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Site selection is one of the basic vital decisions in the start-up process, expansion or relocation of businesses of all kinds. Starting from the meeting criteria defined in the business strategy , location selection process begins as recognition of existing or projected need to meet new or growing market. Recognition of the need to initiate a seri...
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... Spatial multicriteria analysis land-based unit on a map (whether raster or vector-based) would be colored from green (very suitable) to red (not suitable or compatible). Each map would represent a theme such as current land-use compatibility ( Figure 6). Typical location analysis problems can be characterized as very complex and data intense. ...
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The use of Multi-Criteria Decision Making (MCDM) precisely the Analytic Hierarchy Process (AHP) method in planning a suitable location for car parking, planners put into consideration a lot of factors. These different considerations make the planning process complex and as such there might be confusion of interest in the decision making. This paper...
The presence of logistics clusters makes an important contribution to the effectiveness of the logistics operations, so the development of national economies as well. However, establishing a cluster is a very costly and time consuming process, and the selection of the regions where the cluster is planned to be established is required a detailed pla...
Purpose
The purpose of this paper is to discuss the advantage of a combinatory methodology presented in this study. The paper suggests that the comparison with results of previously developed methods is in high agreement.
Design/methodology/approach
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Citations
... In this analysis, indexes that reflect different dimensions such as economic, social, technical, environmental, political data, etc. are represented in independent maps called layers. These maps can be overlaid, the result being enriched with new useful information for the decision maker or other consumers, according to Rikalovic et al. [63]. ...
Against the background of multiple and simultaneous global socio-economic shocks, coupled with digital transformation and the green transition, regional resilience triggers new structural transformations. The more complex processes that need to be addressed now require the usage of complex integrated tools. The novelty of the integrated approach is the combination of the models and the synthetic spatial–temporal picture offered. The quadruple helix, or 4Helix, model puts Higher Education Institutions (HEIs) at the nexus of generating regional digital resilience. We posit a new mindset and behavior of human capital to reinforce innovation and knowledge production and transfer. We explore, using the Romanian national case, to what degree the spatial 4Helix model generates regional digital resilience as a positive externality of adoption of the ‘new normal’ digital education. We analyze this process in three steps. (1) We determine the spatial distribution of HEIs at the Romanian county level (NUTS3). (2) We calculate the regional static and dynamic resilience indexes (at NUTS2) as the outcome of the method for multi-criteria decision making (MCDM) by each region’s digital economy as well as individual and regional wealth, social digital use and social digital connectivity dimensions. (3) Lastly, we provide the result of overlaid maps and radar charts (using HEIs number and spatial coverage and each region’s static and dynamic digital resilience). These three classes of digital resilience models of 4Helix by region indicate a generalized failure in adopting digital education in Romania. The study contributes by adding a powerful tool to explore the complex processes or phenomena and generating an integrated perspective using a pre-existing framework. In doing so, it enables researchers to better understand and address society’s needs, co-create knowledge and solutions together with the end-users, maximize the impact of these solutions, optimize resources usage, and increase the transparency and accountability of the decision-making processes.
... Multi-Criteria Decision Analysis (MCDA) approach using multiple GIS data for decision-making[61]. ...
Urban planners, local authorities, and energy policymakers often develop strategic sustainable energy plans for the urban building stock in order to minimize overall energy consumption and emissions. Planning at such scales could be informed by building stock modeling using existing building data and Geographic Information System-based mapping. However, implementing these processes involves several issues, namely, data availability, data inconsistency, data scalability, data integration, geocoding, and data privacy. This research addresses the aforementioned information challenges by proposing a generalized integrated methodology that implements bottom-up, data-driven, and spatial modeling approaches for multi-scale Geographic Information System mapping of building energy modeling. This study uses the Irish building stock to map building energy performance at multiple scales. The generalized data-driven methodology uses approximately 650,000 Irish Energy Performance Certificates buildings data to predict more than 2 million buildings’ energy performance. In this case, the approach delivers a prediction accuracy of 88% using deep learning algorithms. These prediction results are then used for spatial modeling at multiple scales from the individual building level to a national level. Furthermore, these maps are coupled with available spatial resources (social, economic, or environmental data) for energy planning, analysis, and support decision-making. The modeling results identify clusters of buildings that have a significant potential for energy savings within any specific region. Geographic Information System-based modeling aids stakeholders in identifying priority areas for implementing energy efficiency measures. Furthermore, the stakeholders could target local communities for retrofit campaigns, which would enhance the implementation of sustainable energy policy decisions.
... In the literature, the planning processes focused on locating a single site generally disaggregate the problem into several levels. Zelenovic [6] distinguishes macro-and micro-locations and proposes a process consisting of four phases involving the selection of the continent, the country, the municipality and finally the specific location in the municipality (see Fig. 1) [14]. ...
Industrial site selection is a strategic decision that involves several criteria with consideration for technical, economic, social, environmental, and political issues. These criteria are generally described using a number of different indicators, expressed in quantitative and qualitative ways with some possible uncertainty. Decision making requires, therefore, appropriate tools to enable data collection, storage, analysis, fusion, and knowledge management to address this complex multifaceted scenario. This paper presents a comprehensive method for industrial site selection, an innovative approach for reasoning uncertainty and efficiently finding the most suitable solution based on a set of interacting decision support systems. Experimental results show that the proposed approach provides accurate results in the region of interest, coinciding with the choices of expert analysts.
... Analysis of attribute data of one thematic layer can be performed: as SQL query against a table with attribute data; using different arithmetic operations(addition, subtraction, multiplication, division), logarithmic functions, trigonometric functions, and so on; application of some nonparametric techniques like Multicriteria methods and methods based on artificial intelligence, and one of them is method that uses artificial neural network [21]. ...
Site selection is one of the basic vital decisions in the start-up process, expansion or relocation of businesses of all kinds. Construction of a new industrial system is a major long-term investment, and in this sense determining the location is critical point on the road to success or failure of industrial system. One of the main objectives in industrial site selection is finding the most appropriate site with desired conditions defined by the selection criteria. Most of the data used by managers and decision makers in industrial site selection are geographical which means that industrial site selection process is spatial decision problem. Such studies are becoming more and more common, due to the availability of the Geographic Information Systems (GIS) with user-friendly interfaces. Geographic information systems (GIS) are powerful tool for spatial analysis which provides functionality to capture, store, query, analyze, display and output geographic information. Geographic Information Systems are used in conjunction with other systems and methods such as systems for decision making (DSS) and the method for multi-criteria decision making (MCDM). Synergistic effect is generated by combining these tools contribute to the efficiency and quality of spatial analysis for industrial site selection. This paper presents a successful solution for spatial decision support in the case of spatial analysis of Vojvodina as a region of interest for industrial site selection.
... There are methods of analysis of geographic data and methods of analysis of attribute data. The most commonly used are the GIS spatial analysis [20]: analysis of attributive (tabular) data, overlapping layers (i.e. query of spatial data), distance analysis and nonparametric techniques such a Multi-Criteria Decision Analysis (MCDA) [19], Genetic Algorithms (GA) [4] etc. Analysis of attribute data of one thematic layer can be performed: as SQL query against a table with attribute data; using different arithmetic operations (addition, subtraction, multiplication etc.), logarithmic functions, trigonometric functions, multicriteria decision method, and methods based on artificial intelligence. ...
Industrial location (site) selection is a strategic decision and in that sense determining the location is a critical point on the road to success or failure of the company.One of the main goals of industrial location selection is finding optimal location with desired conditions.To select the optimal industrial location it is necessary to do a broad spatial location analysis.Geographic Information Systems (GIS) are ideal for this type of spatial analysis which provides functionality to capture, store, query, and analyse geographic information.Recent development in field of spatial analysis leads to dramatic improvements in the capabilities of GIS in location analysis. These development are reviewed through distance analysis, attribute data analysis, multi-criteria analysis etc. This paper presents the role of GIS in industrial location analysis with examples
The Role of GIS in Industrial Location Analysis. Available from: https://www.researchgate.net/publication/282286105_The_Role_of_GIS_in_Industrial_Location_Analysis [accessed Aug 13 2018].
Buku ini mengulas tentang teori-teori yang dapat digunakan dalam
perencanaan dan sistem analisis spasial berbasis multikriteria dalam
pembangunan wilayah dan kawasan hutan di Indonesia. Buku ini juga
menyajikan contoh-contoh praktis pengolahan data dan hasil-hasil
analisis spasial di kawasan hutan dalam rangka perubahan peruntukan
dan perubahan fungsi kawasan hutan menggunakan teknologi SIG,
Hingga akhir tahun 2018, kawasan hutan mencapai luas 120,6 juta
hektar atau sekitar 63% dari luas wilayah daratan Indonesia. Pemerintah
menetapkan dan mempertahankan kecukupan luas kawasan dan tutupan
hutan minimal 30% dari luas daerah aliran sungai (DAS), dan atau pulau
dengan sebaran yang proporsional guna optimalisasi manfaat lingkungan,
manfaat sosial, dan manfaat ekonomi masyarakat setempat.
Perubahan luas kawasan hutan Negara di Indonesia tampaknya akan
mengalami pengurangan sebagai akibat dari tingginya laju kebutuhan
lahan untuk perkotaan dan permukiman penduduk, pertanian lahan
garapan, perkebunan dan kawasan industri baru. Kondisi tersebut
mengharuskan para akademisi untuk terus berpikir mengembangkan
teknologi perencanaan berbasis analisis spasial dan para praktisi untuk
mengadopsi teknologi tersebut dalam proses perubahan peruntukan dan
perubahan fungsi kawasan hutan, baik dilakukan melalui review rencana
tata ruang wilayah provinsi/kabupaten/ kota setiap lima tahun maupun
yang dikerjakan secara parsial yang bisa saja terjadi setiap tahun.
Akhbar, Naharuddin, Arianingsih I, Misrah, Akhbar RK. 2022. Spatial model of forest area designation and function based on multi-criteria in dry land and mangrove forest ecosystems, Central Sulawesi, Indonesia. Biodiversitas 23: 3619-3629. Along with the dynamics of rapid social change and the need for land for economic development, land and climate parameters on changes in the designation and function of forest areas, it is time to integrate with socioeconomic parameters and government policies while still paying attention to the condition of existing forest vegetation cover. This study aimed to develop a spatial analysis model of changes in the designation and function of forest areas based on multi-criteria in dry land and mangrove forest ecosystems. The research used a descriptive-spatial method with a multi-criteria-based decision-making technique for changes in the designation and function of forest areas. The data analysis utilizes Geographic Information System. The motivation for the proposed forest area change is the target to be achieved in the multi-criteria decision analysis. This research resulted in a spatial analysis approach that integrates scoring techniques and multi-criteria-based decision-making techniques. In Locus BL_010, a change in the function of forest area can be generated, while in Locus TL_003 a decision is made to change the allocation and function of forest area. The achievement of multi-criteria-based spatial analysis on changes in the designation and function of forest areas is quite flexible in decision making because each proposed motivational target will be achieved if it is in accordance with the established criteria and field facts.
Selecting a suitable site is a critical step in wind energy projects. In this regard, using appropriate decision criteria plays a significant role. Turbulence intensity is one of the main characteristics of airflow that affects the power production and lifespan of wind turbines. Therefore, it is considered as a wind site selection criterion in this paper.
The present paper formulates the effect of turbulence on both power production and lifespan of wind turbines via an equivalent wind power density (WPDeq) function, to use it in the wind site selection process. To implement the proposed methodology, 88 wind sites in Iran have been studied. The results reveal the significant effect of turbulence on the site selection process as some sites have changed their rank up to 8 grades considering turbulence intensity in the siting process.
To consider the turbulence intensity as an independent criterion to use it in multi-criteria decision-making methods, its relative importance (weight) have to be calculated. Sensitivity analysis shows that, on average, the relative importance of turbulence intensity over wind power density can be approximated as 1/5. Researchers can quickly consider turbulence intensity in siting process incorporating its weight in the pairwise comparison matrix of multi-criteria decision–making.
