GIS-BASED METHOD FOR WIND FARM LOCATION MULTI-CRITERIA ANALYSIS

Rapid population growth integrated with poor governance and urban planning is highly challenging resulting key for the selection of unsuitable landfill sites, particularly in developing counties. Therefore, the aim of this study is to investigate the suitable solid waste landfill sites in the capital of the country as a case study, by the integration of Geographical Information System (GIS) with fuzzy logic, analytical hierarchy process (AHP), and weighted linear combination (WLC) method based on multi-criteria decision-making (MCDM). We chose thirteen (13) criteria (9 factors and 4 constraints) and grouped them into two main categories (environmental and socioeconomic) to achieve the objectives. The AHP was employed to evaluate the relative importance of the factors followed by standardization of criteria factors based on fuzzy set theory. Subsequently, all criteria factors were combined based on AHP and fuzzy logic-WLC method in order to obtain land suitability map. Finally, the sites were identified by the intersection of two combined suitability index layers. The obtained results depicted that the integration of fuzzy logic, AHP, and WLC technique with GIS can produce satisfactory results for the suitable locations of solid waste landfill sites over complex topographic regions. Overall, the land suitability obtained based on fuzzy-WLC is more refined and smooth because of its better segregation and its potential to consider full tradeoff between factors and average risk. The AHP was identified (47km2) as high suitable while fuzzy-WLC generated 36km2 as suitable area. Finally, the intersection of both suitability index map shows numerous suitable landfill sites available in Islamabad city; however, the surface areas of the sites are small at individual level (less than 15ha).

The aim of this study was to identify potential sites for wind turbine in the North West of Jordan. The Analytic Hierarchy Process (AHP) was used in a novel approach to identify the potential sites for the wind turbine in the study area based on five physical criteria (Wind Speed, Rainfall, Slope, Altitude and Land use) that affect the wind turbine sites. The importance of each criterion was based on experts’ opinions. The ratings for each criterion were based on the available literature review. The consistency ratio between the experts’ opinions was evaluated using the pairwise comparison method and a final weight was computed for each criterion. A wind turbine suitability map was generated using the weighted linear combination (WLC) method within GIS environment. It was found that 45% of the study area has high and very high suitability for wind turbine. In conclusion, this research will contribute to the enhancement of the available renewable energy resources in Jordan if the selected sites will be utilized for wind turbine.

To prepare landslide susceptibility map of the Shivkhola watershed, one of the landslide prone part of Darjiling Himalaya, RS and GIS tools were being used to integrate 10 landslide triggering parameters like lithology, slope angle, slope aspect, slope curvature, drainage density, lineament, upslope contributing area (UCA), road contributing area (RCA) settlement density, and land use and land cover (LULC). Analytical Hierarchy Process (AHP) was applied to quantify all the factors by estimating factors weight on MATLAB Software with reasonable consistency ratio (CR). Frequency ratio model (FR) was used to derive class frequency ratio or class weight incorporating both pixels with and without landslides and to determine the relative importance of individual classes. All the required data layers were prepared in consultation with SOI Topo-sheet (78B/5), LIIS-III Satellite Image (2010) by using Erdas Imagine 8.5, PCI Geomatica, and ARC GIS Software. The weighted linear combination (WLC) method was followed to combine factors weight and class weight and to determine the landslide susceptibility coefficient value (LSCV or ‘M’) on GIS platform. Greater the value of ‘M’, higher is the susceptibility of landslide. The Shivkhola watershed was classified into five landslide susceptibility zones by averaging window lengths of 3, 5, 7, and 9 and taking into account the landslide threshold boundaries value of 7.05, 9.29, 11.5, and 13.8. The overall classification accuracy rate is 92.22 % and overall Kappa statistics is 0.894. The elements like weighted LULC map, RCA (road contributing area) map and settlement density map were developed and their weighted linear combination was performed to prepare landslide risk exposure map. Then by integrating landslide susceptibility map and landslide risk exposure map landslide hazard risk co-efficient values were derived and a classification was incorporated on ARC GIS Platform to prepare landslide hazard risk map of the Shivkhola watershed. To evaluate the validity of the landslide hazard risk map, probability/chance of landslide hazard risk event has been estimated by means of frequency ratio (FR) between landslide hazard risk area (%) and number of risk events (%) for each landslide hazard risk class. Finally, an accuracy assessment was made through a comparative study between true GPS derived data and a set of randomly selected pixels points from the classified image corresponding to the true data from 50 locations on ERDAS Imagine (8.5) which depicts that the classification accuracy of the landslide hazard risk map was 92.89 with overall Kappa statistics of 0.8929.

Urban development is a high priority in Egypt. New Minia City, located on the eastern bank of the Nile River, approximately 250 km south of Cairo, is one of 16 new development communities. Urban development in New Minia City may encounter several geo-environmental problems. Karst conditions and structural features in the local heterogeneous bedrock limit its suitability for constructional purposes. In this research, suitability of the area for urban development was assessed using a geographic information systems (GIS)-based approach. A weighted GIS model that incorporated land use/cover, types of soil, karst feature distribution, fracture densities, slopes, distances to major faults and streams, road network, and city boundaries was established to create a map of site suitability for the city. Model weights were developed using the analytical hierarchy process (AHP) approach. Current urban land use within New Minia City falls into four classes of suitability. Approximately 7 percent of the area built by 2002 is in the low suitability class, which suggests that the map of site suitability can serve as a reliable base for planning sustainable development in New Minia City. The developed map of site suitability is effective for assessing and revealing ratings of suitability for urban development. Furthermore, the map of suitability provides the foundation for informed decision making in the development of New Minia City.

Montenegro has different influences on the weather and climate; in general, according to Köppen’s classification, there are two climate zones: warm temperate (C) and cold temperate (D). The aim of this study is to determine the susceptibility to wildfires in the Montenegrin coastal municipality of Budva and the northern municipality of Rožaje, which are located in different climatic conditions, using multicriteria GIS decision analysis (GIS-MCDA). Nine natural and anthropogenic criteria were used for the analysis. Open geospatial data were used as input data for all criteria. The assignment of weighting coefficients for the criteria in relation to wildfire susceptibility importance was based on the Analytic Hierarchy Process (AHP) and Fuzzy Analytic Hierarchy Process (F-AHP) procedures. The results for the AHP and F-AHP models were obtained using the Weighted Linear Combination (WLC) method. According to the AHP model, the very high and high category covers 80.93% of the total area in Budva and 80.65% in Rožaje. According to the F-AHP model, the very high and high category occupies 80.71% of the total area in Budva and 82.30% in Rožaje. The validation shows that the models of GIS-MCDA perform fair in both climatic zones. The proposed models, especially in the absence of geospatial data, can be a strategic and operational advantage in the development of plans and strategies for protection against wildfires.

Ecotourism has gained popularity among travelers in recent years due to the detrimental effects of conventional tourism. Purulia district in West Bengal (India), with its diversified picturesque landscape such as lush green forest, mesmerizing riverscape, lakes, waterfall, hills and uniqueness in the local community’s culture gives ample potentiality of ecotourism development. The aim of this paper to explore potentiality of ecotourism in Purulia district, West Bengal, India using Analytical Hierarchy Process (AHP) and Geographical Information System (GIS). Initially, ecotourism inventory dataset was developed based on following criteria: Elevation, slope, proximity to river, distance from road, distance from settlements, distance from ecological sites, distance from railway, distance from tourism sites using ARC-GIS 10.6.1 software. Later, the suitability map of ecotourism development has been developed by applying Weighted Linear Combination (WLC) with combination of the criteria with their respective weights and categorized into five suitability classes as highly suitable (S1), moderately suitable (S2), suitable (S3), less suitable (S4) and unsuitable (S5). Finally, after the identification of suitable zones, six alternatives ecotourism destinations are identified. This proposed method may be helpful for the local stakeholders and public administration in identifying potential ecotourism destination and planning for sustainable ecotourism development.

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.

Analysis and identification of superior agricultural commodity areas play a crucial role in determining regions with high potential for agricultural development. This study aims to identify priority agricultural commodities and assess their development potential in Lawang, Matur District, Agam Regency, West Sumatra Province. The research was conducted in several stages. First, superior agricultural commodities were identified using the Location Quotient (LQ) and Shift Share Analysis (SSA) methods. Second, the potential development areas for these commodities were determined using the Analytical Hierarchy Process (AHP) and Weighted Linear Combination (WLC) approach, integrated with Geographic Information System (GIS) analysis. The results indicate that the priority agricultural commodities in Nagari Lawang are peanuts for the food crop subsector, shallots for the horticulture subsector, and sugarcane for the plantation subsector. These findings provide valuable information for policymakers and local farmers to optimize land use, enhance agricultural productivity, and support sustainable rural economic development. Furthemore, the methodology used in this study can also be applied to other regions to identify superior agricultural commodities.Keywords: Analytical hierarchy process, Leading commodities, Location quotient, Shift share analysis, Weight linear combination.

This study assesses and maps the physical flood vulnerability within the Xerias, Krafsidonas, and Anavros ungauged catchments in Volos, Thessaly, Greece, using a Geographical Information Systems (GIS)-based Multi-Criteria Decision Analysis (MCDA) integrated with the Analytic Hierarchy Process (AHP). Six factors influencing flood dynamics were selected including slope, flow accumulation, geology, land use/cover, flood history and burned areas. The factors were weighted using the AHP based on their relative influence in flood occurrence. Physical flood vulnerability was assessed utilizing the Weighted Linear Combination (WLC) method and visualized through thematic flood-vulnerability maps. The analysis indicates that the southwestern and central-southern parts of the study area, which are highly urbanized and industrialized, exhibit the highest physical flood-vulnerability. Specifically, 32.76% of the Xerias catchment, 41.16% of the Krafsidonas catchment, and 34.71% of the Anavros catchment exhibit high to very high flood vulnerability. On the other hand, mountainous areas with steep slopes, permeable lithology, and dense forests exhibit low to very low physical flood vulnerability. The method’s accuracy was verified through sensitivity analysis and comparison with national flood-risk data for the study area. The results emphasize the physical vulnerability of Volos to flooding and the necessity for targeted flood mitigation measures, demonstrating the value of GIS in flood risk management.

Climate change affects plant species, especially those with restricted ecology and distribution. Centaurium erythraea is a flowering plant species in the Gentianaceae family, native to Europe, with its centre of diversity in the Mediterranean and western Asia. Of the 11 infraspecific taxa distinct from C. erythraea, only two are common in Europe: C. erythraea subsp. erythraea (widespread nominal subspecies) and C. erythraea subsp. majus (mainly distributed in the western Mediterranean region). Freshly collected samples of 36 plants from 11 localities across Lower Silesia (Central Europe) were utilised for taxonomic and genetic analysis. The barcode sequences of chloroplast DNA region matK were used for molecular analysis. Data deposited in GenBank was also used. Five haplotypes were identified among the analysed specimens. Species Distribution Modelling (SDM) techniques were applied to predict the current and future (short- and long-term projections) potential distribution of C. erythraea subsp. majus and to identify the most influential climatic factors. Despite the typical Mediterranean distribution, the presence of C. erythraea subsp. majus outside its natural range in SW Poland has been confirmed by morphological and genetic studies. The mean monthly precipitation of the wettest quarter and the mean daily temperatures of the warmest quarter were identified as the key climatic factors. Short-term scenarios suggest that C. erythraea subsp. majus will maintain most of its current suitable habitats and potentially expand into the lowlands of Central Europe. However, long-term projections indicate a potential reduction in its currently suitable areas, especially in the southern parts of its range, with a possible expansion into north-western Europe. The results of these studies provide clear evidence of the impact of ongoing climate change on species range changes. These findings suggest that climate change may create new opportunities for Mediterranean species to spread to new regions, using C. erythraea subsp. majus as an example.

Weighted linear combination (WLC) method was used to assess landslides vulnerability of the Simbu Province, Papua New Guinea within the GIS environment of ArcGIS. This multi-criteria evaluation method allows flexibility and tradeoffs amongst all parameters used. Ranks and weights are assigned depending on their influence on the occurrence of landslides. Parameters selected for the study include slope angle, elevation, rainfall, vegetation cover, land use/land cover, landform, proximity to roads, proximity to rivers and proximity to lineaments. Restricted in some sense in terms of data, WLC was appropriate in using existing metadata of the country; Papua New Guinea Resource Information System and Forest Information Management System. The landslide susceptibility map provides valuable information of the risk at hand in the province and district levels to better manage and plan mitigation measures. The slope factor was assigned a weighted of 4 as having greater influence on landslides in the region followed by rainfall weighted of 2 and the other having uniform influence of 1. The study area shows the distribution of the five vulnerability/susceptibility classes ranking from very low (1) to very high (5). Areas with very high landslide vulnerability zones are found in the northern and western parts of Simbu Province. Comparatively, southern parts have very low vulnerability areas. From the calculations done, 6.21 % of area is at very low risk, 20.24 % at low risk, 32.27 % of moderate risk, 26.88 % of high risk and 14.41 % of very high risk area coverage.

Landslide susceptibility assessment in Addi Arkay, Ethiopia using GIS, remote sensing, and AHP

Secondary succession of abandoned agricultural land is a long-term process, shaped by numerous biotic and abiotic factors. One stage in this process is the encroachment of pioneer tree species, among which the black cherry Padus serotina is increasingly common. This invasive species is widespread in temperate forests in Europe and is beginning to colonize open habitats, including fallow lands. In this study, we evaluated the effects of P. serotina on floristic composition, vegetation, and species diversity. Ten fallows in Lower Silesia (SW Poland) were selected. Within each field, five study plots invaded by P. serotina and five without this species were established. Botanical composition and area covered by individual plant species were determined in total of 100 plots. Our results indicate that the P. serotina seedlings and saplings have the strongest impact on species composition. The increase in P. serotina cover in the herb layer is accompanied by a reduction in the spread of expansive species such as Calamagrostis epigejos and Solidago gigantea. The low thickets formed by P. serotina provide perching sites for birds and facilitate seed dispersal, which promotes the development of multispecies shrub communities and enhances species diversity in study fallows at the current stage of succession.Supplementary InformationThe online version contains supplementary material available at 10.1038/s41598-025-29099-8.

Rill and gully erosion are an important morphological feature of lateritic terrain in Jhargram District, a part of rolling topography of Chhotonagpur Plateau. The present work took the River Dulung basin’s rill and gully erosion as a study and used analytical hierarchy process (AHP) to extract the anatomical line of rill and gullies. This chapter analyzes the probable risk patches of rill and gullies along the River Dulung basin. To evaluate the risk zone of rill and gully erosion, eight biophysical variables were selected. The analytical hierarchy process (AHP) and weighted linear combination (WLC) were considered to functionalize the conceptual model within a geographic information system (GIS) framework. Results revealed that 2.74 km2 of the study area falls into the very high-risk zone; 201.18 km2 area comes under high-risk zone; 570.04 km2 area falls into moderate risk zone; 111.63 km2 area comes under the low-risk zone and 0.226 km2 area falls into the very low-risk zone.

Renewable Energy (RE)-based power production often comes with certain challenges in variability and uncertainty of generated electricity. One promising solution to tackle these challenges is developing a network of RE power plants with sites located far enough from each other that experience different weather patterns. Most of the site selection-related literature use Geographical Information Systems to determine the studied site RE suitability. This work converts the site selection into a numerical problem through a novel Networked Renewable Power Plant Site Selection model and solves it by employing optimization techniques. To enhance the accuracy of the results, it compares a set of criteria for individual and network of sites at different regions to determine the exact locations for RE plant developments. The Analytical Hierarchy Process is used for criteria weighing. The state-of-the-art meta-heuristic Bare Bones of Fireworks algorithm offer a simple, fast, yet accurate approach to solve the optimization. The proposed method is applied on North Carolina wind farms for both individual and a network of sites. The results identified the areas with the highest wind capacity potential for individual or a network of wind farms in North Carolina. The identified suitable areas were verified with Amazon Wind Farm US East.