individual map of each parameter was created and overlaid all maps of different parameters to assess suitability of the landfill sites in terms of suitability score using ArcGIS.

An interactive multi-criteria spatial decision support system for energy retrofitting of building stocks using CommuntiyVIZ to support urban energy planning

A major concern for any city is urban energy planning, which is particularly multi-sectoral and multi-actor oriented. This concern is especially critical for the built-up urban zones, which are predominantly responsible for the bulk of energy consumption and carbon emissions. Hence, an interdisciplinary, integrated approach is needed to address this complex challenge. This study focuses on both energy retrofit interventions for existing building stocks and the integration of participative processes in decision-making. It deals with the development of a stakeholder-oriented approach to implementing effective strategies in urban energy planning. This can help define meaningful building energy retrofitting scenarios that focus on energy consumption and environmental impact, in addition to economic and social considerations. A major outcome of this study is the development of a new multicriteria spatial decision support system (MC-SDSS) that is an interactive energy-related plug-in for a geographic information system (GIS) environment, adapted from CommunityViz. The methodology used to deliver the tool can be applied to other contexts and situations due to its flexibility. The new MC-SDSS facilitates the decision-making process for stakeholders who ask “what if” questions and visualise “if-then” scenarios in real time to handle the entire planning procedure adequately.

A cyberGIS-enabled multi-criteria spatial decision support system: A case study on flood emergency management

ABSTRACTWith the increased frequency of natural hazards and disasters and consequent losses, it is imperative to develop efficient and timely strategies for emergency response and relief operations. In this paper, we propose a cyberGIS-enabled multi-criteria spatial decision support system for supporting rapid decision making during emergency management. It combines a high-performance computing environment (cyberGIS-Jupyter) and multi-criteria decision analysis models (Weighted Sum Model (WSM) and Technique for Order Preference by Similarity to Ideal Solution Model (TOPSIS)) with various types of social vulnerability indicators to solve decision problems that contain conflicting evaluation criteria in a flood emergency situation. Social media data (e.g. Twitter data) was used as an additional tool to support the decision-making process. Our case study involves two decision goals generated based on a past flood event in the city of Austin, Texas, U.S.A. As our result shows, WSM produces more diverse values and higher output category estimations than the TOPSIS model. Finally, the model was validated using an innovative questionnaire. This cyberGIS- enabled spatial decision support system allows collaborative problem solving and efficient knowledge transformation between decision makers, where different emergency responders can formulate their decision objectives, select relevant evaluation criteria, and perform interactive weighting and sensitivity analyses.

Multi-criteria spatial decision support system for identifying strategic roads in disaster situations

A road transportation network has an important role in the management of disaster situations. Despite its' vulnerability to disasters, it helps to provide emergency responses to disaster management practices. Therefore it is required to identify the most important roads in the network in order to support decision-makers to make appropriate decisions about the roads.This paper introduces an integrated methodology to evaluate the transportation network performance (TNP) in disaster situations by developing a multi-criteria spatial decision support system (MC-SDSS). The developed MC-SDSS is a fully integrated system of Geospatial Information System (GIS) and Multi-Criteria Decision Making (MCDM) methods. On the one hand, GIS functionalities are used for storing the data, performing the analyses in order to produce the required criteria and displaying the results. On the other hand, AHP as a well-known MCDM method is used to receive priorities and preferences of decision-makers about the criteria.Based on the decision-making model (intelligent, design, and choice), four criteria are selected as indicators for evaluating the TNP in disaster situations: capacity, accessibility, vulnerability, and importance criteria. In this regard, criteria maps are generated by GIS tools, the experts' preferences about the criteria are acquired by AHP comparison matrix, and a ranking of the roads are prepared and visualized on the MC-SDSS. Finally, by utilizing the One-At-Time approach as the sensitivity analysis method, MC-SDSS tries to determine the robustness of the results due to the variation or uncertainty resulting from changing the important scales of the criteria in the AHP pairwise comparison matrix.The results show that about 9, 33, 20, and 38% of the roads are very high, high, moderate, and low strategic in the case study (Mazandaran province, Iran) respectively. It also shows that capacity/accessibility pairwise comparison is the most sensitive comparison in the AHP comparison matrix.

Spatial multicriteria decision support for robust land-use suitability: The case of landfill site selection in Northeastern Greece

Multicriteria spatial decision support systems (MC-SDSS) have emerged as an integration of geographical information systems (GIS) and multiple criteria decision aid (MCDA) methods for incorporating conflicting objectives and decision makers’ preferences into spatial decision models. In this paper, we present spatial UTASTAR (S-UTASTAR), a raster-based MC-SDSS for land-use suitability analysis. The multicriteria component of the system is based on the UTA-type disaggregation-aggregation approach. S-UTASTAR is applied in a raster-based case study concerning land-use suitability analysis to identify appropriate municipal solid waste landfill (MSW) sites in Northeast Greece. Moreover, robustness analysis tools are implemented to guarantee robust decision support results. More specifically, during the aggregation phase, the Stochastic Multiobjective Acceptability Analysis (SMAA) is used to indicate the frequency at which a site achieves the best ranking positions within a large set of alternative landfill sites.

Knowledge sharing in Web-based collaborative multicriteria spatial decision analysis: An ontology-based multi-agent approach

The Web-based Multicriteria Spatial Decision Support Systems (MC-SDSS) enhance the collaborative/participatory spatial decision making by providing the relevant GIS-based MCDA (Multicriteria Decision Analysis) tools for active participation/collaboration. Typically, regular/novice decision makers need to acquire knowledge from expert decision makers in a participatory decision making process. Over the last decade or so, significant research efforts have been made to use Web-based GIS-MCDA tools for collaborative spatial decision making. However, these efforts as the collaborative decision making tools lack a knowledge sharing mechanism or framework that allow for exchange and sharing of decision knowledge between decision makers (decision makers' agents). In the case of providing knowledge sharing capabilities by these tools, exchange of decision knowledge relies on decision makers' common sense to manually interpret the meanings of each other's knowledge and use the right ones. To address these limitations, this study proposes an ontology-based multi-agents approach for knowledge sharing in a collaborative MC-SDSS. The decision makers' agents committed to the ontology can interoperate and exchange decision knowledge with intended and unambiguous meanings.

Combining spatial analysis with MCDA for the siting of healthcare facilities

Site selection of healthcare facilities is a typical ill-structured decision problem since it involves multiple criteria and sometimes conflicting stakeholders. Nowadays the site selection problem is ignored by most of the existing evaluation tools. Through a deep literature review the research proposes an evaluation system divided into four criteria (Functional quality, Location quality, Environmental quality, Economical aspects), each in turn composed by sub-criteria supported by the methodology of Multi-Criteria Decision Analysis (MCDA), with the aim of assessing the land suitability for new healthcare structures, in order to improve the transparency and robustness of the decision-making process. After that, spatial component has been added to MCDA using Geographic Information System (GIS). The Multi-Criteria-Spatial Decision Support Systems (MC-SDSS) allow to address choices by an integrated knowledge about territory and by the explicit consideration of the spatial dimension of decision problems. The case study selected to test this method is “La Città della Salute”, in the city of Milan, Italy, a project aimed to answer to scientific and cultural changes of contemporary medicine. The focus of the research is to identify suitability maps able to verify the adequacy of the territory in an adaptive perspective, expanding the alternatives’ domain.

Prevention of landfill pollution by multicriteria spatial decision support systems (MC-SDSS): development, implementation, and case study.

Landfilling of municipal solid waste (MSW) is one of the serious environmental concerns as improper location of MSW landfill site can release the pollutants into the surrounding environment. The process of selecting MSW landfill site is a complicated decision making problem since it is subjected to simultaneous assessment of several environmental criteria, rules, and restrictions besides sociocultural and economic ones. The current study suggests a framework based on Multicriteria spatial decision support systems (MC-SDSS) to select landfill site. The MC-SDSS is an advanced method to integrate multiple criteria decision analysis (MCDA) and geographical information systems (GIS) techniques. This approach enables the incorporation of several conflicting objectives and preferences into spatial decision models. In this study, 14 criteria were chosen and then divided into environmental, sociocultural, and economic categories. Finally, suitability maps were generated based on the MC-SDSS analysis. The developed method was implemented in a real case study in Arak city in northwestern region of Iran, which is environmentally sensitive area. The suitability maps of the case study in Arak showed that 10% (391km2) is least suitable area, 23% (942km2) is low suitable, 37% (1507km2) is moderate suitable, 19% (783km2) is suitable, and 11% (489km2) is most suitable locations for landfill site, and finally, three best alternative sites were introduced for the final landfill site.

Wetland restoration prioritizing, a tool to reduce negative effects of drought; An application of multicriteria-spatial decision support system (MC-SDSS)

In recent years, large parts of arid and semi-arid areas in the world are dealing with water restrictions. In these areas, wetlands provide habitats for migratory birds and have a critical role in socio-ecological systems. Generally, in these areas, changing water-use patterns because of land-use change and water limitation because of climate change have led to the loss of wide areas of wetlands. Wetland restoration is suggested to restore the functions and values of wetlands that have been destroyed or affected by stresses. In this paper, a new application of wetland restoration prioritizing is introduced; restoration prioritizing to reduce the negative effects of drought. In this method, areas with the highest priority for restoration will be determined in a wetland destroyed because of water limitations. Multicriteria-spatial decision support system (MC-SDSS) was used to plan a scheme for Hamun wetlands restoration prioritizing in order to reduce the negative effects of drought and to restore the wetlands. This prioritization-determined areas that are valuable for Long-term water conservation, reduce the negative effects of dust storms and conserve water bird’s habitats. This method was used in a wetland that is the only water resource in the middle of a wide arid plain. Because of water limitation, it is not possible to restore the hole wetland; therefore, different parts of this wetland were prioritized for restoration. Based on the results, it is possible to produce a model to determine which priority can be restored in each amount of water volume. In this way, it becomes clear for decision-makers to select areas for restoration in different volumes of water. The result of this study shows that since MC-SDSS decreases conflicts between alternatives in a decision-making process and uses their spatial situation, it is a preferred method to balance among conflicting goals. Furthermore, because spatial data are the most important parts of MC-SDSS, this paper shows the ability of remote sensing to be used in MC-SDSS method. It seems that in the future; remote sensing will have the most important role in MC-SDSS.

A fuzzy multi-criteria spatial decision support system for solar farm location planning

In recent years, investment in solar energy has increased substantially across countries. Thus, selecting convenient locations for solar farms has become a fundamental problem when determining the investment required due to differences in climatic factors, the type and availability of land, transportation infrastructures, and the quality of power lines. Multi-Criteria Evaluation approaches based on crisp data are generally used in the selection process of optimal locations. However, despite being crisp, the data available when considering the evaluation criteria of the different alternatives constitute a discrete approximation performed on a spatial grid of potential locations. Thus, we introduce a three-stage fuzzy evaluation framework designed to account for the imprecision inherent to the evaluations when identifying the most convenient location for constructing solar power farms. First, we implement ANFIS (Adaptive Neuro-Fuzzy Inference System) on the set of grid intersection crisp data points and derive a coherent set of approximations per each potential discrete location and evaluation criterion. Then, the fuzzy AHP (Analytic Hierarchy Process) method is used to determine the weights of the different criteria considered from the linguistic evaluations provided by different experts. Finally, we define a set of if-then rules combining the different ANFIS evaluation criteria and their weights within a FIS (Fuzzy Inference System) whose output is used to determine the most convenient location for constructing a solar power farm. The efficacy of the proposed evaluation framework is demonstrated through its application to the Iranian regions of Kerman and Yazd.