GIS-based Analytic Hierarchy Process Research Articles

Exploring a GIS-based analytic hierarchy process for spatial flood risk assessment in Egypt: a case study of the Damietta branch

Floods are the most common and costly disasters worldwide, while spatial flood risk assessment is still challenging due to fewer observations and method limitations. In this study, the flood risk zonation in the Nile districts of the Damietta branch, Egypt, is delineated and assessed by integrating remote sensing with a geographic information system, and an analytical hierarchy process (AHP). Twelve thematic layers (elevation, slope, normalized difference vegetation index, topographic wetness index, modified normalized difference water index, topographic positioning index, stream power index, modified Fournier index, drainage density, distance to the river, sediment transport index, and lithology) are used for producing flood susceptibility zonation (FSZ) and six parameters (total population, distance to hospital, land use/land cover, population density, road density, and distance to road) are utilized for producing flood vulnerability zonation. Multicollinearity analysis is applied to identify highly correlated independent variables. Sensitivity studies have been used to assess the effectiveness of the AHP model. The results indicate that the high and very high flood risk classes cover 21.40% and 8.26% of the area, respectively. In 14.07%, 27.01%, and 29.26% of the research area, respectively, flood risk zones classified as very low, low, and moderate are found. Finally, FSZ is validated using the receiver operating characteristics curve and area under curve (AUC) analysis. A higher AUC value (0.741) in the validation findings demonstrated the validity of this AHP approach. The results of this study will help planners, hydrologists, and managers of water resources manage areas that are susceptible to flooding and reduce potential harm.

GIS-based AHP and MCDA Modeling for Cropland Suitability Analysis: A Bibliometric Analysis

The ' Land Suitability Analysis ' is a useful management method for ensuring that agricultural lands are utilized sustainably and planned based on their potential. Geographic Information Systems (GIS) and the Analytic Hierarchy Process (AHP) for cropland suitability analysis have seen substantial contributions from researchers worldwide. This combination assesses and maps the suitability of land for different crops by utilizing the multi-criteria decision analysis (MCDA) strengths of AHP and the spatial analytic capabilities of GIS. This Bibliometric analysis involves examining publications to identify patterns and trends, such as the most prolific authors & Countries, influential journals, and highly cited papers. It helps in understanding the development and current state of a research field. Using Biblioshiny software, the researchers obtained 183 publications of 687 authors and 319 different institutions using the bibliographic information from the Scopus database. The bibliometric analysis uses the following subcategories: Country, Authors, Publication Sources, Annual Scientific Production, and keywords. By examining the outcomes of bibliometric analysis, methodology, and applications, it was discovered that AHP and MCDA are the most often utilized techniques in this respect. Also, the findings indicated a rising number of publications and a growing interest in the subject, especially in recent years. Over the previous 23 years, the overall trend of publications in this field grew gradually at an annual growth rate of 21.81%. Asian nations, especially China, India, and Iran, have had the biggest influence on the nation's scientific output in the discipline. During this period, India and Iran had the most research papers published. In addition, "GIS," "Land Suitability," and "AHP" are the top three most often used terms. Future trends in this subject are predicted by the current keywords: "GIS," "Land Suitability," "AHP," and "Remote Sensing." Moreover, this exhaustive investigation provides a basis for comprehending the present status and future direction of GIS-based cropland suitability research. These discoveries offer valuable insights for future modeling and research endeavors on the subject and aid in identifying research gaps in the existing literature.

Investigation of GIS-based Analytical Hierarchy Process for Multi-Criteria Earthquake Risk Assessment: The Case Study of Kahramanmaras Province

The risk level that earthquakes pose to the environment depends on different factors. Correctly analyzing the effects of these factors is an important step to identify risky areas before the earthquake. Geographic information systems (GIS) provide essential tools for determining the weights of these factors, analyzing them, and creating risk maps. Two devastating earthquakes occurred in Türkiye in February 2023, centered in Kahramanmaras. In this study, a research was carried out to estimate the damage caused by the earthquake in Kahramanmaras by analyzing pre-earthquake data with GIS. The determined factors are seven: fault line risk zone, epicenter risk zone, depth of the magnitude, slope, curvature, population density and building density. These factors have created different weighting scenarios with the Analytical Hierarchy Process (AHP). As a result of the analyses, risk maps were produced. Evaluations were made by comparing the risk maps produced with DPM. Considering all the factors, these results highlight the importance of considering multiple risk criteria when evaluating the potentiality of damage in the study region.

Delineation of potential zones for groundwater recharge using integrated GIS-based AHP and CSI techniques in Ogun Waterside, Southwestern Nigeria

ABSTRACT Ogun Waterside region of southwestern Nigeria experiences seasonal water stress stemming from groundwater overdraft. Therefore, it became imperative to effectively manage the existing groundwater resources to fulfill the anticipated demand for potable water. To achieve this goal, an analysis involving seven spatial parameters: geomorphology, land use/land cover, slope, lineament density, drainage density, soil types, and geology was conducted. These parameters were examined using a combination of geographic information system (GIS)-based analytical hierarchy process (AHP) and cumulative score index (CSI) techniques to delineate potential zones for groundwater recharge. The AHP methodology was employed to assign relative weights to the thematic layers and their corresponding features, reflecting their importance. The AHP results were integrated using a weighted linear combination within a GIS environment to generate the groundwater recharge potential map. Further, the CSI was used to reclassify the composite groundwater recharge potential map. The resultant map revealed three zones which were classified into high, moderate, and low potential zones founded on the CSI approximation. About 98.56 km2 (8.28%) of the study area is categorized as having low potential, 803.77 km2 (67.54%) falls within the moderate potential zone and 287.71 km2 (24.18%) falls in the high potential zone.

GIS-Based Analytical Hierarchy Process for Identifying Groundwater Potential Zones in Punjab, Pakistan

The quality and level of groundwater tables have rapidly declined because of intensive pumping in Punjab (Pakistan). For sustainable groundwater supplies, there is a need for better management practices. So, the identification of potential groundwater recharge zones is crucial for developing effective management systems. The current research is based on integrating seven contributing factors, including geology, soil map, land cover/land use, lineament density, drainage density, slope, and rainfall to categorize the area into various groundwater recharge potential zones using remote sensing, geographic information system (GIS), and analytical hierarchical process (AHP) for Punjab, Pakistan. The weights (for various thematic layers) and rating values (for sub-classes) in the overlay analysis were assigned for thematic layers and then modified and normalized using the AHP. The result indicates that about 17.88% of the area falls under the category of very high groundwater potential zones (GWPZs). It was found that only 12.27% of the area falls under the category of very low GWPZs. The results showed that spatial technologies like remote sensing and geographic information system (GIS), when combined with AHP technique, provide a robust platform for studying GWPZs. This will help the public and government sectors to understand the potential zone for sustainable groundwater management.

Balancing Environmental and Human Needs: Geographic Information System-Based Analytical Hierarchy Process Land Suitability Planning for Emerging Urban Areas in Bni Bouayach Amid Urban Transformation

Urbanization in Bni Bouayach, Morocco, threatens vital irrigated areas and agricultural land, raising concerns about environmental sustainability. This study employs a GIS-based Analytical Hierarchy Process (GIS-AHP) framework to assess land suitability for sustainable development. It addresses knowledge gaps in urban planning as follows: (i) Evaluating land suitability for sustainable development: this analysis identifies areas appropriate for urban expansion while minimizing environmental impact. (ii) Balancing environmental and human needs: the framework integrates ten criteria encompassing accessibility, economic, social, geomorphological, and environmental factors. This comprehensive approach results in a Land Suitability Map with five categories: prohibited/unfit, extremely unsuitable, moderately unsuitable, adequately suitable, and highly suitable. Notably, 39.5% of the area falls within the adequately suitable or highly suitable categories, primarily consisting of accessible bare lands and pastures. These findings provide valuable insights for policymakers to guide Bni Bouayach towards sustainable urban development, ensuring balanced growth that respects both environmental preservation and resident needs.

Geospatial insights into Alphonso mango cultivation: a comprehensive land suitability study in the coastal belt of Maharashtra, India.

Land suitability assessment is integral to the advancement of precision agriculture. This inquiry is focused on identifying optimal regions for cultivating Alphonso mango in the coastal belt of Maharashtra, spanning across Palghar, Raigad, Thane, Ratnagiri, and Sindhudurg districts. Employing a GIS-based Analytic Hierarchy Process (AHP) methodology, 10 crucial parameters have been considered, encompassing climatic, physical, and chemical soil characteristics: cation exchange capacity, organic carbon, slope, rainfall, soil pH, soil texture, mean annual soil temperature, base saturation, soil drainage, and soil depth. Weights are assigned to these parameters based on expert opinions and existing literature to determine their significance in developing a soil suitability map. The study reveals distinct land suitability zones for Alphonso mango cultivation. The land suitability map designates 25.78% of the study area as highly suitable, while 9.18% is considered unsuitable for Alphonso mango cultivation. To validate the study, the Receiver Operating Characteristic (ROC) curve has been employed, indicating an 83% approval rate for the reliability and performance of the soil suitability. The results categorise soil suitability classes, providing valuable insights for farmers and agricultural planners to make informed decisions regarding Alphonso mango cultivation in similar geoenvironmental regions.

Assessment of spatial cyclone surge susceptibility through GIS-based AHP multi-criteria analysis and frequency ratio: a case study from the Bangladesh coast

Tropical cyclones, including surge inundation, are a common event in the coastal regions of Bangladesh. The surge washes out the area within a very short period and remains in flooded condition for several days. Spatial analysis to understand the surge susceptibility level can assist the cyclone management system. Surge susceptibility analysis could be one of the most essential parts of disaster risk reduction through which cyclone vulnerability can be minimized. A Geographic Information Systems-based analytical hierarchy process (AHP) multi-criteria analysis and bivariate frequency ratio (FR) techniques were conducted to understand the surge susceptibility level of a cyclone-prone area on the Bangladesh coast. A total of 10 criteria were considered influential to surge flooding, i.e. Topographic Wetness Index, elevation, wind velocity, slope, distance from sea and rivers, drainage density, Land Use and Land Cover, Normalized Difference Vegetation Index, precipitation, and soil types. The final surge susceptibility maps were categorized into five classes, i.e. very low, low, moderate, high, and very high. Conferring to these susceptibility classes, policymakers can make decisions for future land use management and disaster risk reduction activities. According to this research, AHP showed better precision (Receiver Operating Characteristic) than FR for surge susceptibility prediction on the Bangladesh coast.

Spatio-Temporal Analysis of Erosion Risk Assessment Using GIS-Based AHP Method: A Case Study of Doğancı Dam Watershed in Bursa (Türkiye)

Soil erosion, one of the most serious phenomena in watershed management, can be estimated based on various criteria. Land use change is one of the most important factors affecting the susceptibility of soil erosion. In this study, the effect of land use change on soil erosion risk in two plan periods (2005 and 2017) was investigated using Analytical Hierarchy Process (AHP) and Geographic Information Systems (GIS) for the forest planning units in the Doğancı Dam Watershed, located in Bursa, Türkiye. Eight criteria were evaluated including erosion-related slope, bedrock type, land use/land cover, precipitation, relative relief, aspect, drainage frequency, and density. According to the results, the most effective factor in soil erosion was slope (0.29), while bedrock type and land use/land cover ranked second with 0.19. It was found that full closure forests were characterized by high erosion resistance (0.3), while bare land was characterized as the most sensitive area to erosion (0.39). In terms of spatio-temporal changes in a 12-year period, the areas in the medium and high erosion risk decreased, while low and very low-risk areas increased. The ROC method showed a satisfactory accuracy of 72.8% and 80.2% for the 2005 and 2017 erosion risk maps, respectively.

GIS-Based Analytical Hierarchy Process Modelling and Mapping of Erosion Vulnerability in the Coastal Areas of Rivers State, Nigeria

The problem of coastal erosion in rivers State Nigeria is a significant issue that has far-reaching consequences for the environment and local communities. Despite the efforts of previous research there remains a lack of comprehensive understanding of the factors contributing to erosion vulnerability and their relative importance, hindering effective decision-making and management practices aimed at mitigating the effects of coastal erosion in Rivers State. Therefore, this study aimed at a GIS-based analytical hierarchy process modeling and mapping of coastal erosion vulnerability in Rivers State, Nigeria. The objectives are to establish and classify the geophysical factors according to the levels of coastal erosion risk, calculate the reliability index of the classified geophysical factors, determine the coastal vulnerable areas across Rivers State using analytical hierarchical process and to produce a coastal vulnerability index map defining the extent of erosion vulnerability in Rivers State. The methodology comprises of the acquisition of primary and secondary data, image pre-processing, image classification, DEM processing, classification and standardization of factors, development of pairwise comparism, and weighted linear combination analysis. The study revealed three distinct coastal erosion vulnerability zones: high, moderate, and low vulnerability. The high vulnerability zone encompassed a total expanse of 545.29 square kilometers, constituting 6.38% of the study area. In contrast, the moderate and low vulnerability zones covered 1941.33 square kilometers and 6052.51 square kilometers, respectively, making up 22.73% and 70.89% of the total area. Bonny (139.28 sq km) was ranked as the most vulnerable due to its role as an oil and gas hub. Degema (111.28 sq km) ranked second and requires urgent erosion control. Okrika and Andoni (71.73 sq km and 62.20 sq km) were third and fourth respectively. It is recommended that an advocate for the systematic approach to coastal vulnerability zoning be introduced in the study. The categorization of areas into high, moderate, and low vulnerability zones provides a standardized framework for assessing coastal regions' susceptibility to erosion. This approach can be applied to other regions to facilitate consistent vulnerability assessments.

Earthquake Risk Assessment Using GIS-Based Analytical Hierarchy Process (AHP): The Case of Bitlis Province (Türkiye)

The risk level of natural disasters such as earthquakes depends on many factors. Some of these are direct hazards, while others are vulnerability factors that increase the risk. In this regard, risk assessment should be performed by evaluating the hazard and vulnerability factors together. The Analytical Hierarchy Process (AHP) is a powerful tool for co-evaluating such multiple decision criteria. The spatial visualization of the results facilitates the direct assessment of risks as well. In the present study, the seismic risk assessment of the Bitlis province in Eastern Anatolia, which has a high seismic risk, was performed by using the GIS-based AHP method. Among many criteria, six effective criteria on earthquake risk such as seismicity, demographic and topographic criteria were taken into consideration based on expert decision makers. It is concluded that the results obtained from the study were quite successful in terms of determining the seismic risks of the study area. Accordingly, while the risks are high in densely populated settlements with high peak ground acceleration (PGA), the risk decreases according to soil and land use.

Soil erodibility mapping of hilly watershed using analytical hierarchy process and geographical information system: A case of Chittagong hill tract, Bangladesh

Soil erosion across watersheds and river basins is an alarming environmental deterioration process that poses severe risks to hydrological systems, hydrogeochemical processes, agricultural productivity, and the global natural ecosystem. The use of the Analytical Hierarchy Process (AHP) and Geographical Information System (GIS) to assess soil erosivity for the watershed is widely known. This study applied the AHP and GIS to understand the degree of erosivity of the hilly Karnaphuli watershed in Chattogram, Bangladesh. The study used topographical maps, soil maps, and satellite imagery datasets. It implemented the GIS-based AHP and weighted overlay technique to derive eight factors (slope, elevation, Stream Power Index (SPI), Land Use and Land Cover (LULC), curvature, soil, Topographic Wetness Index (TWI), and rainfall. The geological stage of erosion potential was also identified using Digital Elevation Model (DEM) data through GIS-based hypsometric analysis. The findings demonstrated that the eastern and north-western parts are particularly vulnerable to erosion compared to other parts of the study area. The most dominant variables identified to influence the process of soil erosion are slope, LULC, elevation, and SPI. According to the AHP analysis, slope was the most influential factor (26%), followed by LULC (23.8%), elevation (20.3%), and SPI (13.9%) in the soil erosion process, and the geological stage of erosion potential was determined from the hypsometric curve (S-shaped) and hypsometric integral (0.49), which revealed that moderately eroded areas characterized the whole research region. The findings are significant as they provide valuable information for researchers and planners to address soil erosion and develop measures to control it effectively.

Delineation of groundwater potential zone using remote sensing and GIS-based AHP for sustainable groundwater management in Aceh Besar Regency, Aceh Province, Indonesia

Sustainable groundwater management is crucial for ensuring the long-term availability of water resources and supporting socio-economic activities. As water demands increase and hydrological systems become more complex, accurately identifying groundwater potential zones is essential for effective resource planning and utilization. However, the in-situ data availability is often very limited, particularly on a regional scale. To solve this problem, this study aimed to delineate groundwater potential zones in Aceh Besar Regency using remote sensing and a GIS-based AHP (analytical hierarchy process). Several factors were used to determine groundwater potential zones, including lithology, land use/land cover, slope, lineament density, drainage density, rainfall, and soil type. Each factor was weighted based on an extensive literature review and knowledge-driven decision-making techniques. The results indicated that 26.35% of the area was classified as having low groundwater potential, whereas 53.86% was classified as moderate. Areas that have high to very high groundwater potential cover 16.76% to 3.04% of the Aceh Besar territory. The high groundwater potential zones were mostly located in alluvial and clastic sediments lithology, gentle slopes, and had high annual rainfall. Meanwhile, areas with igneous and metamorphic lithology as well as steep slopes, had moderate to low groundwater potential. Validation was carried out by collecting the high-yield existing production wells and calculating the area under the curve (AUC) of the receiver operating characteristic (ROC) curve with relatively good accuracy (74.5%). This research has effectively described the spatial distribution of groundwater potential, contributing to sustainable groundwater management and enabling informed decision-making for sustainable groundwater practices.

Identification of groundwater potential zones using integrated GIS-based analytical hierarchy process and multicriteria decision analysis methods in Jedeb watershed, Ethiopia

Identification of groundwater potential zones using integrated GIS-based analytical hierarchy process and multicriteria decision analysis methods in Jedeb watershed, Ethiopia

Forest Fire Risk Mapping Using GIS Based Analytical Hierarchy Process Approach

Turkiye is located in a region sensitive to forest fires due to the Mediterranean climate, vegetation and topography of the south and west coasts. Every year, forest fires for various reasons cause thousands of hectares of forest area to be burned. Fires damage the ecosystem as well as have economic consequences. While the Mediterranean, Aegean and Marmara coasts, where the Mediterranean climate and fire-sensitive tree species are dominant, are at primary risk against forest fires, the forests located on the Black Sea coasts where the Black Sea climate is dominant are less risky in terms of fire. For an effective fight against forest fires, it is crucial to identify zones with fire risk based on various parameters such as forest structures (tree species, crown closure, stand age), topographic features (slope, aspect), climate, and proximity to certain points (such as roads, settlements, agricultural areas). Fire risk data will shed light on the measures that can be taken against fire. In this study, GIS (Geographic Information Systems) based Analytical Hierarchy Process (AHP) method, one of the well know MCDA (Multi-criteria Decision Making Analysis) methods, was used to develop the fire risk map of Mersin Forestry Regional Directorate (FRD) within the Mediterranean region of Turkiye. Then, the accuracy of the fire risk map was evaluated by taking into account the previous fires in the regional directorate. As a result, it was found that 13.87% of the study area was classified as very high, 25.87% high, 24.68% medium, 22.44% low and 13.14% very low risk areas. The results showed that tree species are the most effective risk factor in forest fires, and followed by stand age factor. The accuracy of the fire risk map was evaluated by using the location information of a total of 562 fires in Mersin FRD between 2003-2022 that damaged forest areas. In order to determine the accuracy of the fire risk map, ROC (Receiver Operating Characteristic) curve method was used in ArcGIS environment. As a result, the AUC (Area Under Curve) value was found to be approximately 74%, and these values showed that the fire risk map developed for Mersin FRD was moderately reliable. With this study, it has been demonstrated that it is possible to produce reliable fire risk maps in a short time using the GIS-based AHP method.

GIS-Based Analytical Hierarchy Process Modeling for Flood Vulnerability Assessment of Communities Along Otamiri River Basin Imo State, Nigeria

In recent times, communities along the Otamiri River Basin in Imo State have been grappling with flooding issues, especially during the rainy season. This occurs despite the presence of underground drainage systems. The primary concern is heavy rainfall causing the river to overflow and lead to flooding. Hence the study aimed at identifying the flood-prone areas in the Otamiri River Basin in Owerri, Imo State. The objectives are to establish factors for evaluating flood vulnerability within the study area; to classify and standardize the factors according to levels of vulnerability; to determine the reliability of the classified factors; and to produce a flood vulnerability map showing vulnerable areas in the study area. The methodology involved collecting Shuttle Radar Topography Mission and Sentinel 2A imagery of July 2022, and processing the data with ArcGIS and QGIS software to determine the topography and vulnerability areas through geo-referencing and classification. The Analytical Hierarchy Process (AHP) model was employed to identify high flood risk areas, considering factors like drainage density, slope, soil type, precipitation, population density, Euclidean distance, and land use. The study's results categorized vulnerability into five levels: Very Low (0.09% of Owerri, minimal risk), Low (12.93% with lower risk), Moderate (68.83% facing substantial risk), High (18.18% with significant risk), and Very High (0.03% posing extreme risk). These findings are recommended as foundational data for future flood studies in the region.

Site suitability assessment for solar power plants in Bangladesh: A GIS-based analytical hierarchy process (AHP) and multi-criteria decision analysis (MCDA) approach

Solar power plants are important alternatives to fossil fuel-based power plants because they reduce greenhouse gas emissions and mitigate the effects of climate change. The potential of harnessing solar energy is highly dependent on selecting the optimal locations for plant installation. This study primarily aims to select optimal sites for solar energy plant installation using the Analytic Hierarchy Process (AHP) of Multi-Criteria Decision Analysis (MCDA) in a Geographic Information System (GIS) environment. In the underlying processing phase, the AHP method was used to calculate the relative weights of the study area's physiographic, utility, and climate data. These weights were then used in the MCDA to identify the optimal locations for solar plants. The results of the MCDA were presented in the form of a solar plant suitability map, which showed that 44.59 % (66506.49 km2) of the study area in the south and southwest of Bangladesh is highly suitable for the development of utility-scale solar power plants. In contrast, there are substantial areas of about 31.18 % (46507.37 km2) of the country where the installation of any type of power plant is completely prohibited. This research can help authorities and stakeholders decide where to invest in solar energy.

Assessment of Three GPM IMERG Products for GIS-Based Tropical Flood Hazard Mapping Using Analytical Hierarchy Process

The use of satellite precipitation products can overcome the limitations of rain gauges in flood hazard mapping for mitigation purposes. Hence, this study aims to evaluate the capabilities of three global precipitation measurement (GPM) integrated multisatellite retrievals for GPM (IMERG) products in tropical flood hazard mapping in the Kelantan River Basin (KRB), Malaysia, using the GIS-based analytic hierarchy process (AHP) method. In addition to the precipitation factor, another eleven factors that contribute to flooding in the KRB were included in the AHP method. The findings demonstrated that the spatial pattern and percentage area affected by floods simulated under the IMERG-Early (IMERG-E), IMERG-Late (IMERG-L), and IMERG-Final (IMERG-F) products did not differ significantly. The receiver operating characteristics curve analysis showed that all three IMERG products performed well in generating flood hazard maps, with area under the curve values greater than 0.8. Almost all the recorded historical floods were placed in the moderate-to-very-high flood hazard areas, with only 1–2% found in the low flood hazard areas. The middle and lower parts of the KRB were identified as regions of “very high” and “high” hazard levels that require particular attention from local stakeholders.

Geospatial Modeling Based-Multi-Criteria Decision-Making for Flash Flood Susceptibility Zonation in an Arid Area

Identifying areas susceptible to flash flood hazards is essential to mitigating their negative impacts, particularly in arid regions. For example, in southeastern Sinai, the Egyptian government seeks to develop its coastal areas along the Gulf of Aqaba to maximize its national economy while preserving sustainable development standards. The current study aims to map and predict flash flood prone areas utilizing a spatial analytic hierarchy process (AHP) that integrates GIS capabilities, remote sensing datasets, the NASA Giovanni web tool application, and principal component analysis (PCA). Nineteen flash flood triggering parameters were initially considered for developing the susceptibility model by conducting a detailed literature review and using our experiences in the flash food studies. Next, the PCA algorithm was utilized to reduce the subjective nature of the researchers’ judgments in selecting flash flood triggering factors. By reducing the dimensionality of the data, we eliminated ten explanatory variables, and only nine relatively less correlated factors were retained, which prevented the creation of an ill-structured model. Finally, the AHP method was utilized to determine the relative weights of the nine spatial factors based on their significance in triggering flash floods. The resulting weights were as follows: rainfall (RF = 0.310), slope (S = 0.221), drainage density (DD = 0.158), geology (G = 0.107), height above nearest drainage network (HAND = 0.074), landforms (LF = 0.051), Melton ruggedness number (MRN = 0.035), plan curvature (PnC = 0.022), and stream power index (SPI = 0.022). The current research proved that AHP, among the most dependable methods for multi-criteria decision-making (MCDM), can effectively classify the degree of flash flood risk in ungauged arid areas. The study found that 59.2% of the area assessed was at very low and low risk of a flash flood, 21% was at very high and high risk, and 19.8% was at moderate risk. Using the area under the receiver operating characteristic curve (AUC ROC) as a statistical evaluation metric, the GIS-based AHP model developed demonstrated excellent predictive accuracy, achieving a score of 91.6%.

GIS-based analytic hierarchy process (AHP) for soil erosion-prone areas mapping in the Bone Watershed, Gorontalo, Indonesia

GIS-based analytic hierarchy process (AHP) for soil erosion-prone areas mapping in the Bone Watershed, Gorontalo, Indonesia