AHP Model Research Articles

An Integrated Fuzzy Delphi and Fuzzy AHP Model for Evaluating Factors Affecting Human Errors in Manual Assembly Processes

Human errors (HEs) are prevalent issues in manual assembly, leading to product defects and increased costs. Understanding and knowing the factors influencing human errors in manual assembly processes is essential for improving product quality and efficiency. This study aims to determine and rank factors influencing HEs in manual assembly processes based on expert judgments. To achieve this objective, an integrated model was developed using two multi-criteria decision-making (MCDM) techniques—specifically, the fuzzy Delphi Method (FDM) and the fuzzy Analytic Hierarchy Process (FAHP). Firstly, two rounds of the FDM were conducted to identify and categorize the primary factors contributing to HEs in manual assembly. Expert consensus with at least 75% agreement determined that 27 factors with influence scores of 0.7 or higher significantly impact HEs in these processes. After that, the priorities of the 27 influencing factors in assembly HEs were determined using a third round of the FAHP method. Data analysis was performed using SPSS 22.0 to evaluate the reliability and normality of the survey responses. This study has divided the affecting factors on assembly HEs into two levels: level 1, called main factors, and level 2, called sub-factors. Based on the final measured weights for level 1, the proposed model estimation results revealed that the most influential factors on HEs in a manual assembly are the individual factor, followed by the tool factor and the task factor. For level 2, the model results showed a lack of experience, poor instructions and procedures, and misunderstanding as the most critical factors influencing manual assembly errors. Sensitivity analysis was performed to determine how changes in model inputs or parameters affect final decisions to ensure reliable and practical results. The findings of this study provide valuable insights to help organizations develop effective strategies for reducing worker errors in manual assembly. Identifying the key and root factors contributing to assembly errors, this research offers a solid foundation for enhancing the overall quality of final products.

Geomatics Technology Education – Assessment of Learning Pedagogy

Abstract. The paper investigates multidisciplinary education and specialization at the master's level, analyzes assessment methods, and proposes a technique for evaluating geospatial technology education. It emphasises is on pedagogical approaches, and highlights the importance of capacity building to meet the growing demand for skilled professionals in spatial information management. The research provides guidelines for improving course content, structure, and teaching methodologies, aiming to enhance the quality and relevance of geospatial education for both students and stakeholders. This paper is based on online data gathered from 115 universities across the globe, who are imparting geospatial education, campus-based and e-learning, also a survey was conducted of two thousand students. It supported in analysis and suggestion to develop a specific robust technique for assessment of the geospatial technology education and provides the corrective measures to the users of the technique. It proposed a framework aimed at enhancing the course content, organization, and teaching methods substantially. Further an attempt was made to adopt AHP model for investigating the statistical approach. It was aimed to know the actual values and significance of each parameter used for analysis of the study. In order to prepare a common guideline for improving the course structure, course content and teaching methodology, ANFIS architecture (Artificial Neural Fuzzy-Inference System) was adopted. Spatial information represented in the form of thematic maps in relation with the respective attribute data in Geographical Information System (GIS) environment is now used by all spectrum of the society, be it government organizations, industry, and academia. The result of the study has designed the criteria and common guidelines, which may be implemented, would able to help and curtail the challenges of the geospatial education as global vision for Local Action.

Web-based Land Suitability Analysis for Horticulture Crop (Kiwi) in Champawat districts, Uttrakhand using MCDM and Geospatial Analysis

Identifying the suitability of a horticulture fruit with a defined area is an active research area, it has been attempted through different approaches, surveying and geographic information system are the two most popular techniques utilized extensively for this activity across the globe. GIS has its proven advantage over the field surveys based approach and modern GIS tools offers automation of the entire work flow for this activity. This study presents a web-based land suitability analysis for kiwi fruit cultivation in the Champawat District of Uttarakhand, using AHP, TOPSIS, and Ensemble modeling in conjunction with Multi-Criteria Decision Making (MCDM) and Geospatial Analysis. Land suitability was evaluated across various classes based on nine criteria viz. elevation, chilling hours, land use/land cover (LULC), soil texture, soil depth, temperature, rainfall, slope, and aspect. The AHP method identified 26.09 hectares as highly suitable, 14,606.19 hectares as suitable, 31,899.77 hectares as moderately suitable, 8,807.99 hectares as less suitable, and 192.23 hectares as not suitable. TOPSIS results showed 4,294.32 hectares as highly suitable, 14,193.54 hectares as suitable, 11,782.52 hectares as moderately suitable, and 2,399.21 hectares as less suitable. The ensemble method indicated 24.15 hectares as highly suitable, 8,763.51 hectares as suitable, 13,785.13 hectares as moderately suitable, 2,472.13 hectares as less suitable, and 191.94 hectares as not suitable. Integrating these findings revealed that the ensemble approach closely aligns with AHP in identifying highly suitable and less suitable areas, while TOPSIS emphasizes moderate suitability. This synthesis provides valuable insights for land use planning for kiwi cultivation. Additionally, an online spatial decision support system (SDSS) was developed using the Django framework, offering a modular and secure environment for informed decision-making.

Glacial Lake Outburst Flood Susceptibility Mapping in Sikkim: A Comparison of AHP and Fuzzy AHP Models

Glacial Lake Outburst Flood Susceptibility Mapping in Sikkim: A Comparison of AHP and Fuzzy AHP Models

AN INTEGRATED APPROACH TO IDENTIFY SUITABLE AREAS FOR THE LOCATION OF PUBLIC FACILITIES USING MULTI-CRITERIA ANALYSIS BASED ON GIS AND AHP IN THE CITY OF EL KHROUB, ALGERIA

Random and spontaneous urban growth is the result of massive natural population growth, as it is in all developing countries. As for our study air, it also results from the unloading of the mother city of Constantine to the satellite city of El-Khroub, which gave urbanization the power to take over its vast environment, An uneven distribution of public facilities in the city’s major districts, as well as traffic jams. This work attempted to determine the suitability of urban land for the location of public facilities in the city. It should be noted that land suitability assessment is a major factor in urban planning and management. Our land adequacy assessment is subject to the AHP model, calculating the weighting of various criteria including physical, socio-economic, environmental and urban. The final adequacy analysis revealed the proportion of land most suitable, estimated at 3.52% of the total area, covering mainly fallow land. The results of this study provide a detailed mapping of urban development potential, integrating both existing data and future projections.

Mapping of soil erosion risk in Ezeagu Local Government Area of Enugu State, Nigeria

This study centres on mapping soil erosion risk in Ezeagu Local Government Area of Enugu State, Nigeria. A multi-criteria research design was adopted in carrying out this study by using remote sensed images, topographic, soil and rainfall data. K Factor, R Factor, P Factor, K Factor and Digital Elevation Model were generated. SWAT model was used to generate surface runoff and sediment yield and AHP model were used to identify and map levels of soil erosion risk in the study area. Loamy sandy soil with a K Factor value of 0.23 – 0.34 (t h MJ-1 mm-1) and loam soil with a K factor Value of 0.08 – 0.14 (t h MJ-1 mm-1) dominates the study area. The organic matter contents for all the soils were rated low with an average measured organic matter of 0.97 (%). The rainfall erosivity factor (R-factor) results showed variations across the study area from 1029.295 to 1343.092, 1343.092 to 1589.713, 1589.713 to 1744.922, 1744.922 to 1965.777, and 1965.777 to 2060.864 MJ mm ha year-1, h-1 year-1. Areas with dense vegetation had lower P-factors indicating better protection against erosion, while areas under cultivation, especially those with poor management practices and without cover crops show higher P-factors. Almost all the area has a moderate (0.5-0.6) C factor which means moderate protection, areas with higher protection (0.6-1) C factor occupied a small portion towards the east while patches of low C factors are found scattered in the north, west northwest, south and eastern part of the study area. The eastern part of the study area are more susceptible to soil erosion with value ranging from 3.2-5.8, 5.9-9.9 and 10.0-19. Slope steepness and slope length is lower in the northern, western and south-west of the study area. Areas with annual soil loss between 0 to 10 grams, 10 to 20 grams and 30 to 40 grams dominates the northern, western and southern parts of the study area. The erosion risk map depicts that very low-risk area coverage of 24.06%, low risk covers 20.29%, moderate risk occupies 17.75% and high risk erosion risk covers 21.30% while very high risk occupies 16.61% of the total area. This study recommends terracing and gabions in areas identified at risk of erosion, promotion and adoption of agronomic soil conservation methods of mulching, cover cropping and planting plants to enhance soil stability and reduce erosion.

Geospatial analysis of alarmingly increasing flood vulnerability and disaster risk within the northeast himalaya region of India

Geoenvironmetally the eastern part of the Himalaya region is highly vulnerable to flood and other natural disasters as it consists of fragmented and tectonically active geology and geomorphology, very high monsoon rainfall (>360 cm) and subsequent runoff, rugged hilly terrain with high ranges of elevation and slope, dense drainage density etc. Other hand, the unplanned developmental activities keep going and scaling up this vulnerability and risk to floods and other disasters. Addressing this burning issue, a geospatial technology-based case study of the Kohima district, Nagaland state (India), is presented here. The geospatial "technology-based" analyses employed in the study are thematic GIS mapping of flood hazard, vulnerability and risk controlling factors; and performing overlay operation using the AHP model in GIS software to generate spatio-temporal map layers of flood vulnerability and disaster risk. Results reveal that the region is under a high rate of monsoon climate change (increasing temperature, rainfall, rainy days, rainfall events and flood events with an annual rate of 0.35 %, 1.12 %, 0.36 %, 2.67 % and 4 % respectively), land use degradation (increasing built-up area with 0.60 %, annual rate decreasing forest, shrubs and water bodies with 0.80 % accumulated annual rates respectively) and demographic changes (increasing urban as well and rural population density with 0.53–2.10 % and 0.55–2.14 % respectively). Accumulated impacts of climate change, land use degradation and demographic changes causing an increase in flood hazard, vulnerability and disaster risk. Flood hazard zones and vulnerability zones extending with 0.50 % (4.89 km2) and 0.84 % (8.16 km2) annual rates respectively, subsequently the flood risk zones categorized as a moderate, high and very high potential risk, have been spreading out with a yearly rate of 0.07 % (0.65 km2), 0.13 % (1.31 km2) and 0.03 % (0.33 km2) respectively. It decreases the area under low and very low-risk zones by 0.17 % (1.63 km2) and 0.07 % (0.65 km2) annual rates respectively. Following up on these annual rates, the spatial distribution of flood hazard, vulnerability and risk zones for the next decade (2031–2040) have also been projected, revealing alarming situations, if flood disaster risk reduction (F-DRR) measures were not implemented in timely. It is strongly believed that the proposed study will be very useful for district-level planners and administrators to implement sustainable development planning, for the scientific fraternity to enhance their research work in the field of flood disaster management and for individuals for their safety in terms of life and property.

Application of Geographic Information System (GIS), for Crisis Management

Natural disasters have always existed as a natural phenomenon throughout the life of the earth. The occurrence of natural disasters such as floods, earthquakes, storms, etc. in most cases have destructive effects on human settlements and heavy casualties on their residents. It has destroyed the buildings and infrastructures of such areas and imposed unfortunate economic and social consequences on cities and countries. Despite many scientific advances, mankind is still not able to prevent and resist these natural events. Natural disaster management and sustainable development are considered an integrated issue today. Due to limited resources, real development will not be possible without integration with disaster reduction programs. Earthquakes as a natural phenomenon do not have adverse results by themselves. What makes this phenomenon a disaster is the lack of prevention and lack of preparation to deal with its consequences. Therefore, one of the most necessary measures is to apply "principles of crisis management". Crisis management measures can be summarized in three parts: 1. Prevention, 2. Response, and 3. Reconstruction. Therefore, the title is the most important discussion in the strategy of reducing the effects of earthquakes. In this research, we seek to find the best location for crisis management support bases in Malair City, which first identified the effective factors and criteria in the location of relief centers during a crisis. Then, the AHP model was used to determine the importance and value of each criterion and effective elements in the decision, and a questionnaire was designed and distributed among experts and specialists. In the next step, the weight of each of the decision criteria and elements was determined using the hierarchical analysis process method and Expert Choice software. Then, using the field method, figures of the studied area were updated and prepared. In the next step, all information layers were converted to raster in the geographic information system (GIS). Finally, using the Index overlay method, the layers were combined. Three locations were suggested as the best locations for crisis management support bases in Malayer City. Among them, two options, one in the eastern part of the city on Molvi Street, and the other in the southern part of the city on Motahari Street, have been proposed as the best options. In terms of accessibility, they are in a good position. An option, that has a lower score, is located in the southeastern part of the city on Sheikh Kilini Street.

Research on Underwriting Decision-Making of Insurance Companies in Areas with Frequent Extreme Weather Based on Comprehensive Evaluation Method

The purpose of this research is to develop an insurance company underwriting model by pre-processing and model construction of collected data in order to assess whether to underwrite insurance in extreme weather-prone areas and to analyse the factors that influence underwriting decisions. In this paper, data such as insurance company payout rate, number of insured, homeowners' income in selected areas, health insurance coverage, year of construction of historical landmarks, GDP per capita, and tourism income were processed, and minimum-maximum normalisation and zero-mean normalisation were used to eliminate differences in feature magnitude. In the model construction, the logistic regression model and BP neural network were used to derive the underwriting probability, and the three main factors of natural disaster risk assessment, payout rate, and homeowner influence were introduced, and the relationship between these factors and the underwriting probability was described by the logistic distribution function, which determined that the underwriting probability should be underwritten when the underwriting probability Pi≥0.5. The natural disaster risk assessment model selects disaster factors, disaster environment and disaster receptors as assessment indicators, constructs the CEDP model, and calculates the weights using the AHP model, the Topsis model and the CPITIC weighting method, and carries out fuzzy clustering analysis on the CEDP index of 25 regions to classify the risk into five levels. For insurer profits, solvency, premium income and claims ratios were analysed, ratios based on annual claims to total premiums were calculated, and the impact of homeowners' incomes, property and historic buildings on underwriting decisions was assessed. Insurance company underwriting decision factors in areas prone to extreme weather are ultimately determined.

Delineation of groundwater potential zones using multi-criteria analysis (AHP), frequency ratios (RF), remote sensing and GIS: a case study of the Batcham municipality (west Cameroon)

Groundwater resource management and development should be done sustainably, which calls for accurate assessment based on new methods and scientific principles. There is an increasing demand for potable water supplies, to meet the woefully inadequate domestic water needs in the Batcham municipality (west of Cameroun). The dearth of knowledge on sustainable management of water resources is to blame for this predicament. As integrated methodologies are not used in groundwater exploration programs, the current problem has gotten worse. Innovative scientific principles of groundwater resource exploration are required to effectively counteract the non-rationalization of water and the problem of unacceptable failure rates in drilled water borehole development. This will improve the appropriate and sustainable use of these resources. Therefore, the goal of this research is to map groundwater potential zones by utilizing readily available datasets and remote sensing (RS), GIS, Frequency Ratios (FR), and multi-criteria analysis (AHP) techniques. The database used is made up of geological data, hydroclimatic data, well data, and satellite images. Each of the methods used is based on the study of the relationships between the factors controlling the groundwater potential. Among these factors, ten (10) were retained based on previous work; these are slope, elevation, land use, land cover, lineament density, drainage density, topographic wetness index, curvature, geology, rainfall, and the static water level. The AHP allowed, according to the user's expertise, to assign weights to each factor controlling the water potential. The FR made it possible to study the relationships linking each variable with high flow rates. The thematic layers obtained were integrated into a GIS environment to generate the groundwater potential map. Four classes of groundwater potential have been identified: bad, moderate, good, and excellent. The bad classes represent 8.32% and 11.21%; moderate 36.57% and 28.70%; good 43.55% and 38.93%; and excellent 11.56% and 21.16%, for the AHP and FR models, respectively. The overlying of wells with high flow rates on areas of excellent groundwater potential shows perfect concordance, which validated the final map. Likewise, the resulting map was validated by sensitivity curve analysis, and the receiver operating characteristic (ROC) curve from which result accuracy was obtained is 70.63% and 80.28% for the AHP method and FR method, respectively. Finally, the FR model outperformed the AHP model in terms of performance and it is possible to use these dependable models to describe groundwater potential zones in the other regions of Cameroon.

GIS-based analysis of relationship between building density and capacity of urban streets

Governments adopted the policy of increasing accumulation in cities in order to maximum use of desired lands of city districts and to prevent from city buildings in the environment created subsequent to the horizontal city developments. One of the basic foundations that must be evaluated while the population accumulation of capability increase, is the traction ability of accountability communication network in both public and private transport system to new travels created by any new user introduction. In this paper, we discussed about the relation between accumulation and traffic capacity of city streets with regard to a case study of Imam Khomeini Street in Tabriz city, Iran. This relation has been modeled with Logistic and AHP models. After investigating the service level of the street for 14 consecutive hours it is evident that the traffic is saturated at the peak hours and based on this study the suggestion for density increase is eliminated. Because the density increase is possible when v/c

Assessment of Forest Fire Risk in Mazandaran Province Using Fuzzy AHP Model

Assessment of Forest Fire Risk in Mazandaran Province Using Fuzzy AHP Model

AN INTEGRATED APPROACH TO IDENTIFY SUITABLE AREAS FOR THE LOCATION OF PUBLIC FACILITIES USING MULTI-CRITERIA ANALYSIS BASED ON GIS AND AHP IN THE CITY OF EL KHROUB, ALGERIA

Random and spontaneous urban growth is the result of massive natural population growth, as it is in all developing countries. As for our study air, it also results from the unloading of the mother city of Constantine to the satellite city of El-Khroub, which gave urbanization the power to take over its vast environment, An uneven distribution of public facilities in the city’s major districts, as well as traffic jams. This work attempted to determine the suitability of urban land for the location of public facilities in the city. It should be noted that land suitability assessment is a major factor in urban planning and management. Our land adequacy assessment is subject to the AHP model, calculating the weighting of various criteria including physical, socio-economic, environmental and urban. The final adequacy analysis revealed the proportion of land most suitable, estimated at 3.52% of the total area, covering mainly fallow land. The results of this study provide a detailed mapping of urban development potential, integrating both existing data and future projections.

A Novel Visual System for Conducting Safety Evaluations of Operational Tunnel Linings

Based on the lining structure of an operational tunnel, the AHP and Fuzzy mathematical models were used to determine the weight of the evaluation index and solve the membership matrix. The weighted-average Fuzzy comprehensive function was used to combine the two, and the Fuzzy–AHP evaluation model was built and programmed. According to the self-developed Fuzzy–AHP evaluation-programmed model, a visualized structure safety evaluation system for operational tunnels was developed by using MATLAB. The system’s functional design, program development, and computational visualized interface were implemented, and key codes were provided. The system can be divided into four modules: data management, fuzzy computation, predictive analysis and key disease indexes to focus on. In addition, the system can easily edit and modify the evaluation function, which includes not only the Fuzzy evaluation but also other types of evaluation functions applicable to other practical engineering projects, improving the applicability of the system. After that, the system was applied to the structure safety evaluation of a mountain tunnel, which provided the evaluation results and key indexes to focus on in the tunnel. Finally, the rationality of the system design was verified by constructing the corresponding BP–RBF combined neural network. This study provides a reference for the establishment of an intelligent structure safety warning system for operational tunnels.

Simulation of Groundwater Potential Zone Using Geographic Information System (GIS) Through Related Factors

Groundwater is the primary water source for irrigating and drinking in dry seasons. This work was examined to assess groundwater potential area underlain by basement complex with GIS based approach of selected locations in Osogbo. The soil samples were taken and soil textural and permeability analyses were done in the laboratory. Supervised classification analysis was done on LandSAT imagery to generate Land use and a lineament map, surface analyst algorithm was applied on ASTER dam to generate elevation map. Hydraulic conductivity and overburden thickness maps were generated from the Borehole data parameters. Interpolation method was used to generate spatially spread clay, silt, sand, rainfall and hydraulic conductivity. Multi-criteria analysis was used to generate groundwater potential zone map in the study area. Specific factors were considered for groundwater potential zone. Reclassification was done on each of the considered factors and AHP model was used to assign weight to all the factors. The results of the various factors responsible for groundwater potential include lineament density 0-0.0028; sand 67.2-89.60%, silt 9.00-30.00%, clay 0.17-2.80%, permeability 0.000010-0.00002, rainfall 1304.02-1469.06mm/yr, hydraulic conductivity 0.21-0.96m/min, land use consisting of degraded forest 48.65%, riparian forest 13.05%, built up 38.29%, and water body 0.001%. However, ground water potential of the study area was assessed and classified into fair, good and very good with the coverage of 2%, 80% and 18% respectively. Conclusively, the groundwater recharge potential is very good at Ofatedo, Gbonmi and Oke-Oro locations, good at Awosuru, Gbodofon and Dagbolu locations, but fair at Mallam Tope location in Osogbo

Research on landslide hazard assessment based on improved analytic hierarchy process optimizing multiple rainfall indicators

Rainfall is the key factor that leads to landslide, so this study introduces multiple rainfall indexes to optimize the rainfall model in view of the single evaluation index of the rainfall model for landslide hazard assessment. In this study, Xiangxiang City of Hunan Province was selected as the study area, and eight types of susceptibility assessment factors including slope, aspect, elevation, normalized vegetation index (NDVI), road, fault, lithology and land use were extracted. By analyzing the characteristics of local rainfall, six types of rainfall induced assessment factors were selected for hazard assessment of the study area. The two types of evaluation factors were substituted into the improved AHP and RF combined weighting models respectively to obtain the susceptibility zoning map and rainfall induced model of the study area, and finally superimposed to obtain the hazard zoning map of the study area.Using ROC curve and hazard zoning in the studied area test results, the results show that:The AUC value of the multi-rainfall index is 17.7% higher than that of the single rainfall index, and the AUC value of the improved AHP is 6% higher than that of the traditional AHP method. It is verified by the disaster points on the day of extreme rainfall in the study area, and the actual occurrence of the disaster points is basically consistent with the hazard evaluation and zoning of the multi-rainfall index. Therefore, the rainfall model of landslides is optimized by using multiple rainfall indexes, which significantly improves the rationality of landslide hazard assessment.The study of multiple rainfall induced indicators can fill the knowledge gap in the current field, provide new insights and understanding for the field, and provide assistance for predicting and preventing landslides in related areas.

Mapping of Orogenic Gold Mineralization Potential in the Kushaka Schist Belt, Northcentral Nigeria: Insights from Point Pattern, Kernel Density, Staged-Factor, and Fuzzy AHP Modeling Techniques

Mapping of Orogenic Gold Mineralization Potential in the Kushaka Schist Belt, Northcentral Nigeria: Insights from Point Pattern, Kernel Density, Staged-Factor, and Fuzzy AHP Modeling Techniques

Integrated frequency ratio-analytical hierarchy and geospatial techniques-based earthquake risk assessment in mountainous cities: a case from the Northwestern Himalayas

ABSTRACT Earthquake risk management (ERM) needs proper planning and mitigation measures to minimise adverse impacts. In this context, we quantify the earthquake risk based on hazard, exposure, and vulnerability in the Northwestern Himalayas, Pakistan. A complete earthquake catalogue along with topographic, geo-environmental, seismic, and social causative factors were integrated into a geospatial environment for earthquake risk profiling. The integrated frequency ratio-analytical hierarchy process (FR-AHP) techniques were employed to measure the causative factor weights and historical earthquake distribution within the causative factor classes for hazard assessment. Simultaneously, AHP was utilised to calculate the vulnerability. The exposure was obtained by integrating the hazard and the land use map to estimate damage and loss. Finally, the risk was estimated and mapped across the study area at high resolution. The developed AHP model for vulnerability and hazard showed high accuracy for training and validation data sets (i.e. 98% and 93%, respectively). While there is an evident geographic disparity in the estimated risk, the results show that ∼25% of areas fall under the “very high-risk” zones where population and building density are high near active fault zones. The current study offers actionable insights for risk-reduction initiatives in the mapped high-risk zones.

Existing Green Port Sustainable Practices under Fuzzy AHP Model: A Case Study of Karachi Port

Maritime transport drives globalization and international trade. Ports worldwide handle 80% of seaborne trade by volume and 70% by value. Sustainable development is more important due to unexpected worldwide environmental changes. Ports are vital to economic progress. Port construction and operation polluted the environment, prompting the green concept. The present study used the "Fuzzy AHP Model"to assess Karachi Port's sustainable green port practices based on previous research. The study identified five key characteristics of a green port: little hazardous waste handling, a weak air and water pollution control system, poor port greenery, and habitat quality maintenance below international standards at Karachi port. Future research should create and apply solutions to improve this study's prioritized features. Innovative technology, policies, and collaborations can sustain green ports. Port and regional studies uncover green port best practices and contextual differences. Monitor and evaluate strategies to adapt to changing environmental standards and maritime transport issues.

Application of optical images and analytical hierarchy process model for solid waste dumping site analysis in Kombolcha town, Northeastern, Ethiopia

Improper open dumping of solid wastes caused different serious problems in fast-growing towns in Ethiopia like Kombolcha town. This unsuitable solid waste dumping management brings health challenges by spreading diseases, contaminating water, polluting air, and spreading of different disease-causing insects such as mosquitoes. Therefore, selecting suitable solid waste dumping site analysis (SWDSA) is very essential to minimize these negative effects related to improper solid waste dumping in such towns. The primary goal of this study is to use optical images and the AHP model to find appropriate solid waste dumping sites in Kombolcha Town. The nine governing factors such as soil texture, geology, faults, groundwater well points (GWWPs, rivers, roads, built-up, Land use land cover (LULC) and slopes, were considered to achieve the aim of this study. These factors were extracted and delineated from the various optical data such as Landsat 8 images, digital elevation model, Google Earth images, geological map, soil map, and also field survey. The factor classes and factors were ranked and weighted utilizing a comparison matrix according to importance and finally by applying the AHP spatial analysis extension tool in Arc GIS software the SWDSA map of the study area was generated. Therefore, as a result of this study about 19.4 km2 (22.8 %), 22.8 km2 (26.8 %), 20.5 km2 (24.1 %), 16.1 km2 (18.9 %), and 6.2 km2 (7.3 %) of the study area falls in not suitable, less suitable, moderately suitable, suitable and highly suitable ranges respectively. Based on the result of this further analysis, D is the 1st suitable site with a score is 83.6 %, site B is the 2nd suitable site is a score is 83.2 %, site C is the 3rd suitable site with a score of 65.1 % and site A is the last suitable site and scored 60.4 %. Therefore, this study strongly recommends that the waste management municipal office of Kombolcha town and other concerned government and non-government bodies apply and consider these identified the best suitable solid waste dumping sites.