A Methodology for the Selection of Multi-Criteria Decision Analysis Methods in Real Estate and Land Management Processes

Real estate and land management are characterised by a complex, elaborate combination of technical, regulatory and governmental factors. In Europe, Public Administrators must address the complex decision-making problems that need to be resolved, while also acting in consideration of the expectations of the different stakeholders involved in settlement transformation. In complex situations (e.g., with different aspects to be considered and multilevel actors involved), decision-making processes are often used to solve multidisciplinary and multidimensional analyses, which support the choices of those who are making the decision. Multi-Criteria Decision Analysis (MCDA) methods are included among the examination and evaluation techniques considered useful by the European Community. Such analyses and techniques are performed using methods, which aim to reach a synthesis of the various forms of input data needed to define decision-making problems of a similar complexity. Thus, one or more of the conclusions reached allow for informed, well thought-out, strategic decisions. According to the technical literature on MCDA, numerous methods are applicable in different decision-making situations, however, advice for selecting the most appropriate for the specific field of application and problem have not been thoroughly investigated. In land and real estate management, numerous queries regarding evaluations often arise. In brief, the objective of this paper is to outline a procedure with which to select the method best suited to the specific queries of evaluation, which commonly arise while addressing decision-making problems. In particular issues of land and real estate management, representing the so-called “settlement sector”. The procedure will follow a theoretical-methodological approach by formulating a taxonomy of the endogenous and exogenous variables of the multi-criteria analysis method

A Spatial Decision Support System for Agricultural Land Management in Maros Region, Indonesia

Land management which is increasingly complex from time to time, land convertion due to increasing population have caused conflicting various interests. Land management models developed to date are less able to answer the problems quickly and dynamically. Maros regency is one of the biggest producers of rice in South Sulawesi Indonesia. Its variability is fairly complex, consisting of coast, low land, and high land. Having a border with Makassar, its population pressure causes a bigger change of land function. It thus needs a model that can provide an optimal solution of land use and land management. The purpose of this research is to develop a model of Spatial Decision Support System (SDSS), which can help spatial decisions for the best land management of food crops,  and to test the validity and sensitivity of the models. In this study, SDSS development methods integrate fuzzy set, Analytic Hierarchy Process (AHP), and Compromise Programming modules, to produce spatial information on land management. SDSS design utilizes some knowledge input in the operation, including experts who understand the mechanism of the SDSS and its applications. The results of study are in form of spatial distribution of Land Suitability Index (LSI) resulting from land quality assessment. The results can be used to simulate food land management models in various scenarios. Compromised situation between biophysical and non-biophysical parameters provide distribution pattern of values of land management for food crops. Keywords: Spatial Decision Support System, fuzzy set, Analytical Hierarchy Process and Compromise Programmin

An Integrated Fuzzy MCDM Hybrid Methodology to Analyze Agricultural Production

A hybrid model was developed by combining multiple-criteria decision-making (MCDM) with the analytic hierarchy process (AHP) and a fuzzy set to give decision support for choosing sustainable solutions to agricultural problems. Six steps were taken to build the suggested hybrid model: identifying and weighing criteria; normalizing data using fuzzy membership functions; calculating the weighting of the criteria using AHP; and selecting the best alternative for the agricultural problem. The objective of this case study is to demonstrate how agricultural production techniques (APTs) are becoming more complex as agricultural production becomes more complex. Organic agriculture aims to protect both the environment and consumer satisfaction by utilizing organic management practices that do not have the negative effects associated with conventional and genetic engineering production. Meanwhile, products obtained through conventional and genetic engineering techniques are more cost-effective. To present the superiority of the proposed fuzzy MCDM hybrid model, this problem is used as the causative agent’s dataset. Because the challenge involves a large number of competing quantitative and qualitative criteria, the assessment approach should improve the ratio of input data to output data. As a result, agricultural productivity should be controlled holistically. However, because the problem may contain both qualitative and quantitative facts and uncertainties, it is necessary to represent the uncertainty inherent in human thinking. To achieve superior outcomes, fuzzy set theory (FST), which enables the expression of uncertainty in human judgments, can be integrated with). The purpose of this study is to present a novel MCDM approach based on fuzzy numbers for analyzing decision-making scenarios. The proposed methodology, which is based on Buckley’s fuzzy analytic hierarchy process (B-FAHP) and the Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (F-TOPSIS), uses Buckley’s fuzzy analytic hierarchy process (B-FAHP) and fuzzy TOPSIS to determine weights and rank alternatives, respectively. As a result, we attempted to include both the uncertainty and hesitancy of experts in the decision-making process through the use of fuzzy numbers. We have three main criteria in this study: Satisfaction (C1), Economy (C2), and Environment (C3). An important objective of the current research is to build a complete framework for evaluating and grading the suitability of technologies. A real-world case study is used to demonstrate the suggested paradigm’s validity. © 2022 by the authors. Licensee MDPI, Basel, Switzerland

Integrated Framework for Inclusive Town Planning Using Fuzzy Analytic Hierarchy Method for a Semi Urban Town

Planning is a continuous process and must incorporate a regular evaluation of implementation and further revision for effective and efficient utility for the betterment of society through modification of the planning standards. Development plans for cities / towns are criticized for being rigid and static, having little regard for investment planning efforts, and taking a very long time in the process of formulation and approval. In depth analysis and review of the existing situation, covering the demographic, economic, financial, infrastructure, physical, environmental, and institutional aspects, is important so as to identify the strengths and weaknesses in the city overall development. In the present study, an attempt has been made to thoroughly review the existing planning standards adopted for the preparation and implementation of development plans in India, especially in Maharashtra. Since the development plan's objectives are not measurable, this study will use the Fuzzy Analytic Hierarchy Process (AHP) to assess their level of performance. For the purpose of identifying the various viewpoints of various stakeholders, field surveys and questionnaire surveys were conducted. This application can be used as an objective evaluation tool for planners and policy makers to improve planning practices and provide necessary knowledge for revising plans. The results indicated the importance of criteria from the pre-planning, preparation, and implementation stages of DP. These results were used for two semi-urban towns in Maharashtra regions and could also be used by planning engineers for further development of planning standards. Doi: 10.28991/CEJ-2022-08-12-07 Full Text: PD

Land-use suitability evaluation for organic rice cultivation using fuzzy-AHP ELECTRE method

Land conversion to organic agriculture is the answer to land degradation problems that interfere with land resources sustainability. An evaluation of land-use suitability is crucial to measure the appropriateness of land for agricultural cultivation. Specifically, organic rice cultivation has some particular standard criteria such as temperature, rainfall, soil depth, pH, c-organic, slope, erosion level, a transition period that influence ranking results, and land suitability classes. Eight organic farmlands were used as alternatives, namely Sawangan, Mangunsari, Tirtosari, Podosoko, Butuh, Krogowanan, Kapuhan, and Jati. Fuzzy Analytic Hierarchy process is used to determine the level of importance of the criteria based on weight assessments by three agricultural experts. The ELECTRE method is applied to rank the most suitable land from several alternatives for organic rice cultivation. The combination of these two multi-criteria decision-making methods complements each other to solve problems in land suitability evaluation. A web-based decision support system (DSS) was created to accelerate data processing integration and present factual information from the land suitability selection process. The implementation of DSS with fuzzy-AHP ELECTRE for evaluating land-use suitability in organic rice cultivation provided the best score for Tirtosari with Ekl=4 and spearman rank correlation the system comparison results with actual data rs=0.95. This study's results indicate that integrating the web with fuzzy-AHP ELECTRE is quite effectively applied for decision-making in organic farming

Land-use suitability evaluation for organic rice cultivation using fuzzy-AHP ELECTRE method

Land conversion to organic agriculture is the answer to land degradation problems that interfere with land resources sustainability. An evaluation of land-use suitability is crucial to measure the appropriateness of land for agricultural cultivation. Specifically, organic rice cultivation has some particular standard criteria such as temperature, rainfall, soil depth, pH, c-organic, slope, erosion level, a transition period that influence ranking results, and land suitability classes. Eight organic farmlands were used as alternatives, namely Sawangan, Mangunsari, Tirtosari, Podosoko, Butuh, Krogowanan, Kapuhan, and Jati. Fuzzy Analytic Hierarchy process is used to determine the level of importance of the criteria based on weight assessments by three agricultural experts. The ELECTRE method is applied to rank the most suitable land from several alternatives for organic rice cultivation. The combination of these two multi-criteria decision-making methods complements each other to solve problems in land suitability evaluation. A web-based decision support system (DSS) was created to accelerate data processing integration and present factual information from the land suitability selection process. The implementation of DSS with fuzzy-AHP ELECTRE for evaluating land-use suitability in organic rice cultivation provided the best score for Tirtosari with Ekl=4 and spearman rank correlation the system comparison results with actual data rs=0.95. This study's results indicate that integrating the web with fuzzy-AHP ELECTRE is quite effectively applied for decision-making in organic farming

An Assessment of Land Use/Cover Suitable for Peri-urban Green Space Development: an Example of an Integration of GIS with the Multi-Criteria Analysis (MCA) Approach

Land allocation priorities to urban green cover are usually neglected particularly in the countries of developing economies such as Turkey. Lack of urban green space can cause many social and physical problems among the residents. Therefore, urban planning and policy should incorporate suitable green land in the urban planning of cities to optimise the benefits obtained from urban green spaces. Land suitability analysis is a commonly used methodology which provides a framework for developing strategies in the planning of green land development. Two different approaches will be utilised for the assessment of suitability of land uses for urban agriculture, forest and natural vegetation in the Pendik district of Istanbul. Standardisation of values in criteria maps was done using the deterministic approach in the first case whereas fuzzy membership was utilised as an alternative in the second case. Analytical Hierarchical Process (AHP) was used for the weighting of sub-criteria and map layers were overlaid using the weighted linear combination using the GIS software. Geophysical factors, transport and services accessibility, land cover/use, blue and green amenities, soil properties, geology and erosion susceptibility are the main criteria selected for the assessment of urban green land suitability. The provision of suitable land for urban agriculture, forest and natural vegetation uses will provide a framework to the land use planning and decision support aimed at contributing to urban sustainable development

Mapping the Land-Use Suitability for Urban Sprawl Using Remote Sensing and GIS Under Different Scenarios

Urbanization is one of the important issues in fast developing countries, such as China, Turkey, Brazil, and South Africa. Therefore, sustainable urbanization strategies come into question while designing the cities. In this point, land-use suitability mapping for urban areas is of importance. Spatial information sciences, such as geographical information systems (GIS) and remote sensing are applied widely for mapping land-use suitability. In this study, Van City, which is the most crowded city in eastern Turkey, was evaluated by applying three different scenarios called ecological, economic, and sustainable. The multi-criteria evaluation technique was used in GIS environment in the mapping stage. Distance from roads, distance from urban boundary, hillshade, slope, elevation, land-use cover, and land-use ability factors were used as inputs in the analysis stage. The weights of each input factor were calculated according to urban change dynamics between 2002 and 2015. As a result of the study, the weighting approach using the natural change dynamics of Van City has a great potential to define objective weights. In addition, Van City was developed orderly on agricultural lands and grasslands, and it was not a sustainable development for the region because the main income is still agriculture and animal production, so a new strategy was designed in a sustainable scenario to prevent agriculture and grassland area loss in a mutual benefit between nature and human

Neuro-fuzzy resource forecast in site suitability assessment for wind and solar energy: a mini review

Abstract:Site suitability problems in renewable energy studies have taken a new turn since the advent of geographical information system (GIS). GIS has been used for site suitability analysis for renewable energy due to its prowess in processing and analyzing attributes with geospatial components. Multi-criteria decision making (MCDM) tools are further used for criteria ranking in the order of influence on the study. Upon location of most appropriate sites, the need for intelligent resource forecast to aid in strategic and operational planning becomes necessary if viability of the investment will be enhanced and resource variability will be better understood. One of such intelligent models is the adaptive neuro-fuzzy inference system (ANFIS) and its variants. This study presents a mini-review of GIS-based MCDM facility location problems in wind and solar resource site suitability analysis and resource forecast using ANFIS-based models. We further present a framework for the integration of the two concepts in wind and solar energy studies. Various MCDM techniques for decision making with their strengths and weaknesses were presented. Country specific studies which apply GIS-based method in site suitability were presented with criteria considered. Similarly, country-specific studies in ANFIS-based resource forecasts for wind and solar energy were also presented. From our findings, there has been no technically valid range of values for spatial criteria and the analytical hierarchical process (AHP) has been commonly used for criteria ranking leaving other techniques less explored. Also, hybrid ANFIS models are more effective compared to standalone ANFIS models in resource forecast, and ANFIS optimized with population-based models has been mostly used. Finally, we present a roadmap for integrating GIS-MCDM site suitability studies with ANFIS-based modeling for improved strategic and operational planning

Multi crteria decision making and its applications : a literature review

This paper presents current techniques used in Multi Criteria Decision Making (MCDM) and their applications. Two basic approaches for MCDM, namely Artificial Intelligence MCDM (AIMCDM) and Classical MCDM (CMCDM) are discussed and investigated. Recent articles from international journals related to MCDM are collected and analyzed to find which approach is more common than the other in MCDM. Also, which area these techniques are applied to. Those articles are appearing in journals for the year 2008 only. This paper provides evidence that currently, both AIMCDM and CMCDM are equally common in MCDM