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Erdin, Ceren, and Halil Emre Akbaş. "A Comparative Analysis of Fuzzy TOPSIS and Geographic Information Systems (GIS) for the Location Selection of Shopping Malls: A Case Study from Turkey." Sustainability 11, no. 14 (July 14, 2019): 3837. http://dx.doi.org/10.3390/su11143837.
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Multi-criteria decision-making (MCDM) techniques are increasingly being used for the problem of location selection, which directly affects the long-term success of a company. Besides these techniques, with the advantage of handling both spatial and non-spatial data, geographic information systems (GIS) also represent a useful method for selecting the appropriate location for different kinds of facilities and sites. In this respect, this study aims to compare the results of a MCDM technique, fuzzy technique for order preference by similarity to ideal solution (TOPSIS), and GIS for the location selection of shopping malls in Turkey. According to the results of both fuzzy TOPSIS and GIS, the Marmara region was determined as the best alternative for shopping malls in Turkey.
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Ozdemir, Sahika, and Yavuz Ozdemir. "Prioritizing store plan alternatives produced with shape grammar using multi-criteria decision-making techniques." Environment and Planning B: Urban Analytics and City Science 45, no. 4 (January 6, 2017): 751–71. http://dx.doi.org/10.1177/0265813516686566.
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To generate alternatives and variations of specific architectural models, shape grammars can be used by applying a set of geometric rules step by step. With the development in human life, advances in store design, design concept, commercial buildings’ architectural and spatial fiction, the magazine of the interior, and facade design cause rising competition between stores and also between designers. For this reason, in this paper we study the evaluation of store plan alternatives produced with shape grammar using two of multi-criteria decision-making (MCDM) techniques with fuzzy numbers, namely fuzzy analytic hierarchy process and fuzzy analytic network process. The main contribution of this paper is to prioritize plan alternatives using numerical methods with experts’ view. To the authors’ knowledge, this will be the first interdisciplinary study which uses MCDM techniques for evaluating shape grammar outputs in architectural design.
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Vitianingsih, Anik Vega, Nanna Suryana, and Zahriah Othman. "Spatial analysis model for traffic accident-prone roads classification: a proposed framework." IAES International Journal of Artificial Intelligence (IJ-AI) 10, no. 2 (June 1, 2021): 365. http://dx.doi.org/10.11591/ijai.v10.i2.pp365-373.
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<span id="docs-internal-guid-9754d3d8-7fff-a7d2-6605-1c8f8c5a707a"><span>The classification method in the spatial analysis modeling based on the multi-criteria parameter is currently widely used to manage geographic information systems (GIS) software engineering. The accuracy of the proposed model will play an essential role in the successful software development of GIS. This is related to the nature of GIS used for mapping through spatial analysis. This paper aims to propose a framework of spatial analysis using a hybrid estimation model-based on a combination of multi-criteria decision-making (MCDM) and artificial neural networks (ANNs) (MCDM-ANNs) classification. The proposed framework is based on the comparison of existing frameworks through the concept of a literature review. The model in the proposed framework will be used for future work on the traffic accident-prone road classification through testing with a private or public spatial dataset. Model validation testing on the proposed framework uses metaheuristic optimization techniques. Policymakers can use the results of the model on the proposed framework for initial planning developing GIS software engineering through spatial analysis models.</span></span>
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Abdul Rasam, Abdul Rauf, Noresah Mohd Shariff, JilorisF Dony, and Oliver Hoon Leh Ling. "Local Spatial Knowledge for Eliciting Risk Factors and Disease Mapping of Tuberculosis Epidemics." Environment-Behaviour Proceedings Journal 5, SI2 (December 27, 2020): 45–51. http://dx.doi.org/10.21834/ebpj.v5isi2.2522.
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Predicting risk areas of tuberculosis (TB) epidemics needs a proper understanding of the disease transmission process in identifying holistic risk factors. This study was performed to determine the causative factors triggering the epidemics in Shah Alam, Malaysia by utilising spatial analysis techniques and participation of local-expert knowledge or local spatial knowledge (LSK) approach. LSK approach was conducted to collect data on TB risk factors by combining experienced local experts' opinions, multi-criteria decision making (MCDM) analysis, and GIS mapping. The combination of experts participatory GIS and knowledge elicitation can generate a useful spatial knowledge framework for risk assessment of local epidemics. Keywords: Local spatial knowledge, MCDM method, experts participatory GIS, tuberculosis. eISSN: 2398-4287 © 2020. The Authors. Published for AMER ABRA cE-Bs by e-International Publishing House, Ltd., UK. This is an open access article under the CC BYNC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer–review under responsibility of AMER (Association of Malaysian Environment-Behaviour Researchers), ABRA (Association of Behavioural Researchers on Asians) and cE-Bs (Centre for Environment-Behaviour Studies), Faculty of Architecture, Planning & Surveying, Universiti Teknologi MARA, Malaysia. DOI: https://doi.org/10.21834/ebpj.v5iSI2.2522.
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Nalbant, Kemal Gökhan, Şahi̇ka Özdemi̇r, and Yavuz Özdemi̇r. "Evaluating Inclusive Campus Environment Design Criteria Using CFPR and FANP Methodologies." WSEAS TRANSACTIONS ON COMPUTER RESEARCH 9 (August 2, 2021): 92–102. http://dx.doi.org/10.37394/232018.2021.9.11.
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University campuses bring together individuals from different socio-cultural backgrounds. At the same time, university campuses contribute to the personal and intellectual development of individuals and serve as a socialization area. Campuses create vitality with their social, cultural, economic, and spatial effects. In this paper, we study for evaluating inclusive campus environment design criteria using the Fuzzy Analytical Network Process (FANP) and Consistent Fuzzy Preference Relations (CFPR) techniques, which are two Multi- Criteria Decision Making (MCDM) methods. Seven Inclusive Campus Environment Design Criteria are “Land Use Organization”, “Compactness”, “Connectivity”, “Configuration”, “Living campus”, “Greens” and “Context”. The major contribution of our study is to prioritize inclusive campus environment design criteria by using numerical methods from the decision maker's perspective. According to the authors’ knowledge, this will be the first interdisciplinary study to use MCDM methods for evaluating inclusive campus environment design criteria. Additionally, the results of both methodologies are compared
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Yildirim, Volkan, Tugba Memisoglu, Sevket Bediroglu, and H. Ebru Colak. "MUNICIPAL SOLID WASTE LANDFILL SITE SELECTION USING MULTI-CRITERIA DECISION MAKING AND GIS: CASE STUDY OF BURSA PROVINCE." Journal of Environmental Engineering and Landscape Management 26, no. 2 (June 27, 2018): 107–19. http://dx.doi.org/10.3846/16486897.2017.1364646.
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Rapid population growth, economic development and industrialization have created many problems related to municipal solid waste management (MSWM) in developing countries like Turkey. Solid waste disposal has become mandatory because of increasingly common factors such as global warming and contamination of water resources. In recent years, this situation has revealed the need for effective management of solid waste. Suitable site selection requires evaluation and analysis of multiplefactor. Therefore, it is very important that the design of landfill site selection take into account environmental, economical and sociologicalfactors. In order to do this, the Geographical Information System (GIS) used with Multi Criteria Decision Making (MCDM) techniques is a useful tool for creating a model. One such MCDM is the Spatial-integrated Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). In this study, TOPSIS was applied to integrate environmental, economical and sociological sensitivity into determine alternative solid waste landfill sites for Bursa Province, Turkey. Using the data obtained by comparing the geo-statistics, six of the most suitable landfill areas were determined. In the final stage, as a result of this study, the Kayapa district was identified as the most suitable landfill area.
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Lee, G., K. S. Jun, and E. S. Chung. "Group decision-making approach for flood vulnerability identification using the fuzzy VIKOR method." Natural Hazards and Earth System Sciences 15, no. 4 (April 20, 2015): 863–74. http://dx.doi.org/10.5194/nhess-15-863-2015.
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Abstract. This study proposes an improved group decision making (GDM) framework that combines the VIKOR method with data fuzzification to quantify the spatial flood vulnerability including multiple criteria. In general, GDM method is an effective tool for formulating a compromise solution that involves various decision makers since various stakeholders may have different perspectives on their flood risk/vulnerability management responses. The GDM approach is designed to achieve consensus building that reflects the viewpoints of each participant. The fuzzy VIKOR method was developed to solve multi-criteria decision making (MCDM) problems with conflicting and noncommensurable criteria. This comprising method can be used to obtain a nearly ideal solution according to all established criteria. This approach effectively can propose some compromising decisions by combining the GDM method and fuzzy VIKOR method. The spatial flood vulnerability of the southern Han River using the GDM approach combined with the fuzzy VIKOR method was compared with the spatial flood vulnerability using general MCDM methods, such as the fuzzy TOPSIS and classical GDM methods (i.e., Borda, Condorcet, and Copeland). As a result, the proposed fuzzy GDM approach can reduce the uncertainty in the data confidence and weight derivation techniques. Thus, the combination of the GDM approach with the fuzzy VIKOR method can provide robust prioritization because it actively reflects the opinions of various groups and considers uncertainty in the input data.
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SAYYED ALI, ALAVI, MESHKINI ABOLFAZL, and EBRAHIMI MOHAMMAD. "Operational site selection for disaster management bases in Tehran, Iran." MAUSAM 71, no. 3 (August 3, 2021): 431–42. http://dx.doi.org/10.54302/mausam.v71i3.42.
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Natural disasters play a main role in human life. It should be taken into consideration that it is impossible to predict these disasters from happening, but preparation for a good response for these disasters can be a good solution to decrease post-damage casualties in the cities. Herein, Disaster Management Bases in terms of prevention, preparation and dealing with the crisis play a key role, especially in Tehran and in times of natural disasters. There is no doubt that a high level and efficient function of these bases has a striking correlation with the way they are located in both an urban and regional level in a way that in addition to providing security of the bases against disasters, based on the service area they could be able to provide good services for the areas of crisis. This paper tries to use Multi Criteria Decision Making (MCDM) techniques and spatial analysis method in order to assess the effectiveness of these bases. Based on assessments Disaster Management Bases have spontaneously distributed in Tehran and have located in inappropriate places. Thus using MCDM with GIS analysis, the best locations in case study area was proposed.
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Lee, G., K. S. Jun, and E. S. Cung. "Group decision-making approach for flood vulnerability identification using the fuzzy VIKOR method." Natural Hazards and Earth System Sciences Discussions 2, no. 9 (September 30, 2014): 6141–71. http://dx.doi.org/10.5194/nhessd-2-6141-2014.
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Abstract. This study proposes an improved group decision making (GDM) framework that combines VIKOR method with fuzzified data to quantify the spatial flood vulnerability including multi-criteria evaluation indicators. In general, GDM method is an effective tool for formulating a compromise solution that involves various decision makers since various stakeholders may have different perspectives on their flood risk/vulnerability management responses. The GDM approach is designed to achieve consensus building that reflects the viewpoints of each participant. The fuzzy VIKOR method was developed to solve multi-criteria decision making (MCDM) problems with conflicting and noncommensurable criteria. This comprising method can be used to obtain a nearly ideal solution according to all established criteria. Triangular fuzzy numbers are used to consider the uncertainty of weights and the crisp data of proxy variables. This approach can effectively propose some compromising decisions by combining the GDM method and fuzzy VIKOR method. The spatial flood vulnerability of the south Han River using the GDM approach combined with the fuzzy VIKOR method was compared with the results from general MCDM methods, such as the fuzzy TOPSIS and classical GDM methods, such as those developed by Borda, Condorcet, and Copeland. The evaluated priorities were significantly dependent on the employed decision-making method. The proposed fuzzy GDM approach can reduce the uncertainty in the data confidence and weight derivation techniques. Thus, the combination of the GDM approach with the fuzzy VIKOR method can provide robust prioritization because it actively reflects the opinions of various groups and considers uncertainty in the input data.
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Tongbram, Purnachandra, and Chandra Upadhyaya. "POTENTIAL SITE SUITABILITY ANALYSIS OF SMALL HYDROPOWER PLANT IN IRANG RIVER CATCHMENT, MANIPUR, INDIA: A GEO-SPATIAL AND MCDM APPROACH." International Journal of Engineering Applied Sciences and Technology 7, no. 3 (July 1, 2022): 129–35. http://dx.doi.org/10.33564/ijeast.2022.v07i03.020.
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India being one of the leading developing country where 80% of its energy or power supply are produced by fossil fuel: coal, oil and solid biomass. Using of fossil fuel-based power led to environmental degradation and to reduce it an alternative power source is required. Amongst the alternate source, Hydropower is the most suitable source for power supply. Hydropower is one of the oldest renewable power sources where it generates power from the flow of water by converting its gravitational flow or potential energy of water source into electricity. Due to roughness and inaccessible of terrain of the study area, the use of conventional method becomes almost impossible. With the help of new innovative methodologies and techniques of Remote Sensing (RS) and Geographic Information System (GIS) this study has been carried out. In this study nine geo-spatial inputs are used to find the site suitable for small hydropower (SHP) project. The multi criteria decision making (MCDM) techniques is used to evaluate the input’s weights. After the weight is obtained for each input, it is overlaid according to its weight using overlay tool to obtained the site suitable for SHP project. The outcome of this study allows spotting identification of SHP potential zone
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Bahadori, Mohammad Sadegh, Alexandre B. Gonçalves, and Filipe Moura. "A GIS-MCDM Method for Ranking Potential Station Locations in the Expansion of Bike-Sharing Systems." Axioms 11, no. 6 (May 31, 2022): 263. http://dx.doi.org/10.3390/axioms11060263.
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Bicycle-sharing systems (BSSs) are an effective solution to reduce private car usage in most cities and are an influential factor in encouraging citizens to shift to more sustainable transport modes. In this sense, the location of BSS stations has a critical impact on the system’s efficiency. This study proposed an integrated geographic information system–multi-criteria decision-making (GIS-MCDM) framework that includes the analytic hierarchy process (AHP), technique for order preference by similarity to the ideal solution (TOPSIS), and spatial data processing in GIS to determine a ranking of potential locations for BSS stations. The results of the proposed GIS-MCDM method can be used for both planning a new BSS or expanding one that is currently under operation. The framework was applied to a case study for expanding GIRA, the BSS of Lisbon, Portugal. In it, location criteria were selected in four categories, including criteria from the literature and extracted from available transaction data; in addition, we also suggested some criteria. The rebalancing operator’s staff were the decision makers in this study via their responses to the AHP questionnaire. The rebalancing staff believed that the main criterion of “city infrastructure” with the two sub-criteria of “population density” and “slope” were the most important. Furthermore, the proximity to the “bike network” with the sub-criterion of “proximity to the current bike stations” had less importance. Each criterion’s weight and inconsistency rate were obtained using the Expert Choice software. The geographic values of each criterion were created utilizing the ArcGIS software, and its network analyst module was employed for applying location techniques. Based on the created suitability map, the city’s center was the main suitable area for establishing new stations. Forty-five new bike stations were identified in those areas and ranked using the TOPSIS technique.
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Arabameri, Alireza, Saro Lee, John P. Tiefenbacher, and Phuong Thao Thi Ngo. "Novel Ensemble of MCDM-Artificial Intelligence Techniques for Groundwater-Potential Mapping in Arid and Semi-Arid Regions (Iran)." Remote Sensing 12, no. 3 (February 4, 2020): 490. http://dx.doi.org/10.3390/rs12030490.
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The aim of this research is to introduce a novel ensemble approach using Vise Kriterijumska Optimizacija I Kompromisno Resenje (VIKOR), frequency ratio (FR), and random forest (RF) models for groundwater-potential mapping (GWPM) in Bastam watershed, Iran. This region suffers from freshwater shortages and the identification of new groundwater sites is a critical need. Remote sensing and geographic information system (GIS) were used to reduce time and financial costs of rapid assessment of groundwater resources. Seventeen physiographical, hydrological, and geological groundwater conditioning factors (GWCFs) were derived from a spatial geo-database. Groundwater data were gathered in field surveys and well-yield data were acquired from the Iranian Department of Water Resources Management for 89 locations with high yield potential values ≥ 11 m3 h−1. These data were mapped in a GIS. From these locations, 62 (70%) were randomly selected to be used for model training, and the remaining 27 (30%) were used for validation of the model. The relative weights of the GWCFs were determined with an RF model. For GWPM, 220 randomly selected points in the study area and their final weights were determined with the VIKOR model. A groundwater potential map was created by interpolating the values at these points using Kriging in GIS. Finally, the area under receiver operating characteristic (AUROC) curve was plotted for the groundwater potential map. The success rate curve (SRC) was computed for the training dataset, and the prediction rate curve (PRC) was calculated for the validation dataset. Results of RF analysis show that land use and land cover, lithology, and elevation are the most significant determinants of groundwater occurrence. The validation results show that the ensemble model had excellent prediction performance (PRC = 0.934) and goodness-of-fit (SRC = 0.925) and reasonably high classification accuracy. The results of this study could aid management of groundwater resources and assist planners and decision makers in groundwater-investment planning to achieve sustainability.
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Önden, İsmail. "INTEGRATING GIS WITH F-AHP FOR LOCATING A SINGLE FACILITY." Transport 33, no. 5 (December 19, 2018): 1173–83. http://dx.doi.org/10.3846/transport.2018.6677.
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Location selection problems stand out as popular research topics. Due to the popularity, different solution approaches emerged in the literature. Multi-criteria Decision Making (MCDM) techniques are examples of the solution approaches and they are frequently used because of their ordering capability in ranking the decision alternatives and success in representing decision makers’ experiences. On the other hand, Geographic Information Systems (GIS) is able to perform different spatial data analysis and provide geographic material. To reach a better decision, integration of experts’ opinions and certain geographic information derived from GIS is necessary. Within this context, in this paper, integration of the GIS abilities with Fuzzy Analytic Hierarchy Process (F-AHP) is discussed with two different integration methodologies for locating single facility. A hypothetical case study is provided to determine a location problem, which focuses on logistics activities. The results have shown that both proposed methodologies are able to order location alternatives in multiple criteria environments.
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Bahadori, Mohammad Sadegh, Alexandre B. Gonçalves, and Filipe Moura. "A Systematic Review of Station Location Techniques for Bicycle-Sharing Systems Planning and Operation." ISPRS International Journal of Geo-Information 10, no. 8 (August 17, 2021): 554. http://dx.doi.org/10.3390/ijgi10080554.
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Designing or expanding a bicycle-sharing system (BSS) involves addressing the infrastructure’s location of the bicycle stations. Station location is an essential factor for designing and implementing a new system or for its operation. In a complex spatial optimization context, geographic information systems (GIS) can support this decision problem. There are also numerous ways of subdividing the broad spectrum of location-allocation models used in previous studies. However, a station location comprehensive review and systematization with the specific aim of characterizing the state of the art of BSS is missing. The present research aimed to provide a comprehensive systematization for station location problems, criteria, and techniques, seeking to identify the current state of practice. We searched scientific publication databases to collect relevant publications—the final list comprised 24 papers for the literature review. The systematization addresses the two major problems concerning bicycle station location: initial network design and operation improvement (where changes in operating a BSS are implemented). Based on the literature, we propose a set of four main criteria for choosing appropriate places for bike stations (or parking) in a city: “bike network”, “operator”, “user”, and “city infrastructure”. The sub-criteria mentioned in the literature are categorized based on the proposed classification and new sub-criteria are suggested. We also group location modeling techniques into three categories: “mathematical algorithms”, “multi-criteria decision making”, and “GIS”. Combining GIS and multi-criteria decision making (MCDM) has received more attention in recent years to locate bike stations, evaluate their operating performance, and have more accurate and practical results.
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Özkan, Bariş, Eren Özceylan, I. brahim Halil Korkmaz, and Cihan Çetinkaya. "A GIS-based DANP-VIKOR approach to evaluate R&D performance of Turkish cities." Kybernetes 48, no. 10 (November 4, 2019): 2266–306. http://dx.doi.org/10.1108/k-09-2018-0456.
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Purpose The purpose of this study is to measure the R&D performance of 81 cities in Turkey by using a scientific approach. Design/methodology/approach A four-step solution approach is developed for this problem. In the first step, a hierarchical structure of 14 indicators (including number of patents, publications, R&D expense, etc.) in three dimensions is constructed. In the second step, explicitly and implicitly spatial indicators such as university location and R&D manpower are mapped by using geographic information system (GIS). In the third step, a hybrid multi-criteria decision making model, namely, DANP that combines decision-making trial and evaluation laboratory (DEMATEL) and analytic hierarchy process (ANP) techniques is applied to assign different level of importance to the indicators. In the last step, Višekriterijumska Optimizacijai kompromisno Rešenje (VIKOR) method is used to rank the performance of 81 cities. Obtained results are visualized using GIS to show the pros and cons of each city in terms of R&D performance. Findings Results of the paper show that Istanbul, Ankara and Konya are ordered as contenders of best R&D performances and on the contrary, Igdir, Sirnak and Tunceli are ordered as the worst R&D performances among 81 cities. Research limitations/implications One limitation of the study can be the considered criteria. However, all the criteria are obtained from literature and experts; thus, the paper covers as much criteria as possible. Practical implications The proposed study may allow Ministry of Science, Industry and Technology of Turkey to formulate more effective strategies to improve cities’ R&D performance. In addition, any country can apply the same methodology for measuring the R&D performance of their cities by using their related data. As the worst R&D city performances belong to the eastern part of Turkey, it can be deducted that the socio-cultural structure of the eastern part of the country needs improvement. Originality/value To the best of the author’s knowledge, this is the first study which applies a GIS-based MCDM approach for R&D performance measurement. Thus, the value of this paper belongs to both literature and real life.
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Albraheem, Lamya, and Leena Alabdulkarim. "Geospatial Analysis of Solar Energy in Riyadh Using a GIS-AHP-Based Technique." ISPRS International Journal of Geo-Information 10, no. 5 (May 3, 2021): 291. http://dx.doi.org/10.3390/ijgi10050291.
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In recent years, spatial multi-criteria decision analysis (MCDA) has been applied to different types of spatial problems, such as solar power site suitability. MCDA can be used to support the process of identifying suitable regions for solar energy projects. To the best of our knowledge, no study has addressed the problem of site evaluation for solar photovoltaic PV systems in the Riyadh region. Therefore, a spatial MCDA framework is proposed to perform a geospatial analysis of solar energy in the Riyadh region, which includes data collection, spatial analysis, a spatial decision support system and visualization. The methodology that was used to solve the site suitability problem is described. It involved the combination of a Geographical Information System (GIS) and the Analytic Hierarchy Process (GIS-AHP). The results show that the most suitable sites are in the north and northwest of the Riyadh region, with an area that represents 16,748 Km2 with an 80% suitability degree. In addition, it was proven that Afif is the largest suitable city. It has high solar radiation, at an average of 2.631687 MWh/m2/year, and low temperatures, at an average of 26.3 °C, as well as having flat areas with a slope under 5°. The results were validated using a sensitivity analysis model and also compared with those for ground-based stations.
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Biju, Barbara Pavani, André Nagalli, and Edilberto Nunes De Moura. "Geographic Information Systems supported by multi-criteria decision analysis to indicate potentially suitable areas for construction and demolition waste disposal." Revista Brasileira de Ciências Ambientais 56, no. 3 (August 17, 2021): 470–79. http://dx.doi.org/10.5327/z21769478947.
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In Brazil, the disposal of construction and demolition waste (CDW) quite often occurs in inadequate places, resulting in social, economic, and environmental problems. This reflects the need for selecting appropriate areas for the disposal of this type of waste. These areas must follow local standards and regulations to protect human health and the environment. Considering that, this study is intended to indicate potentially suitable areas for CDW landfill deployment, known as Class A landfill in Brazil, supported by a GIS-MCDA based model. The GIS-MCDA technique, used as a basic tool to identify potentially suitable areas, has several advantages, such as low cost, reduced spatial data subjectivity, and fast decision-making process. The place chosen for this study is the Urban Central Core of the Metropolitan Area of Curitiba. By integrating GIS with MCDA techniques in this research study, it was possible to indicate potentially suitable areas for CDW disposal in this region.
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Ali, Sk Ajim, and Ateeque Ahmad. "Spatial susceptibility analysis of vector-borne diseases in KMC using geospatial technique and MCDM approach." Modeling Earth Systems and Environment 5, no. 3 (April 9, 2019): 1135–59. http://dx.doi.org/10.1007/s40808-019-00586-y.
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Taha, Rania, Jörg Dietrich, Alexandra Dehnhardt, and Jesko Hirschfeld. "Scaling Effects in Spatial Multi-Criteria Decision Aggregation in Integrated River Basin Management." Water 11, no. 2 (February 20, 2019): 355. http://dx.doi.org/10.3390/w11020355.
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For river basin management plans (RBMPs), measures are aggregated from smaller spatial units (e.g., water bodies) to the catchment or basin scale. River basin management plans measures in integrated management are evaluated using multiple criteria, e.g., ecological and socio-economiccriteria, etc. Therefore, aggregation often combines spatial analysis and multi-criteria decision analysis (MCDA). Herein, we investigate: (1) the effect of applying different aggregation pathways on the outcome of the RBMP using the technique for order of preference by similarity to ideal solution (TOPSIS) as an MCDA method, (2) the scaling effects considering water body, sub-catchment, and river basin scales, and (3) the effect of using global and local criteria weighing on the final ranking of alternatives. We propose two approaches to aggregate ranks for the entire basin: using non-dominated alternatives only and using a normalized TOPSIS relative closeness value. The results show no variation in the final non-dominated alternative for both aggregation pathways. However, we note rank reversal among the dominated alternatives. These results suggest that scaling effects need to be considered in spatial MCDA.
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Yao, Muller Y., Koffi Kouamé, Germain M. Adja, Serge Loua, Jean K. Kouame, and Roger P. J. Jourda. "Spatial Characterization of Groundwater Potential in the Complex Basement Zone (Dabakala Department, North-Central Côte d’Ivoire): A Multi-Criteria Decision Analysis (MCD) Approach." European Journal of Environment and Earth Sciences 3, no. 4 (July 7, 2022): 7–14. http://dx.doi.org/10.24018/ejgeo.2022.3.4.273.
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The present hydrogeological study was carried out in the complex basement zone (Dabakala department, North-Central Côte d'Ivoire). Indeed, in this area, the population faces a real problem with the drinking water supply during the dry season. The aim of this study is to carry out a spatial characterization of groundwater potentialities in order to establish productive boreholes in the division. Ten decision criteria were developed and then aggregated. The methodology consisted in building a database based on these criteria, using remote sensing and GIS techniques. These criteria applied multi-criteria decision analysis (MCDA) using the Hierarchical Analytical Process (HAP) for their weighting. The resulting groundwater potential map was validated using the sensitivity trend curve technique. Ultimately, the results indicate that approximately 35% of the division’s area has strong to very strong groundwater potential.
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Fu, Yanli, Changfeng Jing, and Mingyi Du. "URBAN RAIN GAUGE SITING SELECTION BASED ON GIS-MULTICRITERIA ANALYSIS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B2 (June 7, 2016): 185–90. http://dx.doi.org/10.5194/isprs-archives-xli-b2-185-2016.
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With the increasingly rapid growth of urbanization and climate change, urban rainfall monitoring as well as urban waterlogging has widely been paid attention. In the light of conventional siting selection methods do not take into consideration of geographic surroundings and spatial-temporal scale for the urban rain gauge site selection, this paper primarily aims at finding the appropriate siting selection rules and methods for rain gauge in urban area. Additionally, for optimization gauge location, a spatial decision support system (DSS) aided by geographical information system (GIS) has been developed. In terms of a series of criteria, the rain gauge optimal site-search problem can be addressed by a multicriteria decision analysis (MCDA). A series of spatial analytical techniques are required for MCDA to identify the prospective sites. With the platform of GIS, using spatial kernel density analysis can reflect the population density; GIS buffer analysis is used to optimize the location with the rain gauge signal transmission character. Experiment results show that the rules and the proposed method are proper for the rain gauge site selection in urban areas, which is significant for the siting selection of urban hydrological facilities and infrastructure, such as water gauge.
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Fu, Yanli, Changfeng Jing, and Mingyi Du. "URBAN RAIN GAUGE SITING SELECTION BASED ON GIS-MULTICRITERIA ANALYSIS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B2 (June 7, 2016): 185–90. http://dx.doi.org/10.5194/isprsarchives-xli-b2-185-2016.
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With the increasingly rapid growth of urbanization and climate change, urban rainfall monitoring as well as urban waterlogging has widely been paid attention. In the light of conventional siting selection methods do not take into consideration of geographic surroundings and spatial-temporal scale for the urban rain gauge site selection, this paper primarily aims at finding the appropriate siting selection rules and methods for rain gauge in urban area. Additionally, for optimization gauge location, a spatial decision support system (DSS) aided by geographical information system (GIS) has been developed. In terms of a series of criteria, the rain gauge optimal site-search problem can be addressed by a multicriteria decision analysis (MCDA). A series of spatial analytical techniques are required for MCDA to identify the prospective sites. With the platform of GIS, using spatial kernel density analysis can reflect the population density; GIS buffer analysis is used to optimize the location with the rain gauge signal transmission character. Experiment results show that the rules and the proposed method are proper for the rain gauge site selection in urban areas, which is significant for the siting selection of urban hydrological facilities and infrastructure, such as water gauge.
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Abd El Karim, Ashraf, and Mohsen M. Awawdeh. "Integrating GIS Accessibility and Location-Allocation Models with Multicriteria Decision Analysis for Evaluating Quality of Life in Buraidah City, KSA." Sustainability 12, no. 4 (February 14, 2020): 1412. http://dx.doi.org/10.3390/su12041412.
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The present study was aimed at evaluating the quality of life in the districts of Buraidah city in the Kingdom of Saudi Arabia as part of the Kingdom’s Vision 2030, based on provided services in terms of distance and time parameters. This was achieved by integrating Geographic Information System (GIS)-based network analysis and multicriteria decision analysis (MCDA) techniques. The service area analysis technique of the GIS Network Analysis tools was applied to the available services in the districts of Buraidah city. Twelve services were investigated with regard to their coverage within 5, 10, and 15 minutes of travel time: universities, high schools, middle schools, elementary schools, hospitals, health centers, ambulance facilities, government services, religious services, security services, sports services, and recreational services. GIS-based multicriteria decision analysis (GIS-MCDA) was implemented in the study to obtain a spatial suitability map of the standard of living quality in the various districts in Buraidah city. The analytic hierarchy process (AHP) technique was used to determine the criteria weights. The location-allocation model was used in the study as well for suggestions of new service locations to improve the spatial distribution of services and enhance the quality of life in the districts. The results of the final suitability map to determine districts with the best standard of living according to the provided services show that the living standards in the city are very good, with very high and high levels in around 51 districts, representing 72.9% (449,235 people), and about 19 districts with moderate, low, and very low levels, representing 27.1% (56,765 people). Narrowing the quality of life gap and improving spatial planning requires correcting the current deficiency in services, which is estimated in this study to be 16 services: one high school, one elementary school, one middle school, two universities, one sports service, two security services, two courts, two hospitals, one health center, one park, and two ambulance facilities.
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Hsu, T. W., C. Y. Shin, S. H. Ou, and Y. T. Li. "Multi-Cross-Correlation Method in Particle Image Velocimetry." Journal of Mechanics 27, no. 3 (August 31, 2011): 365–77. http://dx.doi.org/10.1017/jmech.2011.39.
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ABSTRACTA multi-cross-correlation method (MCCM) was developed in a particle image velocimetry (PIV) auto-processing system to reduce spurious vectors and improve accuracy of measurements. This technique is an improvement based on conventional cross-correlation method (CCM). Four typical neighboring interrogation windows were specified to be overlapped and calculated by MCCM. A high cross-correlation value is obtained in which many particle images match up with their corresponding spatially shifted partners, and small cross-correlation peaks due to interference of noises during experiments are reduced. Several parameters such as out-of-plane motions, particle size, and seeding density are considered for checking both MCCM and conventional PIV algorithms. The examination gives authenticity to the merits of MCCM for avoiding particles loss or mistaken velocity vectors.
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Aşilioğlu, Fatma. "GISIMOS MCDA LAND SUITABILITY MODEL FOR ECOTOURISM DEVELOPMENT." Journal of Environmental Engineering and Landscape Management 29, no. 3 (June 17, 2021): 200–214. http://dx.doi.org/10.3846/jeelm.2021.15101.
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Ecotourism development planning is a multi-criteria process that generally requires spatial analysis. GISimos MCDA model developed by this study, was presented for the first time and applied to the Kalecik sub-province of Ankara, Turkey to determine the suitable areas and their suitability levels for ecotourism development. The model is based on the evaluation of sub-factors representing the topography, land cover, climate and sociocultural characteristics of the region, with the combination of GIS and the revised Simos procedure, one of the MCDA techniques. It included a series of processes such as determining the suitability rates and weights of sub-factors, calculating the Ecotourism Suitability Index values, and overlapping them using the WLC method. The resulting values were categorized as highly suitable, moderately suitable, marginally suitable, and not suitable areas. The results of this study and the method developed will be helpful for decision-makers and planners in the study area and similar regions.
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Xiong, Lei, Ge Sheng, Zi-Mu Fan, Hua Yang, Feng-Jang Hwang, and Bo-Wei Zhu. "Environmental Design Strategies to Decrease the Risk of Nosocomial Infection in Medical Buildings Using a Hybrid MCDM Model." Journal of Healthcare Engineering 2021 (June 15, 2021): 1–17. http://dx.doi.org/10.1155/2021/5534607.
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The prevention and control of nosocomial infection (NI) are becoming increasingly difficult, and its mechanism is becoming increasingly complex. A globally aging population means that an increasing proportion of patients have a susceptible constitution, and the frequent occurrence of severe infectious diseases has also led to an increase in the cost of prevention and control of NI. Medical buildings’ spatial environment design for the prevention of NI has been a hot subject of considerable research, but few previous studies have summarized the design criteria for a medical building environment to control the risk of NI. Thus, there is no suitable evaluation framework to determine whether the spatial environment of a medical building is capable of inhibiting the spread of NI. In the context of the global spread of COVID-19, it is necessary to evaluate the performance of the existing medical building environment in terms of inhibiting the spread of NI and to verify current environmental improvement strategies for the efficient and rational use of resources. This study determines the key design elements for the spatial environment of medical buildings, constructs an evaluation framework using exploratory factor analysis, verifies the complex dominant influence relationship, and prioritizes criteria in the evaluation framework using the decision-making trial and evaluation laboratory- (DEMATEL-) based analytical network process (ANP) (DANP). Using representative real cases, this study uses the technique for order preference by similarity to ideal solution (TOPSIS) to evaluate and analyze the performance with the aspiration level of reducing the NI risk. A continuous and systematic transformation design strategy for these real cases is proposed. The main contributions of this study include the following: (1) it creates a systematic framework that allows hospital decision-makers to evaluate the spatial environment of medical buildings; (2) it provides a reference for making design decisions to improve the current situation using the results of a performance evaluation; (3) it draws an influential network relation map (INRM) and the training of influence weights (IWs) for criteria. The sources of practical problems can be identified by the proposed evaluation framework, and the corresponding strategy can be proposed to avoid the waste of resources for the prevention of epidemics.
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BİLGİLİOĞLU, Süleyman Sefa, and Cemil GEZGİN. "Suitable Site Selection for Landfill with the Integration of Geographic Information Systems (GIS) and Fuzzy Analytical Hierarchy Process (FAHP) Methods in Nevşehir." Afyon Kocatepe University Journal of Sciences and Engineering 22, no. 4 (August 31, 2022): 836–49. http://dx.doi.org/10.35414/akufemubid.1105426.
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Landfilling is the most ordinary technique used for the disposal of solid waste. Solid waste management is an essential section of city planning due to its immense effect on the economy, ecology and environment of the region. With the increase in urbanization and the desire to live in cities, more waste is produced and unfortunately the waste problem is getting worse rapidly. In this context, the construction of new repository areas in an optimal location is one of the most essential issues of solid waste management. The suitability of a landfill site is often a complex process and relies on various criteria and regulations, due to the simultaneous effects of social, environmental and technical criteria. Geographic Information Systems (GIS)-based Multi-Criteria Decision Making (MCDM) is an important method for decision makers in solving spatial problems such as appropriate site selection. In this study, Fuzzy Analytical Hierarchy Process (FAHP), one of the GIS and MCDM methods, were used in order to select the appropriate site for the solid waste landfill in Nevşehir province. For this purpose, exclusion and evaluation criteria were determined by conducting literature studies and taking expert opinions. By calculating the criterion importance levels with FAHP, a suitability map was produced for the solid waste landfill and up to nine areas were found suitable for storage.
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Lowot, Musa W., and Augustina C. Alexander. "Spatial Analysis of Groundwater Potential: A first hand Approach towards Groundwater Development in Moroto District, Uganda." Tanzania Journal of Science 48, no. 4 (December 31, 2022): 962–72. http://dx.doi.org/10.4314/tjs.v48i4.21.
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Groundwater is a vital resource that helps mankind and development. However, in Moroto District challenges of groundwater development has increased arising from changes in rainfall patterns coupled with high abstraction from population increase. In this study, the spatial variability of groundwater potential was assessed to develop a tool that will aid decision on groundwater potential sites selection for groundwater development/exploration. The study utilized an integrated technique and tools such as Remote Sensing (RS), Geographic Information System (GIS) and Multi Criteria Decision Analysis (MCDA) in analysis and delineation of potential areas for successful groundwater development. The generated map through weighted overlay of thematic layers (slope, soil, lithology, rainfall, land use and land cover) produced five categories of potential zones indicating 90% (i.e., 35% very high, 40% high and 15% moderate) of the study area to be suitable for groundwater development and only 10% (i.e., 2% poor and 8% very poor) exists as poor groundwater potential zones. Maps produced from this study can hence be used to identify appropriate sites for groundwater development, and therefore minimizing unsuccessful boreholes development.
Keywords: GIS; Groundwater Development; Groundwater Potential; MCDA; Spatial Analysis.
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Costa, Evaldo, Arthur Paiva, Julia Seixas, Gustavo Costa, Patrícia Baptista, and Brian Ó. Gallachóir. "Spatial Planning of Electric Vehicle Infrastructure for Belo Horizonte, Brazil." Journal of Advanced Transportation 2018 (December 19, 2018): 1–16. http://dx.doi.org/10.1155/2018/8923245.
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In pursuit of a more sustainable transportation system, electric vehicles (EVs) have the potential to play a fundamental role due to their improved efficiency and lower emissions. The absence of an adequate electric vehicle supply equipment (EVSE) network has been one of the major obstacles for the mass adoption of EV, in large municipalities of developing countries. This is the case in Belo Horizonte (BH), Brazil, which also has a high motorization rate (7 light-duty vehicles per 10 inhabitants). The purpose of this study is to measure and identify the optimal locations for EVSE according to selected criteria to meet the needs of light-duty electric vehicles (LDEV) corresponding to a penetration of 1% by 2025 in the municipality of BH. The study highlights the most important attributes that need to be considered for the installation of an EVSE network in an urban space for a developing country. Multi-Criteria Decision Making (MCDM), the Weighted Linear Combination (WLC) method, and the Analytical Hierarchy Process (AHP) technique based on the inputs from a group of Brazilian electrical mobility specialists, coupled with a Geographic Information System (GIS) modeling tool, were used for this study. The results revealed that around 1,200 EVSE units are needed, with a large concentration of EVSE in a small region. We also illustrate where stakeholders should focus their attention for the successful promotion of EV. The development methodology has the potential to be applied in other future EVSE development projects.
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Giuffrida, Nadia. "A public participatory GIS and multi criteria decision analysis framework for the evaluation of transport scenarios." Bullettin of the Gioenia Academy of Natural Sciences of Catania 53, no. 383 (November 17, 2020): MISC6—MISC7. http://dx.doi.org/10.35352/gioenia.v53i383.92.
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The decision-making process of transport projects is very complex, especially for public administrations which have to take into account often incomparable criteria of judgment. In addition, in order to achieve a good social sharing and robustness of the decision, policy makers have to include in the process not only the transport planning experts but also the stakeholders of the community. The purpose of this study is to propose an evaluation framework to support the decision making process, able to allow public participation in the assessment of transport planning and design scenarios while, at the same time, ensuring a high level of technical quality of the final decision. The designed framework includes a method to analyze monetary and non-monetary parameters, easily understandable for all decision makers. It is based on the application of Multi Criteria Decision Analysis (MCDA) techniques, an evaluation process that can take into account different quantitative and qualitative objectives and criteria; in order to favor public participation, the implementation of this technique takes advantage of Geographic Information System (GIS) for its ability to easily represent the impact of spatially based alternative project scenarios. The analysis of several case studies on transport planning and design scenarios allowed to assess the level of implementation of the three main ingredients of the framework: MCDA, GIS and public participation.
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Alizadeh, Mohsen, Mazlan Hashim, Esmaeil Alizadeh, Himan Shahabi, Mohammad Karami, Amin Beiranvand Pour, Biswajeet Pradhan, and Hassan Zabihi. "Multi-Criteria Decision Making (MCDM) Model for Seismic Vulnerability Assessment (SVA) of Urban Residential Buildings." ISPRS International Journal of Geo-Information 7, no. 11 (November 14, 2018): 444. http://dx.doi.org/10.3390/ijgi7110444.
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Earthquakes are among the most catastrophic natural geo-hazards worldwide and endanger numerous lives annually. Therefore, it is vital to evaluate seismic vulnerability beforehand to decrease future fatalities. The aim of this research is to assess the seismic vulnerability of residential houses in an urban region on the basis of the Multi-Criteria Decision Making (MCDM) model, including the analytic hierarchy process (AHP) and geographical information system (GIS). Tabriz city located adjacent to the North Tabriz Fault (NTF) in North-West Iran was selected as a case study. The NTF is one of the major seismogenic faults in the north-western part of Iran. First, several parameters such as distance to fault, percent of slope, and geology layers were used to develop a geotechnical map. In addition, the structural construction materials, building materials, size of building blocks, quality of buildings and buildings-floors were used as key factors impacting on the building’s structural vulnerability in residential areas. Subsequently, the AHP technique was adopted to measure the priority ranking, criteria weight (layers), and alternatives (classes) of every criterion through pair-wise comparison at all levels. Lastly, the layers of geotechnical and spatial structures were superimposed to design the seismic vulnerability map of buildings in the residential area of Tabriz city. The results showed that South and Southeast areas of Tabriz city exhibit low to moderate vulnerability, while some regions of the north-eastern area are under severe vulnerability conditions. In conclusion, the suggested approach offers a practical and effective evaluation of Seismic Vulnerability Assessment (SVA) and provides valuable information that could assist urban planners during mitigation and preparatory phases of less examined areas in many other regions around the world.
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Al-Ghobari, Hussein, and Ahmed Z. Dewidar. "Integrating GIS-Based MCDA Techniques and the SCS-CN Method for Identifying Potential Zones for Rainwater Harvesting in a Semi-Arid Area." Water 13, no. 5 (March 5, 2021): 704. http://dx.doi.org/10.3390/w13050704.
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An increasing scarcity of water, as well as rapid global climate change, requires more effective water conservation alternatives. One promising alternative is rainwater harvesting (RWH). Nevertheless, the evaluation of RWH potential together with the selection of appropriate sites for RWH structures is significantly difficult for the water managers. This study deals with this difficulty by identifying RWH potential areas and sites for RWH structures utilizing geospatial and multi-criteria decision analysis (MCDA) techniques. The conventional data and remote sensing data were employed to set up needed thematic layers using ArcGIS software. The soil conservation service curve number (SCS-CN) method was used to determine surface runoff, centered on which yearly runoff potential map was produced in the ArcGIS environment. Thematic layers such as drainage density, slope, land use/cover, and runoff were allotted appropriate weights to produced RWH potential areas and zones appropriate for RWH structures maps of the study location. Results analysis revealed that the outcomes of the spatial allocation of yearly surface runoff depth ranging from 83 to 295 mm. Moreover, RWH potential areas results showed that the study areas can be categorized into three RWH potential areas: (a) low suitability, (b) medium suitability, and (c) high suitability. Nearly 40% of the watershed zone falls within medium and high suitability RWH potential areas. It is deduced that the integrated MCDA and geospatial techniques provide a valuable and formidable resource for the strategizing of RWH within the study zones.
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Navale, Sanjay, and Vijay Bhagat. "Detection and Delineation of Potential Areas for Tourism Activities in Coastal Zone of Ratnagiri District, Maharashtra (India)." Journal of Geographical Studies 5, no. 2 (December 30, 2021): 79–113. http://dx.doi.org/10.21523/gcj5.21050203.
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Tourism is a device of economic development in developed, developing, and even in underdeveloped countries. The AHP based MCDA techniques used for detection and delineation of the tourism potential zones in the coastal area of Ratnagiri district in Maharashtra (India). The conventional and satellite data viz. ASTER data has been used for spatial analysis in GIS software. Seacoast, elevation, slope, river, LULC, available amenities, accessibility and connectivity, cultural and historical places, and density of settlements used as the criterions for detection of potential zones for tourism activities. The experts’ opinions, literature survey and fieldwork used as the source of information for the selection of criterions and determination of ranks. The weighted overlay technique used to find the comparative levels of tourism potentials: very high, high, moderate and less potentials for tourism. About 13% of TGA shows comparatively very high tourism potential, 25.80% shows high, 54.62 % shows moderate, and 6.57 % shows less tourism potential. The overall accuracy of the categorized map estimated about 89.60%. The thematic maps viz. amenities and settlement were processed using inverse distance weighted (IWD) interpolation technique. Therefore, some areas from the category, ‘high potential’ merged in the category, ‘moderate potential’ and reduced the producer’s accuracy of the classified map. The sandy beaches, lowland area with a gentle slope, river landscape features, road network, cultural and historical places, ideal size of settlements and number of amenities are attractions of tourists in the region. The technique used in this study can be an effective apparatus for precise analysis of site suitability for tourism activities.
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Dissanayake, DMSLB, Takehiro Morimoto, Yuji Murayama, Manjula Ranagalage, and ENC Perera. "Analysis of Life Quality in a Tropical Mountain City Using a Multi-Criteria Geospatial Technique: A Case Study of Kandy City, Sri Lanka." Sustainability 12, no. 7 (April 6, 2020): 2918. http://dx.doi.org/10.3390/su12072918.
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The blooming of urban expansion has led to the improvement of urban life, but some of the negative externalities have affected the life quality of urban dwellers, both directly and indirectly. As a result of this, research related to the quality of life has gained much attention among multidisciplinary researchers around the world. A number of attempts have been made by previous researchers to identify, assess, quantify, and map quality of life or well-being under various kinds of perspectives. The objectives of this research were to create a life quality index (LQI) and identify the spatial distribution pattern of LQI in Kandy City, Sri Lanka. Multiple factors were decomposed, a hierarchy was constructed by the multi-criteria decision making (MCDM) method, and 13 factors were selected under two main criteria—environmental and socioeconomic. Pairwise comparison matrices were created, and the weight of each factor was determined by the analytic hierarchy process (AHP). Finally, gradient analysis was employed to examine the spatial distribution pattern of LQI from the city center to the periphery. The results show that socioeconomic factors affect the quality of life more strongly than environmental factors, and the most significant factor is transportation. The highest life quality zones (26% of the total area) were distributed around the city center, while the lowest zones represented only 9% of the whole area. As shown in the gradient analysis, more than 50% of the land in the first five kilometers from the city center comes under the highest life quality zone. This research will provide guidance for the residents and respective administrative bodies to make Kandy City a livable city. It the constructed model can be applied to any geographical area by conducting necessary data calibration.
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Mishra, Rajesh Kumar, Sharad Tiwari, and Rekha Agarwal. "Role and potential of decision support systems in forestry." Plants and Environment 2, no. 3 (September 30, 2020): 108–12. http://dx.doi.org/10.22271/2582-3744.2020.sep.108.
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Decision Support Systems (DSS) are essential tools for forest management practitioners to help take account of the many environmental, economic, administrative, legal and social aspects in forest management. This paper is concerned with the technique to develop DSS for forest management system to evaluate models and methods considering all the important factors to categorize the problem. The problem is based on temporal and spatial parameters, number of objectives, decision makers and goods and services. Some of these problem dimensions are inter-related, and we also found a significant relationship between various methods and problem dimensions, all of which have been analysed using contingency tables. The results showed that 63% of forest DSS use simulation modeling methods and these are particularly related to the spatial context and spatial scale and the number of people involved in taking a decision. The analysis showed how closely Multiple Criteria Decision Making is linked to problem types involving the consideration of the number of objectives, also with the goods and services. On the other hand, there was no significant relationship between optimization and statistical methods and problem dimensions, although they have been applied to approximately 60% and 16% of problems solved by DSS for forest management, respectively. Metaheuristics and spatial statistical methods are promising new approaches to deal with certain problem formulations and data sources. Nine out of ten DSS used an associated information system, but the availability and quality of data continue to be an important constraining issue, and one that could cause considerable difficulty in implementing DSS in practice. Very often DSS is used largely based to study market economy. The results suggest a strong need to improve the capabilities of DSS in this regard, developing and applying MCDM models and incorporating them in the design of DSS for forest management in coming years.
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Alhammad, Abdulaziz, Qian (Chayn) Sun, and Yaguang Tao. "Optimal Solar Plant Site Identification Using GIS and Remote Sensing: Framework and Case Study." Energies 15, no. 1 (January 3, 2022): 312. http://dx.doi.org/10.3390/en15010312.
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Many countries have set a goal for a carbon neutral future, and the adoption of solar energy as an alternative energy source to fossil fuel is one of the major measures planned. Yet not all locations are equally suitable for solar energy generation. This is due to uneven solar radiation distribution as well as various environmental factors. A number of studies in the literature have used multicriteria decision analysis (MCDA) to determine the most suitable places to build solar power plants. To the best of our knowledge, no study has addressed the subject of optimal solar plant site identification for the Al-Qassim region, although developing renewable energy in Saudi Arabia has been put on the agenda. This paper developed a spatial MCDA framework catering to the characteristics of the Al-Qassim region. The framework adopts several tools used in Geographic Information Systems (GIS), such as Random Forest (RF) raster classification and model builder. The framework aims to ascertain the ideal sites for solar power plants in the Al-Qassim region in terms of the amount of potential photovoltaic electricity production (PVOUT) that could be produced from solar energy. For that, a combination of GIS and Analytical Hierarchy Process (AHP) techniques were employed to determine five sub-criteria weights (Slope, Global Horizontal Irradiance (GHI), proximity to roads, proximity to residential areas, proximity to powerlines) before performing spatial MCDA. The result showed that ‘the most suitable’ and ‘suitable’ areas for the establishment of solar plants are in the south and southwest of the region, representing about 17.53% of the study area. The ‘unsuitable’ areas account for about 10.17% of the total study area, which is mainly concentrated in the northern part. The rest of the region is further classified into ‘moderate’ and ‘restricted’ areas, which account for 46.42% and 25.88%, respectively. The most suitable area for potential solar energy, yields approximately 1905 Kwh/Kwp in terms of PVOUT. The proposed framework also has the potential to be applied to other regions nationally and internationally. This work contributes a reproducible GIS workflow for a low-cost but accurate adoption of a solar energy plan to achieve sustainable development goals.
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Galik, Anna, Monika Bąk, Katarzyna Bałandynowicz-Panfil, and Giuseppe T. Cirella. "Evaluating Labour Market Flexibility Using the TOPSIS Method: Sustainable Industrial Relations." Sustainability 14, no. 1 (January 4, 2022): 526. http://dx.doi.org/10.3390/su14010526.
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This study evaluates labour market flexibility using the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), a multi-criteria decision analysis (MCDA) method. TOPSIS is employed by comparing spatial (i.e., different countries) and temporal (i.e., long-time horizon) terms. Sustainable industrial relations processes are considered in shaping the flexibility of the labour market in 15 European Union Member States from 2009 to 2018. Countries are grouped into classes to provide a basis for benchmarking results against social and employment policies implemented at the national level. A five-step quantitative MCDA method is formulated using published data from the Organisation for Economic Co-operation and Development. The results indicate that the TOPSIS method is an appropriate approach for measuring labour market flexibility internationally. Moreover, in relation to workforce phenomena, the findings show that the method offers the possibility of examining the impact of particular factors related to social and employment policies of a country in terms of sustainable development and socioeconomic growth. The lack of precision tools to forecast the development of national and transnational labour markets—particularly during the COVID-19 era—highlights the importance of such a method for workforce planners and policymakers. Developing sustainable industrial relations in terms of associated national externalities is the motivation of the research.
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Saran, S., and K. V. Ramana. "SITE SUITABILITY ANALYSIS FOR INDUSTRIES USING GIS AND MULTI CRITERIA DECISION MAKING." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences IV-5 (November 15, 2018): 447–54. http://dx.doi.org/10.5194/isprs-annals-iv-5-447-2018.
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<p><strong>Abstract.</strong> Developing countries have to be very cautious in utilizing the land as they affect the food security, cause damage to environment and an ecological imbalance might be created in the process of establishing industries to raise the standard of living of the people from poverty. India, as a developing nation with sufficient amount of arable land at present is producing surplus food which is sufficient for all the population, in the recent decades loosing productive agricultural land without proper scientific solution for industries. This is a major concern because it causes not only food scarcity but dependency on the other nations even though we have lot of industries. We need to maintain a balance between Agriculture and manufacturing sectors to have smooth run of the country’s economy. The purpose of the study is to assess the land use changes in the areas for recent years which have potential for industrial establishment through land suitability analysis (LSA) to emphasize both agriculture and industries with sustainable development. Geographic information Systems (GIS) and Multi Criteria Decision Making (MCDM) are combined to distinctly identify the suitable zones for industries. Six criteria in Analytical hierarchy Process (AHP) and nine criteria in Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) are evaluated by spatial analysis using ArcGIS software. Considerable amount of productive agricultural land is diverted to non agricultural purposes during last 12 years i.e., from 2004&ndash;2016, which is at first taken for industrial establishment. Results obtained by the methodology we followed have given considerable accuracy by cross checking the previously established industries with suitability regions. Thus GIS and MCDM can assist the policy makers and planning officials to get a better overview with the resources they possess to carry forward with less damage to environment and agricultural land.</p>
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Antognelli, Sara, and Marco Vizzari. "Assessing Ecosystem and Urban Services for Landscape Suitability Mapping." Applied Sciences 11, no. 17 (September 5, 2021): 8232. http://dx.doi.org/10.3390/app11178232.
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Ecosystem services (ES) and urban services (US) can comparably improve human well-being. Models for integrating ES and US with unexpressed and objective needs of defined groups of stakeholders may prove helpful for supporting decisions in landscape planning and management. In fact, they could be applied for highlighting landscape areas with different characteristics in terms of services provided. From this base, a suitability spatial assessment model (SUSAM) was developed and applied in a study area considering different verisimilar scenarios that policy makers could analyse. Each scenario is based on the prioritization of a set of services considering a defined group of stakeholders. Consistent and comparable ES and US indices of spatial benefiting areas (SBA) of services were calculated using GIS spatialization techniques. These indices were aggregated hierarchically with the relevance of services according to a spatial multicriteria decision analysis (S-MCDA). Results include maps for each scenario showing detailed spatial indices of suitability that integrate the local availability of SBA of ES and US, along with their relevance. The results were compared with known landscape classes identified in previous studies, which made it possible to interpret the spatial variation of suitability in the light of known landscape features. A complete sensitivity analysis was performed to test the sensitiveness of the model’s outputs to variations of judgements and their resistance to the indicators’ variation. The application of the model demonstrated its effectiveness in a landscape suitability assessment. At the same time, the sensitivity analysis and helping to understand the model behaviour in the different landscape classes also suggested possible solutions for simplifying the whole methodology.
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Silwal, R., A. Roy, H. Karnatak, and R. B. Thapa. "SPATIAL BIODIVERSITY MODEL TO CHARACTERIZE BIOLOGICAL DIVERSITY USING R STATISTICAL COMPUTING ENVIRONMENT FOR NEPAL HIMALAYA." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-5/W3 (December 5, 2019): 121–28. http://dx.doi.org/10.5194/isprs-archives-xlii-5-w3-121-2019.
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Abstract. Biodiversity characters of the landscape provide basis of prioritizing the sites in conservation effort. There is an urgent need for rapid assessment of existing biodiversity using state-of-art tools and technologies at large scale. The purpose of the study is to model and prioritize biological richness based on multi-criteria decision analysis (MCDA) for conservation priority and management planning. Vegetation type map for year 2017 was developed for generation of various landscape indices e.g. fragmentation, patchiness, porosity, juxtaposition etc. The Spatial Biodiversity Model (SBM) prepared for similar landscape of Uttarakhanda, India which is scale, resolution and location independent for spatial biodiversity richness modelling was executed in R programming platform. Satellite data, non-spatial data and ancillary data were used to generate Biological Richness (BR) map which is categorized into 4 classes as low, moderate, high and very high (biodiversity rich) including non-forest area to quantify BR area. The result shows that largest area is under very high biological richness class followed by high, moderate and low BR area. Overall accuracy and Kappa Statistics of LULC/vegetation type classification is 82.61% and 0.8013 respectively. The spatial regression analysis for final output validation has been made with ground based species diversity data where R2 value for Shannon-Wiener index and Margalef’s diversity index are 0.64 and 0.56 respectively. The results also re-emphasize the role of geospatial techniques in the quick appraisal of predicting biological richness. The study result is applicable in systematic inventory of biological resources, land use planning, conservation prioritization and policy support.
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Chiu, Yie-Ru, Kamaleddin Aghaloo, and Babak Mohammadi. "Incorporating Rainwater Harvesting Systems in Iran’s Potable Water-Saving Scheme by Using a GIS-Simulation Based Decision Support System." Water 12, no. 3 (March 9, 2020): 752. http://dx.doi.org/10.3390/w12030752.
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Rainwater harvesting systems (RWHSs) have been accepted as a simple and effective approach to ease the worsening of urban water stress. However, in arid and semiarid regions, a comprehensive method for promoting domestic RWHSs in a large-scale water-saving scheme that incorporates water consumption reducing equipment (WCRE) and gray water reuse (GWR), has not been well developed. For this, based on the case study of Guilan Province, Iran, this study addressed the temporal-spatial complex of rainfall and proposed a GIS-simulation-based decision support system (DSS). Herein, two scenarios, i.e., the typical RWHS and the modified RWHS for arid areas, were tested; and the associated economic analysis was performed and compared with WCRE and GWR. Moreover, for larger-scale implementation, the multiple criteria decision making (MCDM) technique was further applied to address the social-environmental complexity of these water-saving methods. Guilan Province has thereby been classified into three priority levels, providing a straightforward understanding of how to promote the large-scale water-saving scheme. Compared with the traditional generalized method, sensitivity analysis verified that this DSS enhanced the information value. Hence, the DSS that provides more holistic and comprehensive support has been identified as a useful tool to ease the threat of urban water stress.
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Akyol, Erdal, Mutlu Alkan, Ali Kaya, Suat Tasdelen, and Ali Aydin. "Environmental Urbanization Assessment Using GIS and Multicriteria Decision Analysis: A Case Study for Denizli (Turkey) Municipal Area." Advances in Civil Engineering 2018 (2018): 1–7. http://dx.doi.org/10.1155/2018/6915938.
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In recent years, life quality of the urban areas is a growing interest of civil engineering. Environmental quality is essential to display the position of sustainable development and asserts the corresponding countermeasures to the protection of environment. Urban environmental quality involves multidisciplinary parameters and difficulties to be analyzed. The problem is not only complex but also involves many uncertainties, and decision-making on these issues is a challenging problem which contains many parameters and alternatives inherently. Multicriteria decision analysis (MCDA) is a very prepotent technique to solve that sort of problems, and it guides the users confidence by synthesizing that information. Environmental concerns frequently contain spatial information. Spatial multicriteria decision analysis (SMCDA) that includes Geographic Information System (GIS) is efficient to tackle that type of problems. This study has employed some geographic and urbanization parameters to assess the environmental urbanization quality used by those methods. The study area has been described in five categories: very favorable, favorable, moderate, unfavorable, and very unfavorable. The results are momentous to see the current situation, and they could help to mitigate the related concerns. The study proves that the SMCDA descriptions match the environmental quality perception in the city.
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Godlewska, Joanna, and Edyta Sidorczuk-Pietraszko. "Taxonomic Assessment of Transition to the Green Economy in Polish Regions." Sustainability 11, no. 18 (September 18, 2019): 5098. http://dx.doi.org/10.3390/su11185098.
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In this paper, an aggregate indicator of a regional green economy (Regional Green Economy Index—RGEI) was proposed and applied to assess the level of green economy in Polish regions and its changes in the period 2004–2016. The TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) method was applied, which is one of the multi-criteria decision making methods (MCDM), widely used to assess the spatial diversity of socio-economic phenomena. Common reference values (ideal and anti-ideal solution) were used for variables for the entire study period. It allowed not only for creating a ranking of regions, but to assess progress towards the green economy as well. It was found that all regions of Poland made progress in this respect. Most importantly, the regions ranked the worst before Poland’s accession to the European Union, made substantial progress. It was stated as well that none among the studied regions had high values of all variables included in the aggregate index. The maximum value of the RGEI index was about 0.5, while the index range is [0,1]. Additionally, an important finding was the fact that the weights of all diagnostic variables obtained using information entropy method were about equal, which confirms the approach of researchers and institutions who do not use weighting in aggregate indicators for well-being or sustainable development—which means implicitly using equal weights.
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Arabameri, Cerda, Rodrigo-Comino, Pradhan, Sohrabi, Blaschke, and Tien Bui. "Proposing a Novel Predictive Technique for Gully Erosion Susceptibility Mapping in Arid and Semi-arid Regions (Iran)." Remote Sensing 11, no. 21 (November 2, 2019): 2577. http://dx.doi.org/10.3390/rs11212577.
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Gully erosion is considered to be one of the main causes of land degradation in arid and semi-arid territories around the world. In this research, gully erosion susceptibility mapping was carried out in Semnan province (Iran) as a case study in which we tested the efficiency of the index of entropy (IoE), the Vlse Kriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method, and their combination. Remote sensing and geographic information system (GIS) were used to reduce the time and costs needed for rapid assessment of gully erosion. Firstly, a gully erosion inventory map (GEIM) with 206 gully locations was obtained from various sources and randomly divided into two groups: A training dataset (70% of the data) and a validation dataset (30% of the data). Fifteen gully-related conditioning factors (GRCFs) including elevation, slope, aspect, plan curvature, stream power index, topographical wetness index, rainfall, soil type, drainage density, distance to river, distance to road, distance to fault, lithology, land use/land cover, and soil type, were used for modeling. The advanced land observing satellite (ALOS) digital elevation model with a spatial resolution of 30 m was used for the extraction of the above-mentioned topographic factors. The tolerance (TOL) and variance inflation factor (VIF) were also included for checking the multicollinearity among the GRCFs. Based on IoE, we concluded that soil type, lithology, and elevation were the most significant in terms of gully formation. Validation results using the area under the receiver operating characteristic curve (AUROC) showed that IoE (0.941) reached a higher prediction accuracy than VIKOR (0.857) and VIKOR-IoE (0.868). Based on our results, the combination of statistical (IoE) models along with remote sensing and GIS can convert the multi-criteria decision-making (MCDM) models into efficient and powerful tools for gully erosion prediction. We strongly suggest that decision-makers and managers should use these kinds of results to develop more consistent solutions to achieve sustainable development on degraded lands such as in the Semnan province.
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Chae, Ji Seong, Chang Hyun Choi, Jeong Hoon Oh, Young Tae Chae, Jae-Weon Jeong, and Dongkyu Lee. "Urban Public Service Analysis by GIS-MCDA for Sustainable Redevelopment: A Case Study of a Megacity in Korea." Sustainability 13, no. 3 (January 31, 2021): 1472. http://dx.doi.org/10.3390/su13031472.
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With the rapid industrialization and urbanization, suburban areas have been developed to accommodate the sudden demand of the population. However, recent problems such as low fertility and aging induces urban shrinkage by reducing the urban population and the economy in old areas around the suburbs. As urban shrinkage causes inequality among residents in terms of the opportunities to access public services, the enhancement of the accessibility of public services is crucial to achieve inclusive growth. This paper proposes a framework for supplying public services based on the transit-oriented development (TOD) concept with geographic information system (GIS) analysis technique. A total of 24 indices, 4 criteria for 6 public services, are measured and weighted by the entropy method to find vulnerable residential buildings with a poor environment in Jung-nang district, Seoul. With a spatial analysis based on this weight value of residential buildings and the TOD concept, old commercial buildings are selected as candidate buildings for public services. According to the derived results, one candidate building as a public service can improve the environment of 3% to 8% of vulnerable residential buildings. The proposed decision-making methods can provide a valuable reference for selecting the location of public services by computational analysis with GIS.
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Aldhshan, Shaban R. S., Khairul Nizam Abdul Maulud, Wan Shafrina Wan Mohd Jaafar, Othman A. Karim, and Biswajeet Pradhan. "Energy Consumption and Spatial Assessment of Renewable Energy Penetration and Building Energy Efficiency in Malaysia: A Review." Sustainability 13, no. 16 (August 18, 2021): 9244. http://dx.doi.org/10.3390/su13169244.
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The development of sustainable energy systems is very important to addressing the economic, environmental, and social pressures of the energy sector. Globally, buildings consume up to 40% of the world’s total energy. By 2030, it is expected to increase to 50%. Therefore, the world is facing a great challenge to overcome these problems related to global energy production. Malaysia is one of the top consumers of primary energy in Asia. In 2018, primary energy consumption for Malaysia was 3.79 quadrillion btu at an average annual rate of 4.58%. In this paper, we have carried out a detailed literature review on several previous studies of energy consumption in the world, especially in Malaysia, and how geographical information system (GIS) methods have been used for the spatial assessment of energy efficiency. Indeed, strategies of energy efficiency are essential in energy policy that could be created using various approaches used for energy savings in buildings. The findings of this review reveal that, for estimating energy consumption, exploring renewable energy sources, and investigating solar radiation, several geographic information system techniques such as multiple criteria decision analysis (MCDA), machine learning (ML), and deep learning (DL) are mainly utilized. The result indicates that the fuzzy DS method can more reliably determine the optimal PV farm locations. The 3D models are also regarded as an effective tool for estimating solar radiation, since this method generates a 3D model exportable to software tools. In addition, GIS and 3D can contribute to several purposes, such as sunlight access to buildings in urban areas, city growth prediction models and analysis of the habitability of public places.
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Assumma, Vanessa, Marta Bottero, Alessio Ishizaka, and Menelaos Tasiou. "Group Analytic Hierarchy Process Sorting II Method: An Application to Evaluate the Economic Value of a Wine Region Landscape." Environmental Modeling & Assessment 26, no. 3 (April 17, 2021): 355–69. http://dx.doi.org/10.1007/s10666-020-09744-4.
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AbstractIn the ongoing context of climate change, there is an increasing need to support decision-making processes in the domain of landscape planning and management. Suitable evaluation techniques are needed to take into account the interests of actors and stakeholders in shared policy decisions. An important methodological contribution to the field is given by the Multicriteria Decision Analysis (MCDA), due to its ability to combine multiple aspects of a decision problem with the values and opinions expressed by different Decision Makers. The present paper develops the “Group Analytic Hierarchy Process Sorting II method” (GAHPSort II), which aims to sort a group of municipalities included in the UNESCO site “Vineyard Landscape of Piedmont: Langhe-Roero, and Monferrato” (Italy) according to the economic attractiveness of the landscape. Extending the previous versions AHPSort I, AHPSort II and GAHPSort, the GAHPSort II optimizes multi-stakeholder evaluations on large databases by reducing the number of comparisons. Moreover, the GAHPSort II method is proposed as a novel spatial decision support system because it combines a set of economic indicators for landscape and GIS methods for aiding the Decision Makers to better understand the case study and to support the definition and localization of policies and strategies of landscape planning and management.
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Abastante, Francesca, Caterina Caprioli, and Marika Gaballo. "The Economic Evaluation of Projects as a Structuring Discipline of Learning Processes to Support Decision-Making in Sustainable Urban Transformations." International Journal of Sustainable Development and Planning 17, no. 4 (July 27, 2022): 1297–307. http://dx.doi.org/10.18280/ijsdp.170427.
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This paper is based on the following research questions: i) In which way could the discipline Economic Evaluation of Projects contribute to conveying the sustainability concept in urban settings among master’s degree students? What are the methods/techniques that can support decision processes of sustainable urban transformation? In response to the two research questions, the paper proposes a multi-methodological framework as a design tool for students (future professionals) aimed at representing the decision problem from a sustainable planning perspective. Through a Problem-Based Learning approach based on a case study, the proposed framework considers: SWOT Analysis, Stakeholder Analysis (SA), Multicriteria Analysis (MCDA), Cash Flow Analysis (CFA), and the application of the Neighborhood Sustainability Assessment Tools (NSATools). The multi-methodological framework has been applied to an experimental teaching case study as part of the Economic Evaluation of Projects module demonstrating its effectiveness in terms of sustainable spatial planning and structuring of the decision process from a multi-actor perspective. Future directions of the research are aimed at tackling two major limitations of the multi-methodological framework as the need to closely reflect a real decision process through an iterative framework and the sometimes hard interpretation of some elements of urban sustainability.
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Berreghioua, Fatima, and Boudjamea Khalfallah. "Towards sustainable tourism panning in Bou Saâda, Algeria." Glasnik Srpskog geografskog drustva 102, no. 2 (2022): 267–82. http://dx.doi.org/10.2298/gsgd2202267b.
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The city of Bou Sa?da is one of the Algerian cities that have diverse tourism resources, but it has not been adopted as a premier tourist spot nor has it benefited from the tourism programs established within the national strategy for sustainable tourism development for Horizons 2030, which made the tourism weak compared to other Algerian regions that have similar tourism elements. This study aims to evaluate the existing tourism strategy to address the shortcomings and provide solutions by focusing on four variables: tourist destination, tourism industry, the tourist market, and actors in tourism. We have relied on the following techniques: SWOT analysis to identify the strengths, weaknesses, opportunities, and threats of the tourism sector in Bou Sa?da, MCDA Analysis using AHP for spatial planning for the future tourism industry, and a questionnaire form distributed to the residents, the tourists and the experts to take their suggestions and use them in guiding the tourism planning process. The results of the study proved that there is a weakness in the tourism planning process in the city of Bou Sa?da, which negatively affects the tourism traffic, that is still weak compared to the qualifications it has, which if exploited according to a wellthought-out strategy, the city will become a targeted tourist destination.
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Pandey, Varsha, and Prashant Srivastava. "Integration of Microwave and Optical/Infrared Derived Datasets for a Drought Hazard Inventory in a Sub-Tropical Region of India." Remote Sensing 11, no. 4 (February 20, 2019): 439. http://dx.doi.org/10.3390/rs11040439.
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Drought is an intricate phenomenon assessed by analyzing several hydro-meteorological factors such as rainfall, soil moisture, temperature, evapotranspiration, vegetation cover, etc. For effective drought hazard management and preparedness, the monitoring of drought requires the evaluation of influencing factors via the Drought Hazard Inventory (DHI). The main objective of this study is to compare spatial occurrences of drought hazard with the help of microwave and Optical/Infrared datasets obtained from multiple satellites. The long-term climatology of the Tropical Rainfall Measuring Mission (TRMM) Rainfall, Climate Change Initiative soil moisture (CCI-SM) and Moderate Resolution Imaging Spectroradiometer (MODIS) derived Land Surface Temperature (LST), Evapotranspiration (ET) and Normalized Difference Vegetation Index (NDVI) were used in this study for drought hazard assessment. This study was carried out in the Bundelkhand region of Uttar Pradesh, considered as one of the most frequent and dominant drought-prone areas of India. The current study includes the Analytical Hierarchy Process (AHP) technique based on Multi-Criteria Decision Making Analysis (MCDM) for weighting assignment and decision making, while the geospatial platform was used for data layer standardization, integration, and drought assessment. The results indicate that a large percentage of area (38.05% and 27.54%, respectively) lying in the central part of Bundelkhand region is under high to extreme drought conditions, where precautionary measures are needed. To demonstrate the robustness of our results, we compare them with the long-term in-situ ground water depletion as a proxy. Finally, based on the findings of this study, we recommend the methodology for drought assessment at a larger scale, as well as in the remote areas where ground based measurements are limited.