Combining geographic information system, multicriteria evaluation techniques and fuzzy logic in siting MSW landfills

This study presents a methodology for siting municipal solid waste landfills, coupling geographic information systems (GIS), fuzzy logic, and multicriteria evaluation techniques. Both exclusionary and non-exclusionary criteria are used. Factors, i.e., non-exclusionary criteria, are divided in two distinct groups which do not have the same level of trade off. The first group comprises factors related to the physical environment, which cannot be expressed in terms of monetary cost and, therefore, they do not easily trade off. The second group includes those factors related to human activities, i.e., socioeconomic factors, which can be expressed as financial cost, thus showing a high level of trade off. GIS are used for geographic data acquisition and processing. The analytical hierarchy process (AHP) is the multicriteria evaluation technique used, enhanced with fuzzy factor standardization. Besides assigning weights to factors through the AHP, control over the level of risk and trade off in the siting process is achieved through a second set of weights, i.e., order weights, applied to factors in each factor group, on a pixel-by-pixel basis, thus taking into account the local site characteristics. The method has been applied to Evros prefecture (NE Greece), an area of approximately 4,000 km². The siting methodology results in two intermediate suitability maps, one related to environmental and the other to socioeconomic criteria. Combination of the two intermediate maps results in the final composite suitability map for landfill siting.     

Assessing flood hazard using flood marks and analytic hierarchy process approach: a case study for the 2013 flood event in Quang Nam,Vietnam

The production of flood hazard assessment maps is an important component of flood risk assessment. This study analyses flood hazard using flood mark data. The chosen case study is the 2013 flood event in Quang Nam, Vietnam. The impacts of this event included 17 deaths, 230 injuries, 91,739 flooded properties, 11,530 ha of submerged and damaged agricultural land, 85,080 animals killed and widespread damage to roads, canals, dykes and embankments. The flood mark data include flood depth and flood duration. Analytic hierarchy process method is used to assess the criteria and sub-criteria of the flood hazard. The weights of criteria and sub-criteria are generated based on the judgements of decision-makers using this method. This assessment is combined into a single map using weighted linear combination, integrated with GIS to produce a flood hazard map. Previous research has usually not considered flood duration in flood hazard assessment maps. This factor has a rather strong influence on the livelihood of local communities in Quang Nam, with most agricultural land within the floodplain. A more comprehensive flood hazard assessment mapping process, with the additional consideration of flood duration, can make a significant contribution to flood risk management activities in Vietnam.     

Determination of earthquake-risky areas in Yalova City Center (Marmara region,Turkey) using GIS-based multicriteria decision-making techniques (analytical hierarchy process and technique for order preference by similarity to ideal solution)

Disaster mitigation as a pre-disaster measure within the scope of disaster risk management is significant in the sense of reducing the adverse effects of earthquakes in the context of earthquake-sensitive risk planning. In the urban planning context, the existence of numerous decision makers and alternatives, which are depending on many criteria, makes decision-making process difficult. This difficulty was overcomed through geographical information systems (GIS). In the context of GIS-based multicriteria decision-making (MCDM) analysis, we used analytic hierarchy process (AHP) and technique for order preference by similarity to ideal solution (TOPSIS) to determine earthquake-risky areas in Yalova City Center. First, AHP analysis related to geological and superstructure/infrastructure criteria was conducted and two separate AHP maps were obtained. Then, we conducted TOPSIS analysis to consider both criteria in the sense of earthquake risk-sensitive planning. Then, overall earthquake risk map obtained which could be used as an input for disaster mitigation processes.

     

A Comprehensive Model for Evaluating Coalbed Methane Reservoirs in China

Coalbed methane reservoir （CBMR） evaluation is important for choosing the prospective target area for coalbed methane exploration and production. This study aims at identifying the characteristic parameters and methods to evaluate CBMR. Based on the geological surveys, laboratory measurements and field works, a four-level analytic hierarchy process （AHP） model for CBMR evaluation is proposed. In this model, different weights are prioritized and assigned on the basis of three main criteria （including reservoir physical property, storage capacity and geological characteristics）, 15 sub-criteria, and 18 technical alternatives; the later of which are discussed in detail. The model was applied to evaluate the CBMR of the Permo-Carboniferous coals in the Qinshui Basin, North China. This GIS-based fuzzy AHP comprehensive model can be used for the evaluation of CBMR of medium-high rank （mean maximum vitrinite reflectance 〉0.5 %） coal districts in China.     

Integration of GIS,AHP and TOPSIS for earthquake hazard analysis

Worldwide, earthquakes and related disasters have persistently had severe negative impacts on human livelihoods and have caused widespread socioeconomic and environmental damage. The severity of these disasters has prompted recognition of the need for comprehensive and effective disaster and emergency management (DEM) efforts, which are required to plan, respond to and develop risk mitigation strategies. In this regard, recently developed methods, known as multi-criteria decision analysis (MCDA), have been widely used in DEM domains by emergency managers to greatly improve the quality of the decision-making process, making it more participatory, explicit, rational and efficient. In this study, MCDA techniques of the Analytical Hierarchical Process (AHP) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), integrated with GIS, were used to produce earthquake hazard and risk maps for earthquake disaster monitoring and analysis for a case study region of Küçükçekmece in Istanbul, Turkey. The five main criteria that have the strongest influence on the impact of earthquakes on the study region were determined: topography, distance to epicentre, soil classification, liquefaction and fault/focal mechanism. AHP was used to determine the weights of these parameters, which were also used as input into the TOPSIS method and GIS (ESRI ArcGIS) for simulating these outputs to produce earthquake hazard maps. The resulting earthquake hazard maps created by both the AHP and TOPSIS models were compared, showing high correlation and compatibility. To estimate the elements at risk, population and building data were used with the AHP and TOPSIS hazard maps for potential loss assessment; thus, we demonstrated the potential of integrating GIS with AHP and TOPSIS in generating hazard maps for effective earthquake disaster and risk management.     

Fuzzy analytical hierarchy process and GIS for predictive Cu porphyry potential mapping: a case study in Ahar–Arasbaran Zone (NW, Iran)

Selection of potential areas for mineral exploration is a complex process and needs many diverse criteria. Combining analytic hierarchy process (AHP) modeling with geographic information system (GIS) provides an effective means for studies of mineral potential mapping evaluation. Fuzzy AHP is an extension of conventional AHP and by using fuzzy theory is obtained the advantage rather AHP method. In this paper to provide, potential mapping for Cu porphyry mineralization used fuzzy AHP and GIS in the Ahar–Arasbaran areas, several criteria, such as geology, geochemical and geophysical data, alteration, and faults were used. Each criterion was evaluated with the aid of fuzzy AHP and mapped by GIS. The method allowed a mixture of quantitative and qualitative information with group decision. The results and its validation demonstrate the acceptable outcomes for copper porphyry exploration.     

Delineation of groundwater potential zones using remote sensing,GIS, and AHP technique in Tehran–Karaj plain,Iran

Evaluation of groundwater resources in dry areas without enough data is a challenging task in many parts of the world, including Tehran–Karaj plain in Iran, which includes Tehran, the capital city of Iran and Karaj, one of Iran’s biggest cities. Water demand due to increasing agricultural and industrial activities caused many problems in the field of water resources management. In this study, the potential of groundwater resources was evaluated using remote sensing, geographic information system (GIS), and analytic hierarchy process (AHP) for the first time. Digital Elevation Model from Shuttle Radar Topography Mission was used to generate a slope map and drainage density map. Three Landsat-8 satellite images were utilized to provide lineament density and land cover/land use maps. Geological and soil type maps were provided from the Geological Survey and Mineral Explorations of Iran (GSI). Tropical Rainfall Measuring Mission data were used to prepare average annual precipitation map. Discharge values from 102 pumping wells in the time period of 2002–2014 were used to evaluate the results. Seven data layers were prepared, and the geodatabase was made in GIS. The layers and their classes were assigned weights using AHP method. Finally, the layers were overlaid based on their weights, and the potential map of groundwater resources was generated. The area was classified into five zones with very high, high, moderate, low, and very low potentials. The zones covered 5.95, 32.90, 22.70, 10.20, and 28.25% of the study area, respectively. The results showed good agreement with the field data obtained from discharge wells.     

Modelling wind-erosion risk in the Laghouat region (Algeria) using geomatics approach

Wind-erosion risk is a challenge that threatens land development in dry-land regions. Soil analysis, remote sensing, climatic, vegetal cover and topographic data were used in a geographic information system (GIS), using multi-criteria analysis (MCA) to map wind-erosion risk (R_we) in Laghouat, Algeria. The approach was based on modelling the risk and incorporating topographic and climatic effects. The maps were coded according to their sensitivity to wind erosion and to their socio-economic potential, from low to very high. By overlapping the effects of these layers, qualitative maps were drawn to reflect the potential sensitivity to wind erosion per unit area. The results indicated that severe wind erosion affects mainly all the southern parts and some parts in the north of Laghouat, where wind-erosion hazard (H_we) is very high in 43% of the total area, and which was affected mainly by natural parameters such as soil, topography and wind. The results also identified features vulnerable to R_we. The product of the hazard and the stake maps indicated the potential risk areas that need preventive measures; this was more than half of the study area, making it essential to undertake environmental management and land-use planning.     

Landslides susceptibility mapping based on geographical information system,GuiZhou, south-west China

The purpose of this study is to assess the susceptibility of landslides around the area of Guizhou province, in south-west of China, using a geographical information system (GIS). The base map is prepared by visiting the field area and mapping individual landslide at a scale of 1:500,000 topographic maps. In the study, slope, lithology, landslide inventory, tectonic activity, drainage distribution and annual precipitation were taken as independent causal factors. Therefore, six causal factors maps are prepared by collecting information from various authorized sources and converting them in to GIS maps. The susceptibility assessment is based on the qualitative map combination model and trapezoidal fuzzy number weighting (TFNW) approach. Using a predicted map of probability, the study area was classified into four categories of landslide susceptibility: low, moderate, high and very high. In addition, the weighting procedure showed that the TFNW is an efficient method for landslide causal factors weighting.     

GIS-based forest fire susceptibility modeling in Pauri Garhwal,India: a comparative assessment of frequency ratio,analytic hierarchy process and fuzzy modeling techniques

This study performs a comparative evaluation of Frequency Ratio (FR), Analytic Hierarchy Process (AHP), and Fuzzy AHP (FAHP) modeling techniques for forest fire susceptibility mapping in Pauri Garhwal, Uttarakhand, India. Locations of past forest fire events reported from November 2002 to July 2019 were collected from the Uttarakhand Forest Department and Forest Survey of India and combined with the ground observations obtained from the manual survey. Then, the locations were categorized into two groups of 70% (10,500 locations) and 30% (4500 locations), randomly, for training and validation purposes, respectively. Forest fire susceptibility mapping was performed on the basis of fourteen different topographic, biological, human-induced and climatic criteria such as Digital Elevation Model, Slope, Aspect, Curvature, Normalized Difference Vegetation Index, Normalized Difference Moisture Index, Topographic Wetness Index, Soil, Distance to Settlement, Distance to Road, Distance to Drainage, Rainfall, Temperature, and Wind Speed. The Receiver Operating Characteristic curve and the Area Under the Curve (AUC) were implemented for validation of the three achieved Forest Fire Susceptibility Maps. The AUC plot evaluation revealed that FAHP has a maximum prediction accuracy of 83.47%, followed by AHP (81.75%) and FR (77.21%). Thus, the map produced by FAHP exhibits the most satisfactory properties. Results and findings of this study will help in developing more efficient fire management strategies in both the open and the protected forest areas (Rajaji and Jim Corbett National Park) of the district.

     

Landslide hazard mapping in the Constantine city,Northeast Algeria using frequency ratio,weighting factor,logistic regression,weights of evidence,and analytical hierarchy process methods

Landslides constitute the most widespread and damaging natural hazards in the Constantine city. They represent a significant constraint to development and urban planning. In order to reduce the risk related to potential landslide, there is a need to develop a comprehensive landslide hazard map (LHM) of the area for an efficient disaster management and for planning development activities. The purpose of this research is to prepare and compare the LHMs of the Constantine city, by applying frequency ratio (FR), weighting factor (Wf), logistic regression (LR), weights of evidence (WOE), and analytical hierarchy process (AHP) methods used in a framework of the geographical information system (GIS). Firstly, a landslide inventory map has been prepared based on the interpretation of aerial photographs, high resolution satellite images, fieldwork, and available literature. Secondly, eight landslide-conditioning factors such as lithology, slope, exposure, rainfall, land use, distance to drainage, distance to road, and distance to fault have been considered to establish LHMs using the FR, Wf, LR, WOE, and AHP models in GIS. For verification, the obtained LHMs have been validated comparing the LHMs with the known landslide locations using the receiver operating characteristics curves (ROC). The validated results indicate that the FR method provides more accurate prediction (86.59 %) of LHMs than the WOE (82.38 %), AHP (77.86 %), Wf (77.58 %), and LR (70.45 %) models. On the other hand, the obtained results showed that all the used models in this study provided a good accuracy in predicting landslide hazard in Constantine city. The established maps can be used as useful tools for risk prevention and land use planning in the Constantine region.     

DEFLOGIC: a method for assessment of groundwater potential in karst terrains: Gurpi Anticline,southwest Iran

A new hydro-tectonic model, includes eight layers that affect karst hydrogeology was proposed for mapping of groundwater potential in karst areas of Gurpi Anticline, southwest Iran. To produce the groundwater potential map, remote sensing (RS) and GIS techniques were combined with fuzzy logic modeling. Criterion maps include the distances from discharge sites (D), the elevation difference from discharge sites (E), the distance from fractures (F), the fracture length density (L), the slope (O), the lithology (G), the distance from fractures intersections (I), and the fractures intersection density (C) were produced using GIS and RS techniques (DEFLOGIC layers). The approach of fuzzy sets was used to commensurate criterion maps, then fuzzy algebraic sum and gamma operators were applied to aggregate them. The weights of parameters of DEFLOGIC proposed in the range of 1 to 5, which standardized between 0 to 1, based on their importance in karst hydrogeology, professional judgments, and available exploration data. The final groundwater potential maps were verified by geoelectric and well-drilling data. The potential map prepared using fuzzy gamma operator with γ?=?0.92, which it is a flexible distinctive parameters of sum and product of fuzzy operator, depicts the best coincidence with exploration data. The final DEFLOGIC map shows the high groundwater potential in karst formations between Hati and Pebde valleys. The results support the efficiency of DEFLOGIC model to evaluating of groundwater potential in karst terrains, especially in Zagros ranges.     

Application of fuzzy logic and analytical hierarchy process (AHP) to landslide susceptibility mapping at Haraz watershed, Iran

The main goal of this study is to produce landslide susceptibility maps of a landslide-prone area (Haraz) in Iran by using both fuzzy logic and analytical hierarchy process (AHP) models. At first, landslide locations were identified by aerial photographs and field surveys, and a total of 78 landslides were mapped from various sources. Then, the landslide inventory was randomly split into a training dataset 70?% (55 landslides) for training the models and the remaining 30?% (23 landslides) was used for validation purpose. Twelve data layers, as the landslide conditioning factors, are exploited to detect the most susceptible areas. These factors are slope degree, aspect, plan curvature, altitude, lithology, land use, distance from rivers, distance from roads, distance from faults, stream power index, slope length, and topographic wetness index. Subsequently, landslide susceptibility maps were produced using fuzzy logic and AHP models. For verification, receiver operating characteristics curve and area under the curve approaches were used. The verification results showed that the fuzzy logic model (89.7?%) performed better than AHP (81.1?%) model for the study area. The produced susceptibility maps can be used for general land use planning and hazard mitigation purpose.     

地形图扫描数字化点位精度浅谈

地形图数字化是获取矢量空间数据,建立GIS数据库的一项重要的基础工作,而地形图数字化的精度直接影响着GIS数据库的精度.地形图数字化的方式通常有两种,一是手扶跟踪数字化,另一种是扫描数字化.本文就扫描数字化的精度问题做以简单的探讨.     

Determining the hard rock groundwater pathway in Golgohar complex formation using hydrochemical data in AHP

Thirty percent of present industrial water consumption of the Golgohar Iron Ore Mine (GIOM) is supplied from a hard rock well (PW-A15) and the rest from 25 wells located in 4 disconnected alluvial aquifers. This well is drilled in the metamorphic complex of Golgohar formation. Attempts have been made to develop extraction of water from other hard rocks existing in the area with no success. Therefore, extensive researches have been carried out to find the pathway, or a provision pathway of water discharged from this well. To study the hydrochemical similarity of this water with other water resources, 122 water samples from an area of 7132 km² were collected from the existing pumping wells, piezometers, mine exploration bore holes, and three salt pans in the vicinity of the area for hydrochemical analysis. The analyses were performed for concentration of major ions and some minor elements. Furthermore, the spatial distribution of ion concentration was plotted in the GIS to delineate the similarity of the PW-A15 water with other water sources and their hydrochemical neighborhood by analytical hierarchy process (AHP). The AHP was performed in two steps: first, iso-concentration maps of seven major ions, eight minor elements, and TDS were used to produce an AHP map (Map1) using weights for different hydrochemical parameters; and second, a similarity index (SI) map was prepared by performing a suggested clustering approach in SPSS using K-means clustering, which was overlaid on Map1 producing Map2. The result of AHP Map2 was then overlaid on the iso-potential map of the sampled locations in GIS software using a mask operator. Therefore, the zones having the most similarity and higher hydraulic potential than PW-A15 were nominated as the zones which possibly could recharge this well, and the groundwater (GW) pathway was proposed. The result of the study method showed to be successful and will be used as a guide for future exploration drillings.     

An interval matrix method used to optimize the decision matrix in AHP technique for land subsidence susceptibility mapping

The analytical hierarchy process (AHP) is one of the most effective methods for criteria ranking/weighting to have been successfully incorporated into GIS analyses. We present a new method for optimizing pairwise comparison decision-making matrices in AHP method, which has been developed on the basis of an interval pairwise comparison matrix (IPCM) derived from expert knowledge. The method has been used for criteria ranking in land subsidence susceptibility mapping (LSSM) as a practical test case, for which an interval matrix was generated by pairwise comparison. To compare the capability of the AHP method (a traditional approach) with that of the proposed IPCM method (a novel approach), 11 creations of LSSM were ranked using each approach in turn. The criteria weightings obtained were then used to produce LSSM maps based on each of these approaches. The results were tested against a data set of known land subsidence occurrences, indicating an improvement in accuracy of about 14% in the LSSM map that was developed using the IPCM method. This improvement was achieved by minimizing the uncertainty associated with criteria ranking/weighting in a traditional AHP and could form a basis for future research into minimizing the uncertainty in weightings derived using the AHP method. Our results will be of considerable importance for researchers involved in GIS-based multi-criteria decision analysis (MCDA) and those dealing with GIS-based spatial decision-making methods.     

Use of GIS-based fuzzy logic relations and its cross application to produce landslide susceptibility maps in three test areas in Malaysia

Landslides are one of the most frequent and common natural hazards in Malaysia. Preparation of landslide susceptibility maps is one of the first and most important steps in the landslide hazard mitigation. However, due to complex nature of landslides, producing a reliable susceptibility map is not easy. For this reason, a number of different approaches have been used, including direct and indirect heuristic approaches, deterministic, probabilistic, statistical, and data mining approaches. Moreover, these landslides can be systematically assessed and mapped through a traditional mapping framework using geoinformation technologies. Since the early 1990s, several mathematical models have been developed and applied to landslide hazard mapping using geographic information system (GIS). Among various approaches, fuzzy logic relation for mapping landslide susceptibility is one of the techniques that allows to describe the role of each predisposing factor (landslide-conditioning parameters) and their optimal combination. This paper presents a new attempt at landslide susceptibility mapping using fuzzy logic relations and their cross application of membership values to three study areas in Malaysia using a GIS. The possibility of capturing the judgment and the modeling of conditioning factors are the main advantages of using fuzzy logic. These models are capable to capture the conditioning factors directly affecting the landslides and also the inter-relationship among them. In the first stage of the study, a landslide inventory was complied for each of the three study areas using both field surveys and airphoto studies. Using total 12 topographic and lithological variables, landslide susceptibility models were developed using the fuzzy logic approach. Then the landslide inventory and the parameter maps were analyzed together using the fuzzy relations and the landslide susceptibility maps produced. Finally, the prediction performance of the susceptibility maps was checked by considering field-verified landslide locations in the studied areas. Further, the susceptibility maps were validated using the receiver-operating characteristics (ROC) success rate curves. The ROC curve technique is based on plotting model sensitivity—true positive fraction values calculated for different threshold values versus model specificity—true negative fraction values on a graph. The ROC curves were calculated for the landslide susceptibility maps obtained from the application and cross application of fuzzy logic relations. Qualitatively, the produced landslide susceptibility maps showed greater than 82% landslide susceptibility in all nine cases. The results indicated that, when compared with the landslide susceptibility maps, the landslides identified in the study areas were found to be located in the very high and high susceptibility zones. This shows that as far as the performance of the fuzzy logic relation approach is concerned, the results appeared to be quite satisfactory, the zones determined on the map being zones of relative susceptibility.     

Spatial prediction of wildfire probability in the Hyrcanian ecoregion using evidential belief function model and GIS

Accurate estimates of wildfire probability and production of distribution maps are the first important steps in wildfire management and risk assessment. In this study, geographical information system (GIS)-automated techniques were integrated with the quantitative data-driven evidential belief function (EBF) model to predict spatial pattern of wildfire probability in a part of the Hyrcanian ecoregion, northern Iran. The historical fire events were identified using earlier reports and MODIS hot spot product as well as by carrying out multiple field surveys. Using the GIS-based EBF model, the relationships among existing fire events and various predictor variables predisposing fire ignition were analyzed. Model results were used to produce a distribution map of wildfire probability. The derived probability map revealed that zones of moderate, high, and very high probability covered nearly 60% of the landscape. Further, the probability map clearly demonstrated that the probability of a fire was strongly dependent upon human infrastructure and associated activities. By comparing the probability map and the historical fire events, a satisfactory spatial agreement between the five probability levels and fire density was observed. The probability map was further validated by receiver operating characteristic using both success rate and prediction rate curves. The validation results confirmed the effectiveness of the GIS-based EBF model that achieved AUC values of 84.14 and 81.03% for success and prediction rates, respectively.     

Landslide susceptibility evaluation in the Chemoga watershed,upper Blue Nile,Ethiopia

Landslide susceptibility consists of an essential component in the day-to-day activity of human beings. Landslide incidents are typically happening at a low rate of recurrence when compared and in contrast to other events. This might be generated into main natural catastrophes relating to widespread and undesirable sound effects. Landslide hotspot area identification and mapping are used for the regional community to secure from this disaster. Therefore, this research aims to identify the hotspot areas of landslide and to generate maps using GIS, AHP, and multi-criteria decision analysis (MCDA). MCDA techniques are applied under such circumstances to categorize and class decisions for successive comprehensive estimation or else to state possible from impossible potentiality with various landslides. Analytical hierarchy process (AHP) constructively applies for conveying influence to different criteria within multi-criteria decision analysis. The causative landslide identifying factors utilized in this research were elevation, slope, aspect, soil type, lithology, distance to stream, land use/land cover, rainfall, and drainage density achieved from various sources. Subsequently, to explain the significance of each constraint into landslide susceptibility, all factors were found using the AHP technique. Generally, landslide susceptibility map factors were multiplied by their weights to acquire with the AHP technique. The result showed that the AHP methods are comparatively good quality estimators of landslide susceptibility identification in the Chemoga watershed. As the result, the Chemoga watershed landslide susceptibility map classes were classified as 46.52%, 13.83%.18.71%, 15.39%, and 5.55% of the occurred landslide fall to very low, low, moderate, high, and very high susceptibility zones, respectively. Performance and accuracy of modeled maps have been established using GPS field data and Google earth data landslide map and area under curve (AUC) of the receiver operating characteristic curve (ROC). As the result, validation depends on the ROC specifies the accuracy of the map formed with the AHP merged through weighted overly method illustrated very good accuracy of AUC value 81.45%. In general, the research outcomes inveterate the very good test consistency of the generated maps.

     

Mineral potential mapping for rare earth elements mineralization with AHP method in the Kerman-Kashmar Tectonic Zone,Central Iran

One of the major strengths of a GIS is the ability to integrate and combine multiple layers of geoscience data for producing mineral potential maps showing favorable areas for mineral exploration. Once the data is prepared properly, the GIS, jointly with other statistical and geostatistical software packages, can be used to manipulate and visualize the data in order to produce a mineral prospectivity map. Many spatial modeling techniques can be employed to produce mineral potential maps. This paper demonstrates a technique to define favorable areas for REE mineralization with AHP technique using geological, geochemical, geophysical, alteration and faults density spatial data in the Kerman-Kashmar Tectonic Zone of central Iran. The AHP is a powerful and flexible multi-criteria decision-making tool for dealing with complex problems where both qualitative and quantitative aspects need to be considered. This approach is knowledgedriven method and can be applied in other areas for conventional use in mineral exploration.