Integration of AHP and GIS to Derive Walkability Index for Women to Access Rail-Transit Station

The integration of the Analytic Hierarchy Process (AHP) with Geographic Information Systems (GIS) presents a powerful framework for improving waste management practices. AHP serves as a structured decision-making tool that enables stakeholders to prioritize and evaluate various alternatives based on multiple criteria, while GIS enhances this process by providing spatial analysis capabilities that allow for the visualization and examination of geographic data. This combination is particularly relevant in the context of waste management, where decisions often involve complex trade-offs among environmental, economic, and social factors. The primary aim of this study is to investigate the synergistic integration of AHP and GIS within the realm of waste management. Specifically, the research focuses on three critical areas: assessing various waste disposal methods, selecting optimal sites for landfills, and optimizing waste collection routes. By leveraging the strengths of both methodologies, the study seeks to enhance decision-making processes in waste management. The methodology involves breaking down complex decision-making scenarios into a hierarchical structure of criteria and sub-criteria. This structured approach allows stakeholders to systematically compare different options based on a range of factors, including environmental impact, cost-effectiveness, community acceptance, and logistical feasibility. GIS complements the AHP framework by providing essential spatial data that reveals patterns and relationships in waste generation and disposal, facilitating a more comprehensive analysis. The integration of AHP and GIS empowers decision-makers to visualize the potential implications of their choices more effectively. For example, GIS can be utilized to map waste generation hotspots, identify suitable location s for waste management facilities, and analyze transportation routes for their efficiency and effectiveness. This visualization aids in understanding the spatial dynamics of waste management and supports more informed decision-making. Overall, the synergy between AHP and GIS significantly enhances the effectiveness of waste management strategies. This integrated approach not only leads to more sustainable waste management practices but also improves resource allocation and fosters better community engagement in waste management initiatives. By supporting informed, data-driven decision-making, the combination of AHP and GIS ultimately contributes to the development of more efficient and environmentally friendly waste management solutions. The findings of this study underscore the importance of utilizing advanced analytical tools in addressing the multifaceted challenges of waste management, paving the way for innovative and sustainable practices in the field.

Integration of shannon entropy (SE), frequency ratio (FR) and analytical hierarchy process (AHP) in GIS for suitable groundwater potential zones targeting in the Yoyo river basin, Méiganga area, Adamawa Cameroon

The study area comprises Erbil province, Kurdistan region, Iraq. Thirty-five soil samples have been taken from different districts. Several soil analyses have been performed in order to find soil loss as a criterion for land suitability assessment. The other criteria were elevation, slope, aspect ratio, and land use and land cover (LULC). All used criteria have been weighted using Analytic Hierarchy Process (AHP) methodology to find their priorities in order to use them on weighted overlay methodology (WOM) based on the Geographical Information Systems (GIS) technique. Integration of AHP and GIS have been utilized in purpose to find the land suitability based on five classes; high suitable (S1), moderately suitable (S2), marginally suitable (S3), not suitable (N1), and not suitable permanently (N2). The result of land suitability shows that the S1 class is generally located at the northwest of the middle part in the study area extended to the southwest, and it occupies an area of 1243.94 km2 (8.61%). The S2 class occupies a minimum area of 85.52 km2 (0.59%), while the S3 class occupies a massive area relatively about 4886.75 km2 (33.82%). The N1 class occupies the highest area, around 6538.32 km2 (45.26%). At the same time, N2 class takes 1693.16 km2 (11.72%). Both N1 and N2 have an area of 8,231 km2 (56.98%) of the total area while S1, S2, and S3, which takes only 6,216 km2 (43.02%).In this study we found the possibility of using GIS and AHP in order to find the land suitability assessment.

Identifying flood vulnerable and risk areas using the integration of analytical hierarchy process (AHP), GIS, and remote sensing: A case study of southern Oromia region

In solid waste management, landfilling is still widely practiced because it is convenient and consumer friendly. Unfortunately, many landfill sites have closed and cause problem in managing the waste. The purpose of this study is to suggest suitable and potential sites for landfill in Johor Bahru area through mapping technique and database system. Analytical Hierarchy Process (AHP) is a method for analysis and supports decision where multiple and competing objectives are involved. Fifteen parameters were identified to use in AHP process. In this method, the process is divided into hierarchy before pair wise comparison was done and the result is prioritizing according to their weightage. The process is continued with weightage evaluation and its consistency. Landfill site selection process involved many spatial data and strenuous in handling it. Geographic Information System (GIS) can give significant help because it can potentially handle large volume of data that need to be evaluated and processed. The method used in GIS is digitizing, buffering and overlays. As a result in AHP, the most important criterion is river weighted 0.149 of all criteria and the least important criteria are distance to main road weighted 0.028 of other criteria. In GIS method, there are six parameters selected which are main road, plantation, residential area, swamp, grassland and river coverage. The findings identified two potential sites for landfill area because it satisfied all given requirements. Integration of GIS and AHP is suitable to be used in landfill site selection process because it will helps in locating new landfill site that is environmentally, economically and socially wise.

In this study, geographic information system (GIS)‐based network analysis and analytic hierarchy process (AHP) methods were applied to the Erzincan–Trabzon segment of the Turkish high‐speed railway (HSR) project. A new hybrid route, which considers both economic and environmental criteria, was created and compared with three different routes from various preconstruction studies. The route‐generating analysis included the eight parameters (criteria) of slope, geology, soil quality, rivers, protected areas, roads, land cover, and lakes. The optimum route for connecting the port of Trabzon to Turkey's interior via HSR was generated. The weights for determining the route were tested for sensitivity. The study demonstrated the efficiency of GIS and AHP integration in generating optimum routes for HSR projects according to given databases. All these GIS and AHP analyses were applied automatically with our novel GIS extension for determining optimum HSR routes. The final route has preserved cultural and historical structures, environmental integrity. The new hybrid route also decreased construction costs by approximately 12%, and the least‐cost‐path analysis confirmed the environmental efficiency of the route.

This study aimed at delineating the wildfire risk zones in a fire-prone region located in a rarely addressed area of western Iran (Paveh city)by assessing the potential of factors such as NDVI, topographic factors (elevation, slope, and aspect), land cover, and evaporation in explaining the fire occurrence probability. Analytic hierarchy process (AHP) and geographical information system (GIS) methods were used synergistically to integrate the mentioned factors into analysis, following an informed categorization of each factor based on the information on previous fire occurrence. In the AHP process, elevation and evaporation data were considered to be the most critical factors. It was found that the predicted wildfire risk areas were in agreement with past fire events by the use of the methodology proposed by this study. Accordingly, the study's final wildfire risk map indicated that approximately 64.7% of the study area is located in the high- and very high-risk zones. Land-use planners and decision-makers may use the developed map to setup and implement fire prevention strategies and enhance or develop the fire-surveillance logistics and infrastructure, including but not limited to the positions of fire watchtowers, fire lines, and fire sensors, with the aim to minimize potential fire impacts.

The study presents a comprehensive evaluation of optimal locations for solar energy facilities in Yemen by com-bining Geographic Information System (GIS) technology with Multi-Criteria Decision-Making (MCDM) methodolo-gies. It identifies twelve crucial criteria, assigning weights through the Analytical Hierarchy Process (AHP) andsubsequently validating them using the Best-Worst Method (BWM). A weighted overlay analysis conducted inGIS resulted in a national suitability map, indicating that the eastern, southern, and northern regions of Yemen areparticularly well-suited for solar energy development. The findings reveal that 30.84% of the country is classifiedas highly suitable, while 69.16% is moderately suitable, and merely 0.0022% is deemed less suitable for solarinstallations. The sensitivity analysis highlights the significant influence of weighting the criteria, as even slight modifications to factors such as Global Horizontal Irradiance (GHI) and slope can lead to substantial changes in suitability assessments. Overall, the integration of AHP, BWM, and GIS is shown to create a robust framework for solar site selection, providing practical guidance for policymakers and energy planners in Yemen.

Land Suitability Assessment (LSA) aids in identifying optimal crop cultivation sites; thereby, it is the key factor for proper planning to maximize production yield. It needs a combination of Analytic Hierarchy Process (AHP) and Geographic Information System (GIS) to improve LSA for the production of barley, beans, maize, soybean, sugar beet, and wheat in Egypt’s New Delta. Topography (slope), and characteristics of the soil (depth, pH, texture, carbonate content, and salinity) were the six factors employed. Land was assessed on a five-level suitability scale—highly suitable (S1), moderately suitable (S2), marginally suitable (S3), currently not suitable (N1), and permanently not suitable (N2). Pairwise comparisons and consistency ratios in AHP were used to determine weights for the criteria. Weighted overlay analysis produced land suitability maps. Key findings indicate slope as the primary factor for barley and wheat and soil properties as more significant for beans, soybean, and sugar beet. Barley, beans, maize, soybean, and wheat were assessed as highly suitable (S1), moderately suitable (S2), and marginally suitable (S3), but sugar beet was assessed as moderately suitable (S2). The results are valid for crop rotation for increased production and soil fertility by the appropriate use of AHP and GIS in sustainable land use management.

Groundwater is a vital resource, particularly in arid and semi-arid regions where surface water availability is limited. This study focuses on mapping groundwater potential zones (GWPZs) in the Dhule district of Maharashtra, India, an area characterized by complex hydrogeological conditions within the Deccan Volcanic Province (DVP). Utilizing a multi-criteria decision analysis (MCDA) approach, the study integrates geospatial techniques with geoelectric data to accurately delineate areas with high groundwater potential. The analytical hierarchy process (AHP) combined with Geographic Information System (GIS) methodologies enables a detailed assessment of various influencing factors, including geological structures, soil texture, slope, drainage density, and land use patterns. Key findings highlight that regions with specific geological formations, such as weathered and fractured basalts and areas with dykes, show higher groundwater potential due to their enhanced porosity and permeability. The study identifies the central Shindkheda, southern Sakri, and Dhule subdivisions as critical areas for implementing groundwater recharge techniques to mitigate surface runoff and erosion. Recommendations for these regions include the construction of trenches, bunds, recharge pits, and percolation tanks. Additionally, the adoption of water-saving technologies such as drip irrigation and rainwater harvesting is emphasized to improve groundwater recharge and management. The validated approach establishes a strong foundation for future research and interventions aimed at enhancing water security in similar hydrogeological settings. The integration of AHP and GIS provides a robust framework for groundwater resource management, offering valuable insights for decision-makers focused on sustainable water resource utilization.

Flooding is one of the major natural hazards in Taiwan, and most of the low-lying areas in Taiwan are flood-prone areas. In order to minimize loss of life and economic losses, a detailed and comprehensive decision-making tool is necessary for both flood control planning and emergency service operations. The objectives of this research were (i) to develop a hierarchical structure through the analytic hierarchy process (AHP) to provide preferred options for flood risk analysis, (ii) to map the relative flood risk using the geographic information system (GIS), and (iii) to integrate these two methodologies and apply them to one urban and one semi-rural area in central Taiwan. Fushin Township and the floodplain of Fazih River (1 km on either side of the channel) in Taichung City were selected for this study. In this paper, the flood risk is defined as the relative flood risk due to broken dikes or the failure of stormwater drainage systems. Seven factors were considered in relation to the failure of stormwater drainage, and five to that of broken dikes. Following well-defined procedures, flood maps were drawn based on the data collected from expert responses to a questionnaire, the field survey, satellite images, and documents from flood management agencies. The relative values of flood risk are presented using a 200-m grid for the two study areas. It is concluded that integration of AHP and GIS in flood risk assessment can provide useful detailed information for flood risk management, and the method can be easily applied to most areas in Taiwan where required data sets are readily available.

This paper aims to propose a grouping framework for benchmarking the active queue management (AQM) methods of network congestion control based on multicriteria decision-making (MCDM) techniques to assist developers of AQM methods in selecting the best AQM method. Given the current rapid development of the AQM techniques, determining which of these algorithms is better than the other is difficult because each algorithm performs better in a specific metric(s). Current benchmarking studies benchmark the AQM methods from a single incomplete prospective. In each proposed AQM method, the benchmarking was achieved with reference to some evaluation measures that are relatively close to the desired goal being followed during the development of the AQM methods. Furthermore, the benchmarking frameworks of AQM methods are complicated and challenging because of the following reasons: (1) the technical details of the AQM methods are adapted and the input parameters are selected according to the sensitivity of the AQM methods; and (2) a framework is developed and designed for simulating AQM methods, the simulated network and the collected results. For this purpose, a set of criteria for AQM comparison are determined. These criteria are performance, processing overhead and configuration. The benchmarking framework is developed based on the crossover of three groups of multi-evaluation criteria and several AQM methods as a proof of concept. The AQM families that are implemented and utilized in experiments to generate the data that are used as a proof of concept of our proposed framework are the parameter-based (pars) and fuzzy-based AQM methods. Accordingly, constructing the decision matrix (DM) that will be used to generate the final results is necessary. Subsequently, the underlying AQM methods are benchmarked and ranked using MCDM techniques, namely, integrated analytical hierarchy process (AHP) and technique for order of preference by similarity to ideal solution (TOPSIS). The validation was performed objectively. The [Formula: see text] deviation was computed to ensure that the AQM methods ranking undergo systematic ranking. Results illustrate that (1) the integration of AHP and TOPSIS solves the AQM method benchmarking problems; (2) results of the individual TOPSIS context clearly show variances among the ranking results of the six experts; (3) the ranks of the AQM methods obtained from internal and external TOPSIS group decision-making are nearly similar, with random early detection method being ranked as the best one; and (4) in the objective validation, significant differences were found between the groups’ scores, thereby indicating that the ranking results of internal and external TOPSIS group decision-making were valid.

In solid waste management, landfilling is still widely practiced because it is convenient and consumer friendly. Unfortunately, many landfill sites have closed and cause problem in managing the waste. The purpose of this study is to suggest suitable and potential sites for landfill in Johor Bahru area through mapping technique and database system. Analytical Hierarchy Process (AHP) is a method for analysis and supports decision where multiple and competing objectives are involved. Fifteen parameters were identified to use in AHP process. In this method, the process is divided into hierarchy before pair wise comparison was done and the result is prioritizing according to their weightage. The process is continued with weightage evaluation and its consistency. Landfill site selection process involved many spatial data and strenuous in handling it. Geographic Information System (GIS) can give significant help because it can potentially handle large volume of data that need to be evaluated and processed. The method used in GIS is digitizing, buffering and overlays. As a result in AHP, the most important criterion is river weighted 0.149 of all criteria and the least important criteria are distance to main road weighted 0.028 of other criteria. In GIS method, there are six parameters selected which are main road, plantation, residential area, swamp, grassland and river coverage. The findings identified two potential sites for landfill area because it satisfied all given requirements. Integration of GIS and AHP is suitable to be used in landfill site selection process because it will helps in locating new landfill site that is environmentally, economically and socially wise.

Fire is one of the main causes of environmental and ecosystem change. Geospatial data, derived from satellite images and surveying observations, are a useful tool in managing land use and land cover changes. In this paper, we present a multi-criteria-based geographical information system (GIS) for fire risk assessment and fire potential mapping in a peat swamp forest at Hua Sai district, Thailand. Fifty-five fire points in peat swamp areas were reported from 2012 to 2016. Analytic hierarchy process (AHP) and GIS methods were used synergistically to analyze the following contributing factors: elevation, slope, aspect, precipitation, distance from river, distance from settlement and land use. The results of the present study indicate that the predicted fire risk areas from the methodology proposed are found to be in agreement with recorded past fire events. The fire risk map produced can be used for planning and management of wildland fire events in the future. GIS multi-criteria-based models have been developed in the context of fire prognosis; however, most of them attribute weights from simple pair-wise comparisons; we showcase that the integration of AHP provides accurate results for this study area in Thailand.

Nowadays, analysis of land-use suitability requires consideration of variety of criteria including not only natural/physical capacity of a land unit but also socio-economic and environmental impact implications. This chapter suggests an approach instead of typical synthesis and land-use suitability assessment methods that is used in the urban and regional planning. Using the decision support systems with AHP and GIS, a participative, GIS-supported, different, new, flexible, and soft approach is proposed for land-use suitability assessment of cities and regions in particular. The chapter presents a technique integrating SWOT-CATWOE analysis, the Delphi and Inquiry Technique, the Analytical Hierarchy Process (AHP), and a Geographic Information System (GIS) to evaluate the land-use suitability for cities. By the help of this study, settlement suitability analyses have been achieved according to the socio-economic and infrastructure, environmental or physical thresholds of the settlement, and this integration could benefit urban planners and decision makers. The proposed method begins with the identification of settlement requirements, followed by the derivation of settlement evaluation criteria with SWOT-CATWOE analysis and the Delphi and Inquiry Technique. Then, pairwise comparisons (PC matrices) are formed between each pair of settlement criteria. The AHP is used to measure the relative importance or weight of each settlement criterion. This chapter has intended a theoretical and scientific base for an AHP and GIS combination with decision support systems. Thus, when land-use suitability assessment has taken as this combination of decision support systems, AHP and GIS, more realistic, more accurate, and applicable results emerge.