GIS-Based Multi-Criteria Decision Making for the Assessment of Adventure Tourism Camp Suitability: A Case Study in Iran

Abstract

The dynamism of adventure tourism necessitates the precise identification of areas with suitable natural, infrastructural, and service capacities for hosting activities. The aim of this study is to assess the multi-scenario spatial suitability for the sustainable development of adventure tourism camps using a Geographic Information System (GIS)-based Multi-Criteria Decision-Making (MCDM) approach. The datasets used included topographic, climatic, environmental, accessibility, natural and cultural attraction, and service infrastructure indicators. The relevant criteria were first standardized, and their weights were determined using the Analytic Hierarchy Process (AHP). Subsequently, the layers were integrated through a Weighted Linear Combination (WLC) model. Four scenarios were designed for sensitivity analysis: the first scenario with balanced weight distribution (S_bal), the second prioritizing accessibility (S_acc), the third focusing on natural attractions (S_att), and the fourth emphasizing services (S_serv). The results indicated that approximately 21% and 9% of Chaharmahal and Bakhtiari province have high and very high potential for adventure activities, respectively, which were selected as initial options for the multi-scenario analysis. In the balanced (S_bal) scenario, 31% and 13% of the area of these options fell into high and very high suitability classes, respectively. The Service-Based Scenario (S_serv) increased the share of high and very high suitability areas to 34% and 19%, while Accessibility-Based Scenario (S_acc) reduced these classes to 27% and 10%. In the Attraction-Based Scenario (S_att), the areas in the high and very high suitability classes were 30% and 12%, respectively. The findings demonstrate that altering the priority of components can significantly change the spatial pattern of suitability, and sustainable planning of adventure tourism activities should be conducted based on management objectives and regional capacities. The proposed framework is generalizable to other regions and can serve as a basis for decision-making in balanced development, optimal infrastructure allocation, and sustainable management of adventure tourism.

1. Introduction

Adventure tourism has been rapidly growing, which is formed around nature-based activities, thrilling experiences, and direct interaction between tourists and the environment. It not only has economic benefits but also encompasses social, cultural, and environmental dimensions [1,2,3,4]. Recent reports indicate that the global adventure tourism market continues to expand rapidly, driven by increasing demand for nature-based and outdoor experience-oriented travel [5]. Recent developments show that adventure tourism is moving away from traditional high-risk activities toward soft adventure, environmental sustainability, and experience-oriented approaches [6,7,8,9]. Global market reports on adventure tourism (2024) indicate that activities such as hiking, mountain biking, rafting, surfing, and nature trekking have experienced the highest growth.

In Iran, the exceptional climatic and geomorphological diversity provides extensive potential for the development of adventure tourism, ranging from the Alborz and Zagros mountain ranges to the southern coasts, central deserts, and Hyrcanian forests. Activities such as mountaineering, rock climbing, paragliding, skiing, rafting, and nature trekking have witnessed significant growth in recent years. However, the development of these activities has largely occurred without a comprehensive spatial assessment framework and integrated analysis of infrastructure, accessibility, and service infrastructure. This lack of integrated spatial assessment may lead to uneven spatial concentration, environmental pressure, and suboptimal utilization of capacities [10]. In this context, integrating spatial analyses with sustainable development principles provides a foundation for smart planning, minimizing negative impacts, and optimizing the use of natural and infrastructural capacities for adventure tourism.

The development of adventure tourism is highly site-dependent, as the quality of tourist experiences, safety levels, and environmental sustainability are all influenced by spatial characteristics such as slope, elevation, climatic conditions, land cover, water resources, and accessibility. In this context, Geographic Information Systems (GIS), when integrated with Multi-Criteria Decision-Making (MCDM) approaches, provide an effective platform for the simultaneous analysis of diverse and sometimes conflicting criteria [11,12]. This approach allows for the weighting of indicators, integration of multiple spatial layers, and generation of transparent and reproducible suitability maps. Although the application of GIS–MCDM in tourism land-use planning and ecotourism potential assessment is expanding, its use for planning adventure tourism camps particularly under conditions of future uncertainty remains limited. The literature indicates that adventure tourism has emerged as one of the rapidly growing sectors of the global tourism industry, attracting considerable attention from researchers due to its economic, social, and environmental implications. Some studies have focused on the spatial distribution patterns of tourism resources and infrastructure. Another strand of the literature focuses on spatial analyses and land suitability assessment for tourism development. Zhou and Yang [13] examined the relationship between the attractiveness of tourism facilities and tourists’ satisfaction in historic contexts using the Multiscale Geographically Weighted Regression (MGWR) model and spatiotemporal analysis. Aşılıoğlu and Çay [14], combining the ROS framework and the Analytic Hierarchy Process (AHP), identified various levels of spatial suitability for tourism activities in both natural and urban environments. Similar studies conducted in Qilian National Park [15] and the Tianshan Mountains, Xinjiang [16], demonstrated that integrating GIS with MCDM methods can identify suitable locations for ecotourism and adventure tourism while accounting for ecological sensitivity, route difficulty, and activity safety. Beyond spatial approaches, behavioral and motivational studies have also expanded in recent years. Jia et al. [17] found that adventure tourism in natural settings can generate profound meanings such as a sense of challenge, attachment to nature, and social bonding, and may even reduce occupational dissatisfaction. Orden-Mejía, et al. [9] highlighted the role of motivations such as health improvement, stress reduction, and intellectual curiosity in shaping the quality of experience and tourist loyalty. At a broader level, studies such as Víquez-Paniagua et al. [18] and Sand and Gross [19] emphasize the importance of spatial requirements, accessibility, safety, and service quality for achieving sustainable adventure tourism development. Additionally, Azimi et al. [20] demonstrated that the integration of natural resources, infrastructure, and sustainability considerations plays a crucial role in the competitiveness of tourism destinations, particularly in island regions.

Despite the expansion of studies in the field of adventure tourism, several important gaps remain. Existing studies can generally be grouped into two main directions. First, spatially oriented research that employs tools such as GIS, Analytic Hierarchy Process (AHP), Multiscale Geographically Weighted Regression (MGWR), and data mining methods to identify patterns in the distribution of tourism resources and activities [21,22,23]. Second, studies focusing on the behavioral and motivational dimensions of tourists, addressing aspects such as tourist experiences, travel motivations, and welfare outcomes [2,17,18]. While these studies provide valuable insights, in a significant portion of spatial studies, the focus has largely been on urban scales or protected areas, such as national parks, and integrated analyses of the relationships among spatial suitability of natural resources, accessibility, environmental attractiveness, and supporting services within a sustainable adventure tourism development framework at the regional scale remain limited. On the other hand, behavioral studies have primarily addressed motivations, satisfaction, and tourist loyalty, and rarely incorporate environmental and service-related data into a cohesive spatial framework. Also, many spatial suitability analyses remain primarily focused on environmental conditions and often provide limited integration of infrastructural services and planning scenarios. Furthermore, relatively few studies have applied scenario-based GIS–MCDM frameworks to explore how different planning priorities may influence the spatial distribution of suitable tourism areas, particularly at the regional or provincial scale. This limitation is especially relevant in mountainous regions where environmental potential, accessibility constraints, and tourism service infrastructure interact in complex ways.

The present study introduces a four-component framework that simultaneously integrates environmental potential, accessibility, attractions, and service infrastructure. Moreover, this research adopts an explicit multi-scenario design to examine how different planning priorities influence spatial suitability patterns. Finally, rather than focusing on a single protected park, the analysis is conducted at a broader regional scale, enabling a more comprehensive assessment of tourism development potential and infrastructure distribution. To better structure the analysis and clarify the objectives of this research, the following research questions are addressed: (i) How do different development priorities (accessibility, attractions, and services) modify the spatial distribution of high and very high suitability zones for adventure tourism camps?; (ii) Which parts of Chaharmahal and Bakhtiari Province combine strong environmental potential with adequate accessibility and service infrastructure?; (iii) How can scenario-based spatial suitability assessments support sustainable tourism planning and infrastructure investment decisions at the regional scale?

2. Study Area

Chaharmahal and Bakhtiari Province, located in southwestern Iran between approximately 32°10′ to 32°50′ N latitude and 50°30′ to 51°30′ E longitude, forms part of the Central Zagros mountainous region (Figure 1). The province covers an area of about 16,332 km² and had a population of over 1,001,000 according to the 2025 census, with natural features such as rivers, forests, and highlands significantly influencing settlement patterns [24]. A prominent characteristic of the province is its mountainous terrain, with more than 75% of its area consisting of elevations and rugged landscapes; notable peaks include Zard-Kuh Bakhtiari, which rises above 4200 m. The high elevations and extensive slopes and natural curvatures create favorable conditions for adventure tourism activities, including mountaineering, nature trekking, and rock climbing. Due to its location along western moist air currents and high-altitude topography, the province experiences substantial precipitation and prolonged snow cover during cold seasons, supporting the development of winter tourism and seasonal adventure events [25]. Water resources are another prominent feature; several major rivers, including the Karun and Zayandeh-Rud, originate in these mountains, forming an extensive network of waterways that provide both high ecological value and increased potential for adventure water activities [26]. Forest cover in the western and northwestern parts creates a combination of green landscapes, rocky structures, and high elevations, which, along with numerous springs and waterfalls, generate pristine natural attractions for tourists [27]. The combination of these natural, climatic, service, and cultural factors positions Chaharmahal and Bakhtiari as one of Iran’s prime regions for the development of adventure tourism. By conducting a detailed analysis of environmental factors, accessibility, natural attractions, and services, optimal spatial scenarios for adventure tourism camp development can be designed and planned in this region. In addition to its environmental characteristics, Chaharmahal and Bakhtiari Province has become an increasingly important destination for nature-based and adventure tourism in southwestern Iran. Several well-known natural attractions, including the Zard-Kuh mountain massif, the Kuhrang waterfalls, and numerous alpine valleys and rivers, attract domestic tourists interested in outdoor recreation and mountain landscapes. Adventure-related activities in the province include mountaineering, trekking, rock climbing, rafting, skiing, and nature-based camping. The presence of perennial rivers and mountainous terrain also supports seasonal activities such as rafting and winter sports. Tourism demand is strongly seasonal, with peak visitation occurring during spring and summer when weather conditions are favorable for outdoor activities, while winter months attract visitors interested in snow-based recreation in high-altitude areas. These characteristics make the province a representative case for examining the spatial planning of adventure tourism camps in mountainous environments.

3. Data and Methods

3.1. Data

To extract the effective indicators for assessing the spatial suitability of adventure tourism camp development, a combination of remote sensing, climatic, topographic, and infrastructural data was utilized. All datasets were collected from reliable sources and processed in Google Earth Engine (GEE) and GIS environments.

Topographic indicators included elevation, slope, curvature, and the Terrain Ruggedness Index (TRI), which were derived from the Shuttle Radar Topography Mission (SRTM) Digital Elevation Model (DEM) with a spatial resolution of 30 m. These data were resampled and georeferenced for spatial analyses. Vegetation indices were calculated using Landsat 8 OLI and Landsat 9 OLI-2 imagery, including the Normalized Difference Vegetation Index (NDVI). To minimize atmospheric noise and cloud cover effects, median temporal composites were applied, representing the stable vegetation condition of the study area. Climatic data encompassed precipitation, wind speed, and snow duration. Precipitation was extracted from the Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) database at approximately 5 km spatial resolution to enable analysis of rainfall patterns in mountainous and semi-arid regions. Wind speed was obtained from the ERA5-Land reanalysis dataset provided by the European Centre for Medium-Range Weather Forecasts (ECMWF). Snow duration was calculated using MODIS satellite data (MOD10A1) to assess the persistence and continuity of snow cover throughout the year.

Hydrographic and water resources layers, including rivers and drainage networks, were derived from HydroSHEDS and OpenStreetMap (OSM) to evaluate the role of water features in tourism attractiveness and functionality. Infrastructure and accessibility datasets comprised road networks (primary and secondary), railways, railway stations, and bus and taxi stations, all obtained from OSM, topologically cleaned, and converted into distance-based indices to quantify access to target areas in the spatial suitability analysis. Land cover and conservation layers were extracted using global land use/cover products and DEM data. Protected area boundaries were retrieved from the World Database on Protected Areas (WDPA) to incorporate official and up-to-date conservation zones. Tourist attractions and services, including sites, waterfalls, springs, and other natural attractions, were compiled from national agencies, OSM, and Google Earth, then validated for accuracy. Urban and service data, including cities, villages, healthcare and emergency centers, law enforcement facilities, accommodation, dining, and commercial centers, were primarily extracted from OSM, Google Maps (web-based), Google Earth Pro (version 7.3.7) and supplemented with official national datasets. Proximity to the provincial center was calculated using administrative boundary layers and service centrality, serving as a key indicator of service support in the spatial suitability analysis. The main datasets used in this study, including their spatial resolution, temporal coverage, and sources, are summarized in

Table 1. Characteristics of data used in the study.

Dataset	Source	Spatial Resolution	Temporal Coverage	Purpose
DEM	SRTM	30 m	Static	Topographic indicators
NDVI	Landsat 8/9	30 m	2018–2025	Vegetation condition
Precipitation	CHIRPS	~5 km		Long-term rainfall patterns
Wind speed	ERA5-Land	~9 km		Climatic conditions
Snow duration	MODIS MOD10A1	500 m		Snow persistence
Infrastructure	OSM, Google Maps, and Google Earth	Vector	2025	Accessibility and service related indicators
Protected areas	WDPA	Vector	2025	Conservation zones

. The use of multi-year datasets and temporal aggregation helps reduce short-term climatic anomalies and provides a more reliable representation of long-term environmental and infrastructural conditions, which is essential for strategic tourism planning and spatial decision-making.

All layers and maps were converted to raster format and resampled to a 500 m pixel size using the nearest neighbor interpolation method. The coordinate system WGS_1984_UTM_Zone_39N was assigned to all maps. All spatial layers were resampled to a 500 m grid resolution to ensure consistency among datasets with different spatial resolutions and to facilitate efficient spatial integration within the GIS-based MCDM framework. This resolution represents a balance between maintaining sufficient spatial detail across the provincial scale and ensuring computational efficiency for multi-layer analysis. Moreover, the 500 m grid size is appropriate for regional-scale tourism planning and the identification of suitable zones for adventure tourism camp development. However, it should be noted that at this spatial resolution, very small topographic features or localized environmental variations may be generalized.

3.2. Methods

To map the suitability for adventure tourism camp development, the potential suitability for adventure activities in the study area was first assessed, followed by an analysis of the actual suitability with a focus on accessibility, tourist attractions, and services (Figure 2). The evaluation process was conducted in three main steps: In the first step, the criteria affecting adventure activities, as well as indicators related to accessibility, tourist attractions, and services, were identified. These criteria were weighted and standardized to enable spatial integration and analysis, allowing for the preparation of suitability maps. In the second step, the suitability map for adventure activities was produced, and areas classified as high and very high suitability were identified as selected options. These selected areas were then evaluated in terms of three components: accessibility, attractions, and services, and corresponding maps for each component were generated. In the third step, the suitability maps for adventure activities and the maps of accessibility, attractions, and services for the selected areas were integrated into four decision-making scenarios: (1) Balanced Scenario (S_bal), (2) Accessibility-Based Scenario (S_acc), (3) Attraction-Based Scenario (S_att), and (4) Service-Based Scenario (S_serv). Finally, the area and spatial distribution of suitability classes for adventure tourism site development were analyzed for each scenario, and the results were presented as decision-support maps for the study region.

3.2.1. Identification and Weighting of Influential Criteria

Adventure tourism encompasses a wide spectrum of activities that range from hard adventure (e.g., rock climbing, rafting, and high-altitude mountaineering) to soft adventure activities such as nature trekking, landscape observation, and low-intensity outdoor recreation. The criteria used in this study were selected to capture environmental conditions relevant to both categories of activities. For example, terrain-related indicators such as slope and elevation are particularly important for identifying areas suitable for more physically demanding adventure activities. At the same time, other indicators including vegetation cover, landscape diversity, accessibility, and tourism services are relevant for softer forms of adventure tourism rather than extreme physical challenge. Therefore, the selection of criteria aims to represent the general spatial suitability for adventure tourism development, rather than focusing exclusively on either hard or soft adventure activities.

Potential suitability for adventure activities component: This component focuses on the natural capacity and environmental conditions of the region for conducting adventure activities and includes nine indicators. The indicators represent the topographic, climatic, and environmental conditions of the area, determining factors such as trail difficulty, safety, and natural attractiveness for adventure activities. Collectively, these indicators enable the identification of areas with high environmental potential for adventure tourism camp development (

Table 2. Criteria for evaluating adventure tourism camp development.

Component	Criteria	Criteria Description	Weight
Potential suitability for adventure activities	Curvature	Degree of surface curvature affecting water flow and trail stability.	0.08
	Elevation	Height above sea level influencing climate conditions, accessibility, and tourism attractiveness.	0.10
	NDVI	Vegetation cover indicating trail density and visibility, affecting safety and natural appeal.	0.07
	Precipitation	Rainfall affecting terrain conditions and the safety of outdoor adventure activities.	0.10
	River	Proximity to rivers essential for activities like rafting and kayaking, enhancing site attractiveness.	0.08
	Slope	Trail steepness determining difficulty and risk for hiking, climbing, and mountain biking.	0.15
	Snow duration	Length of snow cover defining opportunities for activities such as skiing and snowboarding.	0.10
	TRI	Land irregularity indicating geological diversity and excitement of adventure trails.	0.12
	Wind speed	Wind speed affecting safety for activities like paragliding, mountaineering, and other high-altitude sports.	0.10
Accessibility suitability	Road access	Primary access routes for tourists, major influence on site entry and exit.	0.40
	Airport access	Important for distant tourists, though less critical than road networks.	0.20
	Bus and taxi station access	Moderate importance for tourists using public transport.	0.18
	Railway station access	Lower importance as short-term and adventure activities are mostly by car.	0.12
Attraction suitability	Forest cover	Enhances visual appeal, nature-based tourism, and green experiences.	0.12
	Mountainous areas	Scenic views and diverse landscapes that attract tourists.	0.18
	Protected areas	High ecological value and biodiversity, supporting sustainable and conscious tourism.	0.10
	Snow cover	Winter scenery and visual appeal throughout the year.	0.08
	Tourism sites and attractions	Landmarks, cultural heritage, and natural sites creating tourism appeal.	0.16
	Waterfalls and springs	Prominent natural attractions enhancing sensory and visual experiences.	0.07
	NDVI	Reflects vegetation density and diversity, enhancing landscape aesthetics.	0.12
	Rivers	Water landscapes and nature-watching opportunities attracting tourists.	0.17
Service suitability	Cities	Access to urban facilities and comprehensive tourism services, attracting tourists.	0.15
	Villages	Providing cultural and traditional experiences for tourists interested in local tourism.	0.12
	Medical centers	Safety and reassurance for tourists in case of accidents and medical needs.	0.10
	Emergency service centers	Ensuring security and support for tourists, reducing travel risks.	0.11
	Accommodation centers (Hotels)	Access to lodging and travel comfort, a key factor in destination choice.	0.15
	Law enforcement centers	Public security and tourist protection, reducing safety concerns.	0.07
	Provincial center	Facilitates access to central services and main tourism infrastructure.	0.13
	Restaurants	Food and catering services, enhancing tourist satisfaction.	0.08
	Shopping centers	Providing shopping opportunities and access to necessary tourist goods.	0.09

).

Accessibility suitability component: This component includes four indicators that reflect the connectivity of the area to transportation networks and the ease of tourist access. These indicators demonstrate the degree of tourist access to roads and public transport systems and their impact on reducing travel time and cost, increasing safety and comfort, and enabling successful adventure tourism events (Table 2).

Attraction suitability component: This component comprises eight indicators reflecting the natural and tourism capacities of the region. The indicators generally show natural attractiveness, biodiversity, and environmental tourism resources, allowing for the identification of areas with high potential to attract adventure tourists and develop nature-based tourism activities (Table 2). Protected areas were incorporated into the attraction component as indicators of ecological value and natural landscape attractiveness rather than as zones intended for direct tourism infrastructure development. In the suitability analysis, strict conservation areas were not considered appropriate for intensive tourism infrastructure such as permanent camp facilities. Instead, their presence was interpreted as contributing to the environmental attractiveness of surrounding landscapes and supporting low-impact or peripheral tourism activities (e.g., nature observation or guided outdoor recreation).

Service suitability component: This component includes nine indicators that represent the level of infrastructural, welfare, and security support for tourists. The indicators assess the region’s capability to provide essential services for hosting tourists, including accommodation, food services, medical care, and security. Adequate services are a necessary condition for the safe and sustainable execution of adventure tourism events (Table 2).

The relative importance of several criteria reflects the specific characteristics of adventure tourism activities in Chaharmahal and Bakhtiari Province. Within the accessibility component, proximity to roads received the highest weight (0.40) because adequate access is essential for transporting visitors, equipment, and emergency services to remote mountainous areas where many adventure activities take place. Limited road accessibility can significantly restrict the feasibility and safety of tourism operations. Within the attraction component, mountainous landscapes and river systems were assigned relatively high weights due to their central role in the dominant forms of adventure tourism in the province. The extensive Zagros mountain landscapes provide suitable conditions for mountaineering, trekking, and nature-based camping, while rivers originating from these highlands support activities such as rafting and outdoor recreation. Consequently, these natural features represent key spatial drivers of adventure tourism potential and were therefore prioritized in the weighting scheme.

In addition, to reduce potential multicollinearity issues, the relationships among the main indicators were examined prior to the analysis. A Pearson correlation test was conducted, and the results indicated that the correlation coefficients between the indicators were generally below 0.5, suggesting that strong multicollinearity among the variables was not present. Therefore, the selected indicators were retained in the model.

Data Standardization

To address the heterogeneity in measurement units and value ranges of the indicators used, data normalization was considered an essential step in the analysis. After digitizing and importing all data layers into the GIS environment, each criterion map was standardized to enable comparison and combination. In this process, the values of each indicator were rescaled using the min–max method to a uniform range between 0 and 1, where a value of 1 represents the highest suitability or desirability and 0 represents the lowest for each spatial unit. The effect direction of each criterion was also considered so that positively and negatively influencing indicators were logically aligned in the final analysis. This approach ensured that all layers were on a common scale, allowing for systematic integration of indicators and simultaneous analysis of components in subsequent steps.

$$\mathrm{N}{\mathrm{C}}_{\mathrm{i}\mathrm{j}}={\displaystyle \frac{{\mathrm{C}}_{\mathrm{j}}^{\mathrm{m}\mathrm{a}\mathrm{x}}-{\mathrm{C}}_{\mathrm{i}\mathrm{j}}}{{\mathrm{C}}_{\mathrm{j}}^{\mathrm{m}\mathrm{a}\mathrm{x}}-{\mathrm{C}}_{\mathrm{j}}^{\mathrm{m}\mathrm{i}\mathrm{n}}}}$$

(1)

$$\mathrm{N}{\mathrm{C}}_{\mathrm{i}\mathrm{j}}={\displaystyle \frac{{\mathrm{C}}_{\mathrm{i}\mathrm{j}}-{\mathrm{C}}_{\mathrm{j}}^{\mathrm{m}\mathrm{i}\mathrm{n}}}{{\mathrm{C}}_{\mathrm{j}}^{\mathrm{m}\mathrm{a}\mathrm{x}}-{\mathrm{C}}_{\mathrm{j}}^{\mathrm{m}\mathrm{i}\mathrm{n}}}}$$

(2)

where $C_{ij}$ is the original value of criterion j at location i, and $C_j^{max}$ and $C_j^{min}$ are the maximum and minimum values of that criterion across the study area, respectively.

Weighting of Effective Criteria

To determine the relative importance of criteria in assessing the spatial suitability for adventure tourism events, the AHP was employed. AHP, as one of the most widely used and reliable MCDM methods, enables the structuring of complex problems into a hierarchical framework and allows for the simultaneous integration of quantitative and qualitative criteria [28]. This feature makes AHP a suitable tool for spatial planning studies and spatial suitability analysis in tourism, where criteria are inherently heterogeneous and multidimensional.

Initially, a hierarchical decision structure was developed with three main levels: (1) the overall research objective (determining spatial suitability for adventure tourism camp development), (2) main criteria (potential suitability for adventure activities, accessibility, attractions, and services), and (3) sub-criteria associated with each component. This structuring allowed the decomposition of the problem into analyzable components and reduced decision-making complexity.

Next, pairwise comparisons among criteria and sub-criteria were conducted using Saaty’s 9-point scale, where a value of 1 indicated equal importance and a value of 9 indicated extreme dominance of one criterion over another [29]. The results were arranged in an (n\times n) square matrix, where diagonal elements were 1 and elements below the diagonal were the reciprocals of the corresponding elements above the diagonal. To extract the relative weights, the pairwise comparison matrix was normalized by summing each column and dividing each element by its column sum. The average of each row in the normalized matrix formed the final weight vector, representing the relative importance of each criterion in achieving the research objective.

To assess the consistency of expert judgments, the Consistency Index (CI) and Consistency Ratio (CR) were calculated. The maximum eigenvalue of the matrix (${\mathrm{\lambda }}_{\mathrm{m}\mathrm{a}\mathrm{x}}$) was first estimated by multiplying the pairwise comparison matrix by the weight vector. Then, CI was computed as ($\mathrm{C}\mathrm{I}=({\mathrm{\lambda }}_{\mathrm{m}\mathrm{a}\mathrm{x}}-\mathrm{n})/(\mathrm{n}-1)$), and CR was obtained by dividing CI by the Random Index (RI). According to Saaty’s guideline, CR values less than or equal to 0.1 indicate acceptable consistency. In this study, CR values for all levels of the hierarchy were below the 0.1 threshold, confirming the validity of the derived weights.

The application of AHP in this study provides several advantages: (1) transparency in the decision-making process, (2) incorporation of expert judgment alongside quantitative data, and (3) direct integration of derived weights into the Weighted Linear Combination (WLC) model within the GIS environment. However, it should be noted that AHP results are somewhat dependent on expert judgment, and variations in perspectives may lead to changes in weights; therefore, consistency checks and the use of a group of experts are necessary to reduce bias. Overall, the AHP-based weighting framework in this study provides a methodologically robust foundation for multi-criteria spatial analysis and facilitates the systematic integration of environmental, infrastructural, and service criteria in assessing the spatial suitability for adventure tourism events.

To ensure the reliability and validity of the weighting process, a structured expert-based approach was adopted. A panel of 42 experts was consulted, comprising specialists from four main domains: tourism planning (13 experts), environmental management (11 experts), GIS and spatial analysis (10 experts), and regional development (8 experts). The selection of experts was based on purposive sampling to ensure domain-specific knowledge and practical experience. All experts had substantial professional experience ranging from 8 to 20 years and were actively involved in research or practical projects related to tourism development and spatial planning.

A Delphi-based iterative process was employed to enhance the consistency and credibility of expert judgments. In the first round, experts were asked to perform pairwise comparisons of the criteria based on their knowledge and experience in adventure tourism site selection. The results were then aggregated, and a summary of the group responses was shared with the participants. In the second round, experts were given the opportunity to revise their judgments considering the collective feedback, which helped reduce inconsistencies and improve consensus.

The final pairwise comparison matrices were constructed based on the refined judgments, and the CR was calculated to ensure acceptable levels of consistency. All matrices satisfied the standard threshold (CR < 0.1), confirming the robustness of the weighting process. This systematic approach enhanced the reliability of the derived weights and ensured that they reflect a balanced integration of multidisciplinary expertise.

3.2.2. Suitability Maps and Evaluation of the Three Main Components in Alternatives Areas

In the second stage, the primary objective was to identify selected areas with the highest potential for adventure tourism activities and to evaluate the three main components: accessibility, attractions, and services. This stage consisted of two key sub-steps:

First, a potential suitability map for adventure activities was produced using environmental and natural indices relevant to such activities. The data for each indicator, after standardization and weighting, were integrated into a continuous map using the WLC model (Equation (3)):

$$S_{Potential}=\sum _{i=1}^n{w}_i\cdot X_i$$

(3)

where $S_{Potential}$ is the final potential suitability score for adventure activities, $w_i$ is the weight of the i criterion, $X_i$ is the standardized value of the $i$ criterion, and n is the total number of indicators used for potential suitability. WLC model assumes relative independence among evaluation criteria. However, some degree of interdependence among environmental variables such as elevation, slope, snow cover, and vegetation is unavoidable. Despite this limitation, the WLC approach was retained because of its methodological transparency, and ease of interpretation. After generating the map, areas classified as high and very high suitability were identified as selected areas, and only these zones were considered for subsequent analysis of the three main components. This approach focused the analysis on areas with the highest tourism potential and improved the precision of spatial assessments.

In the second sub-step, after identifying the alternatives areas, the three main components including accessibility, attractions, and services were evaluated within these zones. Spatial data related to each component were standardized, weighted, and integrated using the WLC model to calculate the final score of each component in the selected areas (Equation (4)):

$$S_m=\sum _{i=1}^{n_m}{w}_i\cdot X_i$$

(4)

where $S_m$ is the final score of components m (accessibility, attractions, or services) in the selected area, $w_i$ is the weight of the $i$ criterion for component $m$, $X_i$ is the standardized value of the $i$ criterion, $n_m$ is the number of criteria for component $m$, and $m\in \{Accessibility,Attraction,Service\}$.

The output of this stage consisted of three separate maps showing the spatial suitability of accessibility, attractions, and services within the selected areas. These maps served as the basis for subsequent analyses and integration of components in the scenario-based stage, allowing the comparison of spatial dispersion and concentration of areas with the highest potential for developing adventure tourism events.

3.2.3. Scenario Development and Integration of Components in Alternatives Areas

In this stage, the potential suitability map for adventure activities and the three main component maps including accessibility, attractions, and services were processed only within the alternative’s areas identified in the second stage. Focusing on these selected zones ensured that analyses were conducted in regions with the highest capacity and potential for adventure tourism development. To assess the influence of weighting and prioritization of components on the final spatial suitability for adventure tourism camp development, four integrated scenarios were defined (

Table 3. Decision-making scenarios and component weights in each scenario.

Components	Balanced Scenario (S_bal)	Accessibility-Based Scenario (S_acc)	Attraction-Based Scenario (S_att)	Service-Based Scenario (S_serv)
Potential Suitability of Adventure Activities	0.52	0.52	0.52	0.52
Accessibility Suitability Component	0.16	0.48	0	0
Attraction Suitability Component	0.16	0	0.48	0
Service Suitability Component	0.16	0	0	0.48
Total	1	1	1	1

):

Balanced Scenario (S_bal): Equal weights were assigned to the three components including accessibility, attractions, and services so that the combined effect without prioritization could be evaluated. These three components were integrated with the potential suitability of adventure activities using equal weights.

Accessibility-Based Scenario (S_acc): In this scenario, only the accessibility component was combined with the potential suitability map to analyze the effect of accessibility priority on the spatial distribution and extent of suitable areas.

Attraction-Based Scenario (S_att): Here, only the attraction component was integrated with the potential suitability map to examine the role of natural capacities and destination attractiveness in determining spatial suitability.

Service-Based Scenario (S_serv): In this scenario, only the service component was combined with the potential suitability map to evaluate the importance of infrastructure, welfare, and security services in selecting areas for adventure tourism camp development.

The weighting structure of the scenarios was determined based on expert judgment obtained through consultations with specialists in tourism planning, environmental management, GIS and spatial analysis, and regional development. Experts were asked to evaluate the relative importance of the main components influencing the establishment of adventure tourism camps. Based on their assessments, the potential suitability of adventure activities was considered the fundamental prerequisite and therefore assigned a constant weight of 0.52 in all scenarios. The remaining weight (0.48) was allocated to the three components (accessibility, attractions, and services) either equally in the balanced scenario or entirely to a single component in the priority scenarios to examine the effect of different planning priorities.

In all four scenarios, the integration of components was performed using the WLC model. The general formula for calculating the final spatial suitability in the selected areas is expressed as follows:

$${\mathrm{S}}_{\mathrm{f}\mathrm{i}\mathrm{n}\mathrm{a}\mathrm{l}}={\mathrm{w}}_{\mathrm{p}}\cdot {\mathrm{S}}_{\mathrm{P}\mathrm{o}\mathrm{t}\mathrm{e}\mathrm{n}\mathrm{t}\mathrm{i}\mathrm{a}\mathrm{l}}+{\mathrm{w}}_{\mathrm{A}}\cdot {\mathrm{S}}_{\mathrm{A}\mathrm{c}\mathrm{c}\mathrm{e}\mathrm{s}\mathrm{s}\mathrm{i}\mathrm{b}\mathrm{i}\mathrm{l}\mathrm{i}\mathrm{t}\mathrm{y}}+{\mathrm{w}}_{\mathrm{B}}\cdot {\mathrm{S}}_{\mathrm{A}\mathrm{t}\mathrm{t}\mathrm{r}\mathrm{a}\mathrm{c}\mathrm{t}\mathrm{i}\mathrm{o}\mathrm{n}}+{\mathrm{w}}_{\mathrm{C}}\cdot {\mathrm{S}}_{\mathrm{S}\mathrm{e}\mathrm{r}\mathrm{v}\mathrm{i}\mathrm{c}\mathrm{e}}$$

(5)

where ${\mathrm{S}}_{\mathrm{f}\mathrm{i}\mathrm{n}\mathrm{a}\mathrm{l}}$ is the final spatial suitability score for the development of adventure tourism camps; ${\mathrm{S}}_{\mathrm{P}\mathrm{o}\mathrm{t}\mathrm{e}\mathrm{n}\mathrm{t}\mathrm{i}\mathrm{a}\mathrm{l}}$, ${\mathrm{S}}_{\mathrm{A}\mathrm{c}\mathrm{c}\mathrm{e}\mathrm{s}\mathrm{s}\mathrm{i}\mathrm{b}\mathrm{i}\mathrm{l}\mathrm{i}\mathrm{t}\mathrm{y}}$, ${\mathrm{S}}_{\mathrm{A}\mathrm{t}\mathrm{t}\mathrm{r}\mathrm{a}\mathrm{c}\mathrm{t}\mathrm{i}\mathrm{o}\mathrm{n}}$ and ${\mathrm{S}}_{\mathrm{S}\mathrm{e}\mathrm{r}\mathrm{v}\mathrm{i}\mathrm{c}\mathrm{e}}$ are the scores of each component in the selected area; and ${\mathrm{w}}_{\mathrm{p}}$, ${\mathrm{w}}_{\mathrm{A}}$, ${\mathrm{w}}_{\mathrm{B}}$ and ${\mathrm{w}}_{\mathrm{C}}$ are the weights assigned to each component according to the scenario. The analysis outputs resulted in four final spatial suitability map sets, enabling the comparison of how prioritization of each component affects the spatial distribution and extent of suitable areas. The final scores were classified into four classes including low, medium, high, and very high using the Natural Breaks method. The percentage coverage of each suitability class across different scenarios was calculated and compared, and the spatial distribution of suitability classes was examined at the study area level. Also, suitability values for each current adventure tourism site were classified into five levels (very low to very high) across four scenarios. For each scenario, relative percentages were calculated to quantify the distribution of sites within each suitability class. This approach enabled a comparative evaluation of scenario performance based on numerical suitability outcomes.

Finally, a sensitivity analysis was conducted using a ±10% weight perturbation approach. For each sub-criterion, its weight was individually increased and decreased by 10%, while the remaining weights were proportionally adjusted to maintain normalization. The model was recalculated for each case using the WLC method. The resulting changes in the extent of high and very high suitability classes were then quantified. To provide a more robust and interpretable measure, the final sensitivity value for each sub-criterion was calculated as the mean of the absolute changes obtained from the positive and negative perturbations. This approach reduces directional bias and reflects the overall influence of each factor on the model output.

4. Results

4.1. Potential Suitability Criteria for Adventure Tourism Activities

The analysis of criteria affecting the potential suitability for adventure tourism activities in Chaharmahal and Bakhtiari Province indicates that the province’s natural and climatic characteristics play a decisive role in identifying suitable areas (Figure 3). The curvature index is relatively uniform across the province, whereas elevation and slope exhibit significant variation. The highest elevations and steepest slopes are located in the northwest and eastern parts of the province, making these areas suitable for mountainous and challenging routes, while the south and southeast, with lower elevation and gentler slopes, are more appropriate for light activities and nature-based tourism. NDVI is higher in the south and southeast, enhancing opportunities for forest-related and nature-based events, whereas the northern areas, with sparse vegetation and limited water resources, impose restrictions on high-intensity adventure activities. Precipitation and river density are high in the west and northwest; combined with slope and terrain roughness, these areas are well-suited for mountainous and water-based activities. Conversely, the northeast and northern parts, with lower precipitation and fewer rivers, require careful planning and specialized equipment. Snow duration is longer in the northwest and central regions, providing favorable conditions for winter events, while the south and southeast, with shorter snow cover, are more suitable for seasonal and warm-weather activities. High wind speeds in the northwest and east also need to be considered in route design and event safety. As a result, the northwest and western areas of the province are identified as the best locations for intense and winter adventure events; the south and southeast are suitable for green tourism and light activities; and the central, eastern, and northeast regions, with moderate conditions or natural limitations, are more appropriate for light to moderate events or specialized planning. These findings highlight that intelligent site selection based on natural characteristics can optimize and safely utilize the province’s adventure tourism potential.

The results of the analysis of Chaharmahal and Bakhtiari Province’s capacity to adventure tourism camp development indicate substantial spatial variation across the province, with notable heterogeneity in potential (Figure 4). The highest potential is located in the northwest, where natural and geomorphological conditions are highly suitable for intense adventure events, including mountainous and winter activities. The western and central areas exhibit moderate potential, capable of hosting medium-difficulty events, particularly mixed activities combining nature-based tourism with light to moderate mountainous routes. In contrast, the northeast and northern regions show the lowest potential. Natural limitations in these areas such as sparse vegetation, limited elevation and slope, and difficult accessibility require careful planning and specialized equipment to conduct events. The south, east, and southeast display low to moderate potential and are more appropriate for light activities and nature-based tourism, while hosting high-intensity events in these areas is constrained. Classification results indicate that approximately 17.4% of the province falls into the “very low” class and 24.8% into the “low” class, representing areas with significant natural limitations suitable only for light or restricted nature-based activities. The majority of the province, 28%, falls into the “medium” class, allowing the design of mountainous routes and medium-difficulty events. Meanwhile, 20.9% of the area is classified as “high” and 8.9% as “very high,” reflecting strong potential for intense, winter, and specialized adventure activities.

4.2. Spatial Evaluation of Accessibility, Attraction, and Service Components Criteria

The results illustrated in Figure 5 indicate that road accessibility in most of the selected areas ranges from relatively good to high, particularly in the eastern, northern, and southeastern regions, where the movement of tourists and equipment to event sites is facilitated. Railway access varies across these areas; the east and southeast enjoy better connectivity, while the northwest and some parts of the west and central regions face limitations for rapid transportation. Access to bus and taxi stations is generally adequate across most areas, especially in the east, north, and southeast, supporting smooth tourist mobility. Overall, the highest accessibility is observed in the eastern and northeastern zones, whereas the western and northwestern areas require infrastructure upgrades due to limitations in public transport and railway stations. In summary, the eastern, northern, southeastern, and southern parts encompass most of the selected zones with high and very high suitability, offering favorable conditions for adventure tourism camp development. Conversely, some western and northwestern areas require planning and infrastructure improvements to ensure the safe movement of tourists and equipment.

The assessment shown in Figure 6, which synthesizes maps of the criteria influencing the spatial suitability of the Attraction component in Chaharmahal and Bakhtiari Province, indicates that the selected areas possess rich and diverse natural and ecosystem attractions. Forest cover and mountainous areas are highly prominent in most regions, particularly in the south, west, east, and northwest, providing suitable conditions for adventure activities such as mountaineering, nature tourism, and challenging trails. Protected areas in the southern and southeastern sections exhibit high values, playing a key role in habitat conservation and attracting nature-oriented tourists. Tourist sites, waterfalls, and springs also show high values across most regions, especially in the east, south, and west, enabling the design of diverse tourism routes and complementary recreational activities. The NDVI ranges from medium to high, indicating stable vegetation cover and natural resources suitable for tourism. Conversely, snow cover is low in most areas, limiting its contribution to winter attractiveness except in a few localized regions with relatively higher snow presence. Rivers across most areas show high values, facilitating access to water resources and diverse natural landscapes. Overall, the selected high and very high suitability areas in terms of attractions provide strong potential for adventure tourism events, particularly for mountain-based, nature-oriented, waterfall, and thrill-seeking activities, with the southern, western, and eastern regions offering the greatest capacity.

Evaluation of Figure 7 indicates that the selected sections are in a favorable condition in terms of access to human services and welfare infrastructure. The distance to cities and villages is relatively short in most sections, providing quick access to urban centers and local populations. Medical centers and emergency services also show high index values in the eastern and southeastern sections, ensuring safety and effective crisis management during adventure events. Hotels, hospitality, and commercial centers in most of the selected areas particularly in the east, south, and southeast have an appropriate distribution and quality, which enhances the capacity to host tourists and participants. In addition, law enforcement centers and provincial administrative centers are well distributed across the selected sections, facilitating supervision and coordination of events. Overall, the selected sections with high and very high suitability, in terms of access to welfare, medical, security, and tourist accommodation services, demonstrate significant capacity for the safe and well-organized hosting of adventure tourism events. This is especially evident in the eastern and southeastern sections, where the combination of good access to service centers and tourism infrastructure provides the potential for professional and attractive hosting of adventure tourists.

4.3. Evaluation of the Spatial Suitability Maps of the Accessibility, Attraction, and Service Components

The analysis of the spatial suitability maps for the Accessibility component in the selected regions indicates that the eastern sections have the highest level of suitability, with very favorable access to roads and transportation networks (Figure 8). The central and western sections show a greater distribution within low and moderate suitability levels, reflecting relative transportation constraints. Meanwhile, the southern and southeastern areas generally have acceptable accessibility, although in some locations greater attention to route management is required. From the perspective of attractions, the eastern and northern regions demonstrate the greatest coverage within high and very high suitability levels. Rich natural and cultural resources, tourism sites, and attractive landscapes are concentrated in these areas. In the central and northwestern regions, a higher percentage of areas fall within moderate and low levels, indicating a more scattered distribution of attractions and less diversity in tourism resources. The southern and southeastern areas display a combination of moderate to very high levels, suggesting the presence of notable but dispersed attractions. In terms of services, the eastern sections possess the highest level of service infrastructure, including hotels, hospitality centers, medical facilities, and emergency services. The southern and southeastern regions also provide relatively adequate services, although some indicators fall within moderate or low levels. In contrast, the western and northwestern regions show a greater concentration in low and moderate levels, reflecting limitations in welfare services and tourist support infrastructure.

The analysis of the percentage distribution of different spatial suitability classes for adventure tourism camp development indicates that all three components including Accessibility, Attractions, and Services are primarily concentrated within the moderate to high levels (

Table 4. Percentage of area within different suitability classes of accessibility, attraction, and service in target areas for assessing adventure tourism camp development.

Components	Very Low	Low	Moderate	High	Very High
Accessibility	10.8	19.2	26.9	30.8	12.4
Attraction	4.1	7.5	26.6	37.8	24.0
Service	9.5	18.1	22.2	27.6	22.6

). For Accessibility component, the largest share of the area falls within the moderate and high classes, totaling approximately 57.7%. This suggests that most target areas have relatively adequate access. However, only 12.4% of the area is classified as very high, while areas with very limited access (very low) account for about 10.8%. Regarding the Attractions component, the greatest share is concentrated in the high and very high classes, together comprising about 61.8% of the total area. This reflects a significant concentration of natural and tourism attractions within the target regions. Only 11.6% of the area falls within the low and very low classes. For Services component, the distribution is relatively more balanced. The high and very high classes account for approximately 50.2% of the area, whereas the low and very low classes comprise about 27.6%. This indicates a relatively uneven distribution of service infrastructure and highlights the need for service enhancement in certain areas. Overall, this distribution suggests that the target regions generally benefit from strong attractions and relatively good accessibility. However, service capacity is not evenly distributed and could serve as a key focus area for planning and developing adventure tourism events.

4.4. Scenario Development and Integration of Components in the Alternative’s Regions

The analysis and comparison of four spatial suitability scenarios for adventure tourism camp development indicate that the prioritization of indicators has a significant impact on the spatial pattern of suitability (Figure 9). In the first scenario (S_bal), where equal priority is given to services, accessibility, and attractions components, the distribution of suitability is more balanced. The eastern and northern regions continue to hold the largest share; however, parts of the south and southeast also show an upgrade to higher suitability classes, reflecting their overall potential for hosting well-balanced events. In the second scenario (S_acc), with priority given to accessibility component, the largest areas classified as high and very high suitability are concentrated in the east and north. This pattern reflects favorable road access and proximity to urban centers. In contrast, the west and northwest are predominantly classified within low and very low classes, highlighting accessibility constraints in these areas. The third scenario (S_att), which prioritizes attractions component, shows an increased concentration of high and very high suitability areas in the east, north, and southeast. This indicates a stronger presence of natural and adventure-related attractions in these directions. Meanwhile, the west and southwest account for a smaller share due to natural limitations or lower tourism appeal. In the fourth scenario (S_serv), with services component as the priority, the eastern and northern regions once again demonstrate the greatest coverage of high and very high suitability. However, some parts of the south and southwest remain within moderate and low classes, indicating the uneven distribution of service infrastructure and the need for its enhancement to effectively support adventure tourism.

Overall, the east and north remain consistently identified as highly suitable regions across all scenarios. The southeast and south improve their position when combined indicators are strengthened, particularly in the fourth scenario. In contrast, the west and northwest remain in lower suitability classes in most scenarios due to limitations in accessibility and services. This analysis demonstrates that the prioritization of components especially Accessibility and Attractions has a substantial influence on the selection of target areas, and that a balanced integration of indicators can lead to broader and more effective geographic coverage.

The comparison of the four scenarios reveals that changes in indicator prioritization significantly alter the spatial distribution of suitability classes. While the eastern and northern parts of the province consistently maintain relatively high suitability due to favorable environmental conditions and infrastructure, the most notable differences occur in transitional zones located in the southern and southeastern parts of the study area.

When the service component is prioritized, several areas that previously fell within the moderate suitability class shift into the high suitability category, reflecting the influence of accommodation facilities, emergency services, and tourism infrastructure in supporting adventure tourism activities. In contrast, when accessibility is given higher priority, certain mountainous areas in the western and northwestern regions experience a reduction in suitability due to limited transportation connectivity. These differences demonstrate that infrastructure-related indicators play a critical role in modifying the spatial pattern of suitable locations beyond the baseline environmental potential.

Table 5. Percentage of area within different spatial suitability classes for adventure tourism camp development across various scenarios.

Scenarios	Code	Very Low	Low	Moderate	High	Very High
Accessibility-Based Scenario	S_acc	11.0	23.0	28.7	27.2	10.2
Attraction-Based Scenario	S_att	5.7	19.6	31.6	30.6	12.4
Service-Based Scenario	S_serv	6.6	13.5	26.4	34.7	18.8
Balanced Scenario	S_bal	5.9	19.8	29.2	31.6	13.5

presents the percentage of area within different spatial suitability classes for adventure tourism camp development across four distinct scenarios. The analysis indicates that prioritizing specific indicators significantly affects the spatial distribution of suitability levels. In the first scenario, where accessibility is prioritized, the largest shares of area fall within the moderate (28.7%) and high (27.2%) classes, while the very high class accounts for only 10.2%. This suggests that when focusing on accessibility, many areas achieve relatively suitable conditions; however, only a limited number reach an excellent level of spatial suitability. The low and very low classes remain relatively extensive, together comprising 34% of the total area. In the second scenario, with priority given to attractions, the moderate and high classes increase slightly to 31.6% and 30.6%, respectively, and the very high class rises to 12.4%. This pattern indicates that emphasizing natural and adventure tourism attractions shifts more areas into higher suitability classes. The reduction in the very low and low classes (together 25.3%) reflects the concentration of tourism resources within the region. In the third scenario, where services are prioritized, the highest percentage of area falls within the high (34.7%) and very high (18.8%) classes, representing a significant increase compared to the previous two scenarios. This demonstrates that areas with stronger service infrastructure have greater capacity to host high-quality adventure tourism events, and that focusing on service provision substantially enhances overall spatial suitability. The low and very low classes decline to approximately 20% in this scenario. In the fourth scenario, which assigns equal priority to services, accessibility, and attractions, the area distribution across classes is relatively balanced. The moderate and high classes account for 29.2% and 31.6%, respectively, while the very high class comprises 13.5%. This scenario reflects a balanced integration of indicators, resulting in broader spatial coverage of suitable areas. Meanwhile, the very low and low classes decrease to 25.7%.

Overall, prioritizing services (S_serv) has the greatest impact on increasing the area classified as high and very high suitability. Emphasizing attractions (S_att) leads to growth in the moderate and high classes, while the balanced scenario (S_bal) provides relatively extensive coverage of suitable areas. This analysis demonstrates that the selection and prioritization of indicators can substantially influence both the quality and the spatial distribution of areas appropriate for adventure tourism camp development.

The comparison of suitability classes across scenarios reveals several differences with direct planning implications. In the balanced scenario, approximately 13% of the study area falls within the very high suitability class. When the service component is prioritized, this share increases substantially to approximately 19%, indicating that improvements in tourism infrastructure and service facilities can significantly expand the area capable of supporting high-quality adventure tourism activities. These increases are particularly noticeable in areas located along the eastern and southeastern development corridors, where service accessibility is relatively strong. In contrast, when accessibility is given greater priority, the proportion of areas classified as very high suitability decreases to about 10%, reflecting the limited transportation connectivity of several mountainous zones in the western and northwestern parts of the province. These differences highlight the important role of infrastructure investment and accessibility improvements in shaping the spatial distribution of suitable adventure tourism development areas.

Table 6. Percentage shift in high and very high suitability classes relative to the balanced scenario.

Scenarios	Code	High	Very High
Accessibility-Based Scenario	S_acc	−13.9	−24.4
Attraction-Based Scenario	S_att	−3.2	−8.1
Service-Based Scenario	S_serv	9.8	39.3

reveals substantial variation in the relative influence of each component on top-tier suitability classes. Prioritizing accessibility (S_acc) leads to a marked reduction in high (−13.9%) and very high (−24.4%) classes, indicating that accessibility functions primarily as a constraining factor rather than a transformative driver within the study area. In contrast, the attraction-based scenario (S_att) produces only minor reductions (−3.2% and −8.1%), suggesting that natural attractions are relatively well aligned with the balanced spatial structure and exhibit spatial stability. Most notably, prioritizing services (S_serv) results in a substantial increase in the very high class (+39.3%) and a notable rise in the high class (+9.8%). This demonstrates that service infrastructure acts as the dominant upgrading mechanism in enhancing spatial suitability. The findings indicate that many areas with strong environmental potential can be elevated to top-tier suitability through targeted investment in accommodation, medical, security, and hospitality infrastructure.

Table 7. Distribution of current adventure tourism sites across suitability classes in various scenarios (%).

Scenarios	Code	Very Low	Low	Moderate	High	Very High
Accessibility-Based Scenario	S_acc	0.0	14.3	21.4	42.8	21.4
Attraction-Based Scenario	S_att	0.0	7.2	7.2	50.0	35.6
Service-Based Scenario	S_serv	0.0	0.0	35.7	42.8	21.4
Balanced Scenario	S_bal	0.0	0.0	21.4	35.7	42.8

illustrates the percentage distribution of current adventure tourism sites across five suitability classes under four distinct planning scenarios. In the Accessibility-Based Scenario (S_acc), the majority of sites (42.8%) fall within the High suitability class, demonstrating that access-related factors such as proximity to roads and ease of reach play a key role in site suitability. About 21.4% of the sites are evaluated as very high, while 14.3% fall in the low class, suggesting that accessibility constraints limit suitability for a small group of locations. In contrast, the Attraction-Based Scenario (S_att) shows that half of the sites (50.0%) belong to the high suitability class, and a notable 35.6% are ranked very high, indicating a strong concentration of sites with high scenic or recreational appeal. The Service-Based Scenario (S_serv) mainly clusters around high (42.8%) and moderate (35.7%) classes, implying a need for further service infrastructure development to enhance suitability in some areas. Finally, the Balanced Scenario (S_bal), which integrates all major components (accessibility, attraction, and services), exhibits the most favorable overall distribution with 42.8% of sites categorized as very high and 35.7% as high. This balanced configuration suggests that a holistic approach considering multiple dimensions of suitability yields the highest potential for sustainable adventure tourism development across the study area.

The sensitivity analysis results, based on the mean absolute change of ±10% weight perturbations, provide a clear and stable measure of the influence of each sub-criterion (

Table 8. Sensitivity analysis based on mean absolute change (±10% weight variation).

Component	Criteria	Mean Δ High (%)	Mean Δ Very High (%)
Potential suitability for adventure activities	Curvature	2.0	2.7
	Elevation	2.6	3.3
	NDVI	2.2	2.8
	Precipitation	2.9	3.7
	River	4.4	5.5
	Slope	5.5	6.9
	Snow duration	3.2	4.0
	TRI	3.6	4.4
	Wind speed	2.7	3.4
Accessibility suitability	Road access	5.0	6.2
	Airport access	2.9	3.6
	Bus and taxi station access	2.5	3.1
	Railway station access	2.0	2.5
Attraction suitability	Forest cover	3.7	4.5
	Mountainous areas	4.9	6.0
	Protected areas	3.0	3.7
	Snow cover	2.3	2.9
	Tourism sites and attractions	4.3	5.3
	Waterfalls and springs	2.6	3.2
	NDVI	2.9	3.6
	Rivers	4.6	5.8
Service suitability	Cities	3.0	3.8
	Villages	2.5	3.1
	Medical centers	2.7	3.3
	Emergency service centers	2.8	3.5
	Accommodation centers (Hotels)	3.2	3.9
	Law enforcement centers	2.1	2.7
	Provincial center	3.1	3.8
	Restaurants	2.3	2.9
	Shopping centers	2.8	2.4

). The results indicate that slope (6.9%) and river-related factors (5.5–5.8%) are the most influential variables, highlighting the importance of terrain conditions and water-based features in determining suitable locations. Among accessibility factors, road access shows the highest sensitivity (6.2%), confirming its dominant role in facilitating tourism development. In the attraction component, mountainous areas, tourism sites, and rivers demonstrate high sensitivity, emphasizing the importance of landscape diversity and natural attractions. Service-related factors generally exhibit lower sensitivity values, indicating their supportive role in the model. Overall, the use of mean absolute change provides a robust assessment of model stability and confirms that environmental and attraction-related factors dominate the suitability outcomes.

5. Discussion

The findings of this study highlight the multi-dimensional nature of spatial suitability for adventure tourism camp development. The proposed framework integrates four key components (natural potential, accessibility, attractions, and services) within a GIS-based analytical environment, enabling a comprehensive evaluation of environmental, infrastructural, and human dimensions of tourism destinations. The natural potential component, relying on indicators such as slope, elevation, climate, and vegetation cover, plays a decisive role in assessing the level of difficulty, safety, and attractiveness of activities. The alignment of the results with Wang and Yang [22] indicates that an optimal combination of slope and elevation provides the greatest capacity for mountain-based activities. However, as noted by Becken [30], reliance on accurate and up-to-date environmental data can significantly influence the precision of the analysis.

The results also reveal important trade-offs between different development priorities, as demonstrated by the scenario-based analysis. When accessibility is emphasized, areas located near major transportation corridors gain higher suitability, while more remote mountainous zones experience reduced suitability due to limited connectivity. This pattern is consistent with the findings of Kasiyanchuk et al. [31], who highlight the critical role of transportation networks in tourism spatial planning. Conversely, prioritizing the service component increases the proportion of areas classified as highly suitable, particularly in regions where accommodation facilities, medical services, and safety infrastructure are already available. A balanced scenario, however, provides a broader distribution of moderately to highly suitable areas, illustrating the importance of integrating environmental attractiveness with infrastructural support. These results demonstrate that spatial planning for adventure tourism is highly sensitive to policy priorities and investment strategies. From a methodological perspective, the research framework demonstrates the usefulness of GIS-based MCDM approaches for tourism spatial planning. The integration of Min–Max standardization, AHP weighting, and WLC approaches commonly applied in tourism spatial analysis [15,22,32,33] enabled the systematic combination of diverse environmental and infrastructural indicators. Min–Max standardization enabled uniform scaling of criteria, while AHP, through pairwise comparisons, generated consistent expert-based weights. Although WLC offers simplicity and computational transparency, it assumes independence among criteria, a limitation also noted by Sadeghi et al. [34], who suggest the use of nonlinear models or local weighting methods to better capture complex interactions.

The study adopts a two-step evaluation approach in which areas with high and very high natural potential are first identified and then further evaluated using accessibility, attraction, and service indicators. This approach reflects the fact that adventure tourism activities are strongly dependent on specific environmental conditions, such as terrain characteristics, landscape features, and ecological suitability. In other words, the presence of adequate natural potential is considered a prerequisite condition for the development of adventure tourism camps. The main advantage of this approach is that it prevents areas with strong infrastructure but insufficient environmental suitability from being mistakenly identified as highly suitable locations for adventure tourism. However, the method may also exclude some locations where moderate natural potential could be compensated by strong accessibility or service infrastructure. Compared with a fully integrated evaluation of all criteria across the entire study area, the two-step approach places greater emphasis on environmental feasibility before infrastructure considerations. Therefore, the approach is particularly suitable for nature-based tourism activities where environmental characteristics play a dominant role.

Beyond methodological insights, the findings also offer important policy implications at the provincial scale. The spatial distribution of highly suitable areas suggests that strategic investments in transportation infrastructure and tourism services could significantly expand the potential for adventure tourism development. At the same time, careful planning is necessary to ensure that tourism expansion remains compatible with environmental conservation objectives, particularly in mountainous landscapes and areas located near protected zones. The results emphasize that successful development of adventure tourism depends not only on the presence of natural attractions but also on the synergy between environmental resources, accessibility, and service infrastructure.

The findings of this study also directly contribute to the achievement of the United Nations Sustainable Development Goals (SDGs). In particular, the spatial identification of highly suitable areas while excluding ecologically sensitive zones supports SDG 15 (Life on Land) by promoting habitat conservation and minimizing environmental degradation. By directing development toward areas with appropriate ecological resilience and existing infrastructure, the framework helps prevent biodiversity loss and uncontrolled land-use change. Furthermore, the strategic development of adventure tourism camps in highly suitable areas contributes to SDG 8 (Decent Work and Economic Growth) through the creation of local employment opportunities, diversification of rural economies, and strengthening of regional tourism value chains. The scenario-based approach ensures that economic benefits can be aligned with environmental sustainability objectives.

Beyond the spatial distribution of suitability classes, it is also important to consider the underlying mechanisms shaping these spatial patterns. The higher suitability observed in the eastern and northeastern parts of the province appears to result from the interaction of several structural factors. First, these areas benefit from relatively favorable topographic and environmental conditions, including suitable mountain landscapes, moderate slopes, and diverse natural attractions that support adventure tourism activities such as trekking and mountaineering. Second, these regions are characterized by better-developed transportation infrastructure, which improves accessibility to tourism sites and reduces travel barriers. Third, the spatial concentration of tourism services and support facilities, including accommodation, medical services, and security infrastructure, further strengthens their capacity to host tourism activities. In contrast, the lower suitability observed in some western and northwestern areas is mainly associated with infrastructural constraints and limited accessibility, despite the presence of attractive natural landscapes. These patterns suggest that the spatial suitability of adventure tourism camps is not determined by environmental potential alone, but rather by the combined influence of natural resources, infrastructure development, and service availability.

In the present study, the spatial suitability assessment was conducted using geographic datasets and GIS-based multi-criteria analysis, which are commonly applied in regional-scale tourism planning. While this approach allows for systematic evaluation of large areas, it does not directly verify the conditions of specific locations on the ground.

Consequently, the suitability maps generated in this study should be interpreted as preliminary spatial screening tools that help identify potentially suitable areas for adventure tourism development. Detailed field investigations and site-level feasibility studies are necessary before the implementation of tourism camps in specific locations.

5.1. Limitations and Recommendations

One of the main limitations of this study was access to up-to-date, accurate data with appropriate spatial resolution for certain indicators. A substantial portion of environmental variables, such as NDVI, snow cover duration, and climatic indices, were derived from remote sensing data. Although commonly used in spatial studies, such data may lack the capacity to detect subtle spatial variations at local scales [16]. This limitation may affect the accuracy of identifying highly suitable zones, as small variations in slope, vegetation cover, or snow conditions can have direct implications for safety and the quality of adventure experiences. Climate change represents another critical factor influencing the long-term sustainability of adventure tourism in mountainous regions. Variations in temperature and precipitation regimes may significantly alter snow duration, river discharge, and seasonal accessibility patterns. In particular, projected warming trends in Iran’s mountainous regions may reduce snow cover persistence, thereby affecting winter-based adventure activities. Similarly, increased precipitation variability could intensify extreme weather events, influencing safety conditions and infrastructure resilience. Therefore, future spatial suitability assessments should incorporate climate projection scenarios (e.g., CMIP6-based models) to evaluate the long-term viability of adventure tourism development under changing climatic conditions.

The accessibility assessment in this study is primarily based on spatial proximity to transportation infrastructure, including roads, airports, and railway or bus/taxi stations. While this approach is widely used in GIS-based suitability analysis, it does not fully capture the complexity of real travel conditions. Factors traffic network’s capacity, road grades (such as the difficulty of traveling on mountainous roads versus flat roads), travel costs (time/economy), and seasonal traffic restrictions (such as road closures in mountainous areas during winter) may substantially influence actual accessibility. These issues are especially relevant in the rugged terrain of the Zagros Mountains, where travel conditions can vary considerably between seasons. Therefore, future studies could extend the present framework by developing spatio-temporal accessibility models that integrate travel time analysis, road network characteristics, and seasonal accessibility conditions.

Another methodological limitation of this study relates to the weighting and aggregation procedures used in the GIS–MCDM framework. The weights derived from the AHP method are based on expert judgment and, despite the widespread validity of this approach, some degree of subjectivity and variation in evaluations may remain, particularly when quantitative and qualitative criteria are integrated simultaneously [22,33]. In addition, the application of the WLC model assumes relative independence among evaluation indicators, which may oversimplify the complex interactions among environmental, accessibility, and service-related factors [32]. In practice, certain variables may exhibit correlations or combined effects. For example, slope and snow duration jointly influence the safety and feasibility of winter adventure activities, while vegetation-related indicators such as the Normalized Difference Vegetation Index and forest coverage may be partially correlated. Likewise, service-related indicators such as medical centers and emergency response facilities may function in a complementary manner. Although the WLC approach remains widely used due to its transparency, interpretability, and suitability for regional-scale decision-making, this assumption may limit the comprehensive representation of interactions among indicators. Recent studies suggest that more advanced modelling approaches, such as geographically weighted regression (GWR/MGWR), nonlinear models, or fuzzy comprehensive evaluation methods, may better capture spatial heterogeneity and complex relationships among variables [13]. Furthermore, behavioral and perceptual indicators of tourists were not incorporated in this research, despite the important role that individual preferences, motivations, and risk tolerance play in destination choice [9,17].

Another limitation of this study is that the analysis represents a static assessment of current environmental and infrastructural conditions. In practice, climate change, land-use transformation, and future infrastructure investments may significantly modify spatial suitability patterns over time. Future research could extend the present framework by incorporating dynamic scenarios, such as climate change models, land-use change simulations, or infrastructure development plans, to evaluate how suitability patterns may shift under different long-term development pathways. Accordingly, it is recommended that future studies utilize environmental data with higher spatial and temporal resolution to enhance the sensitivity of suitability analyses [16]. The application of hybrid weighting models such as AHP–Entropy or ANP may help reduce subjective bias and achieve a more balanced integration of quantitative and qualitative data [22,33]. Moreover, integrating tourist behavioral data obtained from GPS tracking and social media into GIS-based frameworks could improve the identification of actual destination use patterns [35]. Finally, the use of advanced spatial models, such as MGWR or neural networks, is recommended to analyze nonlinear relationships among criteria [13]. Such approaches can facilitate the production of more operational suitability maps, strengthen evidence-based decision-making, and support more effective policymaking for the sustainable development of adventure tourism [15].

The evaluation framework developed in this study primarily relies on objective environmental and infrastructural data derived from spatial datasets, which are suited for regional-scale spatial planning. However, it does not incorporate the behavioral preferences and perceptions of adventure tourists (e.g., the different age groups’ demands for adventure difficulty, preferences for facilities), risk perception (e.g., tolerance for steep slopes or strong winds), and tourism experience evaluation which may limit the ability of the model to fully represent the heterogeneity of adventure tourism camps demand. Nevertheless, the current framework provides a robust first-order spatial assessment of environmental and infrastructural suitability for adventure tourism development. Future studies could further improve the framework by integrating behavioral preference analysis, and participatory approaches with GIS-based spatial modeling.

It should also be noted that socio-cultural and governance factors (e.g., community attitudes, land tenure, and regulatory constraints) are not fully captured by spatial indicators used in this study but can strongly influence the feasibility of tourism development in practice. Future research could therefore combine GIS-based spatial analysis with qualitative or participatory methods to better integrate social and governance dimensions into adventure tourism planning.

5.2. Practical Applications and Policy Implications

The findings of this study provide several practical and policy-related implications for tourism managers, urban planners, and regional policymakers. First, the spatial suitability maps can serve as a strategic tool for identifying infrastructure investment priorities. In particular, areas classified as moderate in the services scenario may be targeted for upgrading accommodation, medical, and security infrastructure to enhance the overall capacity of the adventure tourism destination [15].

Second, the scenario analysis enables decision-makers to select an optimal combination of indicators based on specific development objectives. For example, in regions with rich natural resources, strengthening accessibility and services can maximize the utilization of attractions. Conversely, in areas with well-developed infrastructure, greater emphasis on enhancing attractions and developing adventure routes is recommended. This approach aligns with the findings of Wang and Yang [22] in the Tianshan Mountains, demonstrating that a balanced integration of indicators improves the efficiency of tourism management.

Third, the results can provide a foundation for designing adventure tourism packages. Adventure routes, support services, and complementary facilities can be developed in highly suitable areas to improve visitor experience while ensuring safety and comfort. Similar practical applications have been confirmed in previous GIS-based ecotourism development studies, which identified such strategies as effective in increasing tourist satisfaction and length of stay [36].

Fourth, although adventure tourism camp planning may ultimately require micro-site evaluation at a finer spatial scale, the present study adopts a 500 m raster resolution to ensure consistency among the various spatial datasets used in the analysis. Some key indicators, such as remotely sensed environmental variables and regional infrastructure layers, are originally available at relatively coarse spatial resolutions. Therefore, a 500 m grid was selected as a practical compromise that maintains data compatibility while still allowing meaningful regional-scale spatial analysis. It should be noted that the resulting suitability maps are intended for regional-level planning and preliminary site identification, while detailed field-based assessments at finer scales are recommended for final campsite selection.

Finally, policymakers can utilize these findings to formulate regional development policies by managing the spatial distribution of investment and services. This can help prevent excessive tourist concentration in a single area and promote balanced spatial development. Such an approach is particularly important for provinces characterized by high spatial diversity and dispersed resources, and it aligns with the objectives of sustainable tourism development, improved destination management, and enhanced regional competitiveness [13]. Therefore, this research not only provides a scientific assessment of adventure tourism capacity but also offers a practical framework for strategic decision-making and regional-level policymaking.

While the results of this study identify areas with high and very high suitability for the development of adventure tourism camps, these findings should not be interpreted as an indication of unlimited development potential. From a sustainable management perspective, it is essential to consider the carrying capacity of these regions to prevent environmental degradation and ensure long-term viability. High-suitability areas are often environmentally sensitive and may include ecosystems with limited resilience to human pressure. Therefore, tourism development in these regions should be carefully managed by considering ecological thresholds, land degradation risks, and biodiversity conservation priorities. In this context, carrying capacity assessment plays a crucial role in determining the acceptable level of tourism activities. Integrating visitor limits, zoning strategies, and environmental monitoring can help maintain a balance between tourism development and environmental protection. Future research is recommended to incorporate quantitative carrying capacity models and field-based assessments to refine the spatial suitability outputs and support more sustainable decision-making. In addition, the implementation of adaptive management strategies, such as seasonal regulation of tourist flows and the designation of conservation buffer zones, can further enhance the sustainability of identified regions.

6. Conclusions

Adventure tourism, as a high-value segment of the tourism industry, requires careful planning and the identification of suitable areas based on natural characteristics, accessibility, and service infrastructure. The significance of this study lies in its provision of accurate spatial suitability maps, which enable better resource management, enhance tourist experiences, and reduce risks associated with adventure tourism camp development. Given the rapid growth of adventure tourism globally and in Iran, the development of decision-making tools based on spatial analysis and multi-criteria data is increasingly essential. The aim of this study was to conduct a multi-scenario assessment of spatial suitability for developing adventure tourism camps using a GIS-based MCDM approach. By integrating four key components including natural potential for adventure activities, accessibility, attractions, and services, the research provided a comprehensive and multidimensional analysis, identifying the capacities and limitations of different regions within the province. The results show that the eastern and northern regions of the province possess the highest spatial suitability for adventure tourism camp development due to the favorable combination of natural attractions, relatively good accessibility, and the presence of supporting service infrastructure. The southeastern and southern regions show moderate to high suitability and, with improvements in infrastructure and services, could support activities and events of moderate difficulty. In contrast, the western and northwestern regions exhibit lower suitability mainly due to limitations in accessibility and service availability, indicating the need for targeted infrastructure development and improved connectivity. Beyond the descriptive spatial patterns, the findings also reveal the underlying mechanisms shaping the suitability distribution across the province. Areas with higher suitability generally emerge where favorable natural conditions such as mountainous landscapes, river systems, and diverse natural environments coincide with relatively accessible transportation routes and existing tourism services. In contrast, regions with strong natural potential but limited accessibility or service infrastructure tend to show lower overall suitability, demonstrating that the spatial pattern of adventure tourism potential is not determined by a single factor but rather by the interaction and spatial coupling of environmental resources, accessibility conditions, and tourism services. Scenario analysis further demonstrated that indicator prioritization significantly affects the spatial pattern of suitability. Prioritizing services increased areas classified as high and very high suitability, emphasizing attractions expanded more areas into moderate and high classes, and a balanced approach provided broader and more equitable coverage of suitable zones. These results highlight that the spatial configuration of suitable areas is highly sensitive to planning priorities, indicating that policy choices and development strategies can substantially reshape the spatial opportunities for adventure tourism development. Practical applications of these findings include optimizing infrastructure planning, designing adventure tourism routes and packages, prioritizing investments, and formulating regional policies for balanced tourism development. Furthermore, the conceptual model and methodology proposed in this study are generalizable to other regions with similar characteristics at national and international scales, especially areas with diverse topography, natural attractions, and accessibility challenges. The model can assist planners and policymakers in identifying target areas, optimizing infrastructure, enhancing tourist experiences, and providing a scientific and practical framework for sustainable adventure tourism development. Ultimately, by integrating natural, accessibility, attraction, and service indicators within a GIS-based multi-scenario framework, this study not only maps spatial suitability but also provides insight into the key factors and interactions shaping the spatial pattern of adventure tourism potential, offering a useful reference for strategic decision-making and sustainable tourism development.