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Scientific Reports volume 16, Article number: 17022 (2026) Cite this article
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Saudi Arabia’s Vision 2030 includes a “Green Hajj” initiative to reduce the environmental impact of the annual pilgrimage. This study identifies optimal locations for large-scale solar PV plants near Meena, Muzdalifah, and Arafat in Makkah using GIS-based Multi-Criteria Decision Analysis (MCDA) and the Analytic Hierarchy Process (AHP). Key criteria assessed were solar irradiance, PV output, terrain, infrastructure proximity, and land use. The analysis categorized land suitability into five levels: 10.38% of the area (mainly northeast) is most suitable for PV with an estimated output of 1830 kWh/kWp/year; highly suitable zones comprise 10.87%, moderately suitable 23.58%, low suitability 26.02%, and 29.15% is unsuitable due to challenging terrain or proximity to protected areas. The most- and highly suitable categories could produce 6.75 GW of electricity; just 10% (675 MW) would meet Hajj’s peak demand of 500–600 MW. This approach offers a robust method for sustainable energy planning in sensitive, high-demand regions.
Heavy dependence on fossil fuels has driven up greenhouse gas emissions and heightened climate concerns. Fuels like petroleum, coal, and natural gas are limited and release large amounts of CO₂ when burned^24,37,45. In 2018, energy-related CO₂ emissions hit a record 33.1 gigatons, highlighting the need for clean energy alternatives. Renewable sources—solar, wind, water, and geothermal—are sustainable, widely available, and help cut emissions while supporting technologies such as green hydrogen. Many countries are investing in large-scale solar PV farms to address climate change and improve energy security. Research highlights solar energy’s key role in reducing emissions and increasing energy independence, with cost-benefit analyses showing clear environmental and economic benefits for solar and wind projects^3,17. In line with the United Nations Sustainable Development Goal 7 (Affordable and Clean Energy), many nations – including traditionally fossil-fuel-dependent ones – are accelerating policies to shift to deploy clean energy infrastructure (United Nations, 2021).
Saudi Arabia exemplifies this shift. Historically, the country’s electricity has been generated almost entirely from oil and natural gas²³. In 2018 only about 0.05% of its 383.8 TWh electricity output came from renewable sources¹¹. Solar energy is plentiful, but its adoption has been limited by cheap fossil fuels and technical issues such as heat and dust reducing efficiency. In Mina, Muzdalifah, and Arafat, installing solar panels is challenged by land allocated for pilgrims, safety requirements, and dense tent configurations that conflict with PV systems without significant redesign. Advances in cooling and dust-resistant PV technology, rising electricity demand, and the need to reduce CO2 emissions are driving interest in solar power⁴⁴. Over the past twenty years, Saudi Arabia’s electricity generation capacity has increased from 133.354 TWh/year to 449.426 TWh/year. The Saudi government launched an ambitious renewable energy program as part of Vision 2030⁵⁰. The Kingdom aims to install 9.5 GW of renewable capacity by 2030 – a target in which solar power is expected to play a leading role. Long-term strategies even envisage around 40 GW of solar capacity in later decades. This policy shift is driven by soaring domestic energy demand (which nearly tripled from 2000 to 2017) and a desire to reduce reliance on fossil fuels. Saudi Arabia’s geography and climate are highly advantageous for solar development: it receives some of the world’s highest solar irradiance levels and has vast expanses of undeveloped land suitable for solar farms. Leveraging these natural resources could transform the energy landscape and aligns with national goals for diversified, sustainable growth³⁵.
Within this context, the Holy Sites region of Makkah – specifically the pilgrimage areas of Meena, Muzdalifah, and Arafat – presents a compelling opportunity for large-scale solar PV implementation. Each year, these sites host millions of pilgrims during Hajj, leading to substantial increases in electricity demand for applications such as cooling, lighting, water desalination, and transportation. Peak power loads in the area reach 500–600 MW during Hajj, supplied mostly by distant oil-fired plants. This creates both logistical inefficiencies and environmental burdens^{1,2,4,16,21,26,28,42}. Building local solar capacity reduces dependence on distant power sources, lowers costs, and boosts resilience. The holy sites have ideal conditions for PV generation—arid climate, year-round sun, flat land, and little vegetation. Solar farms here would advance the “Green Hajj” initiative by lowering emissions and promoting renewables, while also supporting Saudi Arabia’s climate and energy goals.
However, optimally siting solar PV plants in this sensitive region is a complex spatial decision problem. It requires balancing various technical, environmental, and logistical factors (solar resource availability, terrain suitability), environmental considerations (land use, protected areas), and economic/logistical constraints (proximity to existing infrastructure and demand centers)^{36,43,46,47,53}. Combining Multi-Criteria Decision Analysis (MCDA) with Geographic Information Systems (GIS) offers an efficient approach for evaluating solar farm sites. Studies show suitability depends on factors such as solar irradiation, topography, climate, and access to grids and roads. GIS merges spatial data, while MCDA—particularly the Analytical Hierarchy Process (AHP)—helps prioritise each criterion. AHP assigns weights based on expert input and compares spatial parameters for decision-making purposes.
Numerous case studies have used GIS-MCDA for renewable energy site selection in regions such as North Africa, Asia, and the Middle East, demonstrating its use in identifying suitable locations^8,38,29; (Ouchani et al., 2021). While newer methods such as fuzzy logic, TOPSIS, and hybrid models address uncertainty and alternative comparison, AHP is still popular for its straightforward and reliable approach to weighting criteria^22,38,43. Akkas et al., applied AHP, ELECTRE, TOPSIS, and VIKOR methods to evaluate potential sites for solar PV farms in the Anatolian Region of Turkey⁵. AHP was applied in Tunisia to select wind-solar sites^46,47. Research indicates that the central and southern regions of the country are highly suitable for solar installations, with the potential to generate approximately 781.83 TWh of energy annually from solar sources. In the Karapinar region of Konya, Turkey, AHP analysis determined that 13.92% (840.07 km²) of the study area exhibits high suitability for solar farm development⁵². In Oman AHP method demonstrated that the central region has high suitability for solar energy farm establishments (Al-Awadhi, Al Ramimi, Al Jabri, & Abulibdeh, 2025). Monte Carlo and Fuzzy AHP methods, combined with GIS, were used in Cameroon to rank hybrid solar-wind sites for electricity and hydrogen production³⁹. AHP has been also applied to solar PV site selection in Bangladesh, Morocco, Kuwait, the United States, and Egypt^{15,30,32,36,41}.
Several studies in Saudi Arabia have utilised AHP for analysing site suitability for solar PV plants. Al Garni et al., for example, assessed potential PV plant locations and reported that 16% (300,000 km²) of the country’s area is considered suitable for developing utility-scale PV power plants, with the most appropriate regions located in the north and northwest. The identified suitable lands generally correspond to areas near main roads, transmission lines, and urban centres⁸. A study in Riyadh region, of Saudi Arabia, using the AHP method found that the north and northwest parts of the region—covering 16,748 km²—are the most suitable sites, with an 80% suitability rating¹⁰.
AHP-TOPSIS ranked solar, wind, biomass, geothermal, and their hybrids as energy potential options in the country. Solar was identified as the top alternative, with hybrid solar-wind next¹⁴. In the Western region of Saudi Arabia, the Analytic Hierarchy Process (AHP) was employed to assess the potential for Concentrated Solar Power (CSP). The evaluation indicated that approximately 70% of the province’s land is suitable for CSP development, with Makkah, Taif, Al-Khumra, and Turbah identified as the most advantageous locations³¹. A recent study assessing solar energy potential across various regions in the country found that, for PV technology, the Abha region ranked first with a performance score of 91%, indicating its exceptional suitability. Jeddah followed, achieving a performance score of 83%⁹. Whereas a study evaluated the solar PV potential of 17 selected cities in Saudia Arabia⁷, found that Tabuk city, located in northern Saudi Arabia, has the highest potential at 87%, while six other cities scored at or above 80%. Other studies have utilised AHP across the entire Mekkah Province^23,34, these studies have not necessarily focused on the Holy Sites. Additional studies have examined various locations throughout Saudi Arabia^27,40. To the best of our knowledge, this is the first study to specifically target the Muslims’ Holiest Sites in Saudi Arabia. This study offers new insights by applying AHP to a very specific context. It focuses on the key locations of the Hajj pilgrimage—Mina, Muzdalifah, and Arafat—which are operationally important and culturally sensitive, yet have not previously been the focus of detailed suitability assessments. The study also determines criteria weights based on the unique logistical and security needs of accommodating millions of pilgrims, unlike broader national or regional analyses. Additionally, it carefully considers land-use constraints due to sacred sites and temporary pilgrimage infrastructure, turning the “Green Hajj” policy into a practical spatial framework. As a result, this research goes beyond general regional recommendations to provide concrete, location-specific guidance for integrating sustainable energy into one of the world’s most complex and significant settings.
This paper presents a GIS-based AHP framework to assess solar PV suitability in the Holy Sites region of Makkah. The specific objectives are: (1) to establish a set of evaluation criteria (environmental, climatic, topographic, and infrastructural) relevant to solar farm siting in the study area; (2) to determine criterion weights through AHP pairwise comparisons, based on expert assessments of their relative importance; (3) to generate a spatially explicit suitability map (30 m resolution) by integrating the weighted criteria in GIS; and (4) to analyze the geographic distribution of high and low suitability zones, including estimates of solar energy output in optimal areas, and discuss implications for planning. The study aims to inform Saudi Arabia’s renewable energy initiatives within the context of the Hajj sites, illustrating how energy solutions may be integrated with cultural and environmental considerations. The manuscript is structured as follows: Sect.  2 outlines the study area, Sect.  3 details the methods, Sect.  4 covers results and discussion, and Sect.  5 summarizes the conclusions.
The study focuses on the environs of Meena, Muzdalifah, and Arafat Fig. 1, which are key sites in the Hajj pilgrimage, located in the Makkah region of western Saudi Arabia. Geographically, this area lies in the Hejaz mountains at the edge of the Saudi Arabian Shield. Meena is a narrow valley situated about 8 km east of the Grand Mosque (Masjid al-Haram) in Makkah, roughly at 21.42° N, 39.89° E. It is often referred to as the “City of Tents” due to the tens of thousands of temporary tents that accommodate pilgrims during Hajj. Muzdalifah is an open plain about 9 km southeast of Meena (approx. 21.39° N, 39.89° E), located along the route between Meena and Arafat. Pilgrims gather and rest overnight at Muzdalifah after the Day of Arafat. Arafat is a broader area centered around Jabal Arafat (Mount Arafat), about 20 km southeast of central Makkah (around 21.35° N, 39.99° E). The Plain of Arafat is the site of the peak Hajj ritual (the Wuquf on the Day of Arafat), where pilgrims stand in prayer from noon until sunset on the 9th day of the Islamic month Dhu al-Hijjah.
Study area location
The region features an arid climate with very low annual rainfall (often less than 100 mm/year) and high summer temperatures (up to 45 °C). It receives some of the highest global horizontal irradiance worldwide, averaging 2000–2200 kWh/m² per year. The abundant solar resource, undeveloped land, and existing infrastructure make the area suitable for solar PV development, though careful site selection is needed to avoid conflicts with pilgrimage activities and environmental, topographic constraints, permanent structures, and any environmental or topographic constraints (e.g., mountainous slopes, flash flood pathways, etc.). In this study, we defined a contiguous study area encompassing the valleys and plains of Meena, Muzdalifah, and Arafat and their immediate surroundings (approximately a few hundred square kilometers in total area). The boundary was set to include areas suitable for evaluating potential solar farm sites to support holy site energy needs. Urban zones in Mekkah, Mina, Muzdalifah, and Arafat—with dense development and permanent pilgrim facilities—were excluded and marked as “Holy sites limit” in Fig. 1.
This method tackles energy issues at holy sites and offers a model for renewable energy planning in sensitive areas, balancing technical needs with preservation. Our findings provide actionable guidance for policymakers and developers supporting Saudi Arabia’s renewable energy goals and the requirements of its holiest Islamic locations.
Prior to outlining the methodology, we wish to confirm that conducting this research in Saudi Arabia did not require any institutional, national, or international guidelines or permissions.
Geographic Information Systems (GIS) are highly proficient in spatial analysis, enabling the geographic modeling of problems to yield results through advanced computer processing. This methodology is particularly effective for assessing site suitability, forecasting outcomes, interpreting spatial changes, and identifying patterns.
This study employed GIS-based Multi-Criteria Decision Analysis (MCDA) to assess several criteria and identify optimal locations for solar photovoltaic (PV) farms in the Holy Sites region. Figure 2 outlines the workflow, which included: (1) selecting criteria and gathering relevant data, (2) utilizing the Analytic Hierarchy Process (AHP) for MCDA, and (3) creating suitability maps through spatial overlay methods. Spatial analysis was performed with ArcGIS Pro, and criterion weights for the GIS evaluation were calculated using MS Excel.
Workflow diagram for PV solar plant site selection procedures
For solar farm site suitability, we identified twelve criteria from literature and local context, grouped into Climatic, Topographic, Environmental, and Economic/Infrastructural categories. These cover solar potential, terrain, land use, and infrastructure access. Table 1 lists each criterion, its data, and sources.
All spatial datasets were projected to WGS 84 / UTM zone 39 N and resampled to a 30 × 30 m grid for consistent cell-based analysis. While this high resolution helped identify suitable parcels, it reduced detail in coarser datasets like climate surfaces. Each criterion was represented as a GIS layer and standardized on a suitability scale from 1 (very low suitability) to 5 (very high suitability). Normalization is required to integrate criteria with varying units and ranges in a consistent manner. A combination of benefit functions (where higher criterion values are preferable) and cost functions (where lower values are preferable) was used for reclassification. For instance, Global Horizontal Irradiance (GHI) scores increase with higher irradiance (benefit), while slope and distance from grid decrease with steeper terrain or greater distances (cost). Class thresholds were determined based on literature sources and expert advice. As an example, areas with slopes exceeding 15° received low scores due to construction and panel orientation challenges, whereas areas with slopes below 3° received the highest scores. Land cover was reclassified into five classes (1 to 5) representing ranks of importance using GIS: open undeveloped land was rated suitable (score 5), while built-up or restricted areas, such as urban zones, existing site facilities, and major roads, were considered unsuitable (score 1). For distance-based criteria (roads, grid, settlements), Euclidean distance rasters were calculated, and locations within optimal ranges of infrastructure (e.g., 0.5–5 km from a road) were assigned higher suitability. Areas less than 100 m from infrastructure were categorized as “restricted” due to right-of-way considerations, and those beyond 10 km were considered less favorable. All criterion layers were converted into five-class rasters reflecting relative suitability for solar PV site selection.
The Analytic Hierarchy Process (AHP) is designed to explicitly integrate multiple conflicting criteria in decision-making⁴⁹. AHP has been developed by Saaty⁴⁸. It has been widely employed in research to evaluate the suitability of solar PV sites, reflecting its growing adoption as a robust decision-making tool^{8,18,19,20,29,33,43,51}. AHP uses expert knowledge-based pairwise comparison procedure to judge the relative significance/hierarchy of the criteria^46,47. These judgments form a Pairwise Comparison Matrix (PCM) that shows the overall relative importance and preferences of the experts. The AHP tool relies on fundamental four steps: defining the hierarchical structure using PCM (step 1); relative weighting of criteria (step 2); consistency assessment of the PCM by calculating Consistency Ratio (CR) (step 3); and finally weighted-overlay of criteria layers with their weights in GIS (step 4).
Pairwise comparison involves evaluating two criteria at a time to determine their relative importance toward achieving a specific goal, using expert-knowledge and insights and a consistent scale. Typically, the standard 1–9 scale introduced by Saaty⁴⁸ is applied: a score of 1 indicates both criteria are equally influential, while a score of 9 signals that one criterion has a much greater effect on the mapped variable than the other. In this study, AHP was organized with a single hierarchical level comprising 12 criteria beneath the overarching goal of “optimal solar PV site selection”. Energy planning experts familiar with Saudi Arabia and the Hajj sites were consulted in conducting pairwise comparisons for solar site selection. Three domain experts were selected based on their extensive experience in solar energy planning, GIS-based environmental analysis, and familiarity with the Saudi Arabian context, particularly the Holy Sites region. The experts were engaged independently through individual structured interviews. Each expert was provided with a detailed description of the twelve selected criteria and the objective of the study. They were then asked to independently complete pairwise comparison matrices using Saaty’s 1–9 scale (Table 2), assessing the relative importance of each criterion pair for solar PV site selection in the study area.
To aggregate the individual judgments and derive a single representative comparison matrix, the Geometric Mean Method was employed. This method is recommended in AHP for aggregating group decisions as it preserves the reciprocal property of the pairwise comparison matrices. Specifically, for each entry a_iⱼ in the aggregated matrix, the geometric mean of the corresponding entries from the three experts’ matrices was calculated. This aggregated matrix was then used to compute the final criterion weights (Table 6) and the Consistency Ratio (CR = 0.024), ensuring the collective judgment was both consistent and representative of the expert panel’s consensus. This structured approach enhances the transparency and replicability of the weight derivation process.
If a criterion “i” is assigned a non-zero value (ranging from 1 to 9) in comparison to a factor “j”, then the reciprocal value is attributed to “j” when compared to “i” (ranging from 1 to 1/9). This reciprocal relationship reflects the dynamic interaction between the two factors and constitutes a fundamental component of the AHP’s comprehensive analytical methodology. Through pairwise comparisons, qualitative judgments is translated into quantitative weights. Accordingly, a PCM is formulated according to Saaty’s scores previously derived. The diagonal scores are set at 1, as each factor was being compared to itself. In our case a twelve by twelve PCM was formulated, as shown in Table 4 below.
The PCM were normalized using the eigenvector approach (Saaty, 2003). The eigenvector approach is the standard AHP way to convert a PCM into a normalized priority (weight) vector. The normalized PCM elements were calculated by dividing the element values, in Table 4, by their respective total column values, shown in Table 5. Then the eigenvector values were subsequently calculated for each criterion by dividing each sum of row values in the normalized PCM by the total criteria count (12 criteria in our case). The eigenvector and the criteria weights are shown in the last two columns in Table 5.
The pairwise criteria judgment is based on subjective comparisons and can lead to potential inconsistencies in the PCM that can lead to fraud weightings of the criteria. Consistency ratio (CR) measure was introduced by Saaty to quantitatively assess the consistency of the criteria weighting^48,49. CR helps assess the logical coherence and internal consistency of the relative judgments provided by experts, as it quantifies the extent of such inconsistencies. A CR value below 0.1 (< 10%) indicates an acceptable level of inconsistency, meaning the derived weights are sufficiently consistent and reliable for use in the subsequent analysis. If the CR exceeds 0.1, it signals significant contradictions, and a revision of the expert comparisons is recommended to improve coherence.
The CR is calculated by dividing the Consistency Index (CI) by the Random Consistency Index (RI) value, as shown in Eq. (1).
where, CI is the consistency index, and RI is the random consistency index. The CI is calculated using Eq. (2):
Where: λ mαx: a total value of Weighted SUM Values divided by Criteria Weights. n: the number of the applied criteria in the study.
Following the derivation of the criterion weight vector from the PCM in Table 5, the principal eigenvalue (λ max) was calculated. This involved computing the weighted sum vector (by multiplying the original PCM by the derived weight vector) and then dividing each element of this resulting vector by its corresponding criterion weight. The principal eigenvalue (λ max) is the arithmetic mean of these resultant values. For this study, λ max was calculated to be 12.4. This value represents the principal eigenvalue (λ max). Substituting this value into Eq. (2) yields:
({text{CI }}={text{ }}({text{12}}.{text{4}}, – ,{text{12}}){text{ }}/{text{ }}({text{12}}, – ,{text{1}}),=,0.{text{4 }}/{text{ 11}}, approx ,0.0{text{36}})
This very low CI value indicates a minor deviation from perfect consistency and confirms the reliability of the established criterion weights.
The principal eigenvalue measures how much a matrix deviates from consistency and equals the sum of the eigenvalues for the considered factors. For a PCM to be nearly consistent, its principal eigenvalue should be at least equal to the number of factors (n), which is 12 in this case. In this study, the PCM’s principal eigenvalue was 12.4, exceeding 12. The calculated CI value was 0.036, confirming that the criteria weights were established correctly.
RI value, in Eq. (1) above, is obtained from the Random Index scale⁴⁸, was 1.54 due to the number of criteria in the study (12 Criteria), Table 3 below.
Following the assessment of criteria-weight consistency as outlined in Step 2, each criterion within the GIS thematic layer was classified into five distinct groups using the Natural Breaks (Jenks) method in ArcGIS Pro. This technique organizes data into categories based on inherent groupings, ensuring maximum similarity within each group and pronounced differences between separate groups (ESRI, ²⁵). Groups in each thematic layer are then assigned values from 1 to 5 through reclassification, considering both benefits (where higher values indicate greater preference) and costs (where lower values are more desirable). This process standardizes each criterion within a thematic layer into a five-level ordinal suitability score, with 1 representing the lowest suitability and 5 indicating the highest. This transformation enabled the integration of diverse data types into a unified analytical framework while ensuring that each criterion’s classes reflect meaningful and practical distinctions in suitability.
After the weights of criteria, and the five suitability scores within each criterion thematic-layer are determined, all criteria layers were integrated in ArcGIS through a weighted overlay to calculate a suitability score for each 30 m cell. Each criterion raster was multiplied by its respective weight (Wₖ), and the results were added together to generate a composite suitability score (E_iⱼ) for each cell. Wₖ denotes the weight of criterion k, and S_iⱼₖ is the standardized suitability score (1–5) of cell ij for criterion k, as indicated by Eq. 3 below:
This formula is essentially a weighted overlay operation, and it was executed using the Weighted Overlay in ArcGIS Pro for efficiency. The result is a continuous suitability value for each 30 m cell.
The weighting of evaluation criteria was carried out using AHP, a robust multi-criteria decision-making method for converting qualitative expert judgments into quantitative priorities⁴⁸. A total of twelve criteria relevant to solar photovoltaic (PV) site selection were evaluated: solar radiation, wind speed, precipitation, slope, aspect, elevation, settlement proximity, road network, power line proximity, relative humidity, temperature, and land use. Each pair of criteria (i, j) was compared based on its relative influence on solar PV site suitability using Saaty’s fundamental 1–9 scale, where a score of 1 denotes equal importance, and values of 3, 5, 7, and 9 represent increasing degrees of importance of one factor over the other. Reciprocals (e.g., 1/3, 1/5) are used to reflect inverse importance relationships between criteria^8,48. If criterion i is judged to be x times more important than criterion j (so ({a_{ij}}=x)), then criterion j must be (1/x) as important as criterion i (so ({a_{ji}}=1/x)). This reciprocal property (({a_{ij}}=1/{a_{ji}})) ensures logical symmetry in the pairwise comparison matrix and supports consistent derivation of criteria weights. The judgments were provided by domain experts in solar energy systems, GIS-based planning, and environmental assessment, with specific knowledge of Saudi Arabia’s climatic and infrastructural context. For example, solar radiation was ranked five times more important than precipitation (value = 5), underscoring the primacy of insolation in determining PV performance. Slope was ranked three times more important than settlement proximity, due to its direct impact on installation feasibility and structural stability. Road network proximity was judged significantly more important than power line proximity (value = 6), reflecting the practical need for access during installation and maintenance. In contrast, land use was treated as moderately more important than humidity, acknowledging that undeveloped or non-restricted land is essential, while atmospheric moisture poses a lesser constraint in arid climates. All 66 pairwise comparisons formed a complete 12 × 12 PCM matrix in Table 4, from which the normalized PCM, eigenvector, and criteria priority weights were derived in Table 5. The normalized PCM elements were calculated by dividing the element values, in Table 4, by their respective total column values, and the eigenvector values were calculated for each criterion by dividing each sum of row values in the normalized PCM by the total criteria count 12. The eigenvalues are multiplied by 100 to produce the final weights in percentage used in the weighted overlay GIS model. The Consistency Ratio (CR) was computed to assess the internal coherence of the judgments. With a CR of 2.4%, which is well below the acceptable threshold of 10%, the matrix exhibits strong consistency, confirming the reliability of the expert inputs. In summary, this weighting process allowed each criterion’s influence on solar PV suitability to be explicitly quantified based on informed expert assessments. These weights form the basis of the spatial decision-making model used to generate the final suitability map.
The AHP weighting results reveal the relative significance of the evaluated criteria in determining suitable solar PV sites (Table 6).
Prior to applying the weights from Table 5 in the GIS overlay analysis, the spatial criteria were prepared through three interconnected stages illustrated in Figs. 3, 4 and 5. Figure 3 presents the spatial distribution of the twelve input criteria in their original form, highlighting the geographic variability of each influencing factor. The Natural Breaks (Jenks) classification method is used to group values in each criterion into 5 groups. Subsequently, these groups were assigned values from 1 to 5, i.e. standardized into five ordinal suitability classes (1 = lowest suitability, 5 = most suitable) as shown in Fig. 4. Finally, Fig. 5 presents the core output of the study: the composite suitability map generated by applying the AHP-derived weights (Table 6) to the reclassified layers using the weighted overlay tool in GIS. This map categorizes the study area into five final suitability classes for solar PV development.
Spatial distribution of the twelve input criteria used in the solar PV site suitability analysis. The criteria include climatic factors (wind speed, humidity, precipitation, temperature, global horizontal irradiance), topographic factors (slope, aspect, elevation), and infrastructural/environmental factors (built-up area, proximity to power lines, road network, and land use). Green areas indicate more favorable conditions for solar PV development, while red zones represent less suitable regions
These classes were then standardized to a scale of 1 to 5 for suitability, with 5 being most suitable and 1 least suitable, as illustrated in Fig. 4. This method grouped similar values and maximized variance between classes, setting clear thresholds in the data (e.g., steep versus flat slopes, high versus low irradiance). For example, wind speeds over 6.4 m/s, GHI above 2180 kWh/m²/year, and locations within 2 km of roads received top suitability scores (class 5). Each reclassified layer was weighted and combined to create the final suitability map.
Reclassification of each criterion into five suitability classes using the Natural Breaks (Jenks) classification method, which identifies natural groupings and gaps in the data. Class 1 representing the lowest level of suitability and Class 5 denoting the highest
AHP produced relative weights for the twelve criteria (Table 5), showing their impact on solar PV site selection in Makkah based on expert judgment and regional features.
Climatology data indicate that solar radiation was the most significant factor (21.5%), as solar energy output depends on solar insolation. Figure 3 displays elevated solar irradiance in the northern and northeastern regions of the study area, which corresponds to higher significance in Fig. 4 and results in greater suitability scores in those areas shown in Fig. 5. This finding aligns with prior studies in arid environments, which consistently identify solar resource availability as the single most critical driver of PV siting^{6,9,12,13,14,38}.
Road network proximity ranked as the second most important factor (17.5%), highlighting the key role of accessibility in construction, operation, and maintenance. The high weight indicates experts’ focus on logistical feasibility, since even areas with ample land may face challenges if site access is poor. Roads around holy sites and in the north-central region, shown in Figs. 4 and 5, lead to higher suitability in nearby zones in the final results.
Two topographic factors- aspect (14.4%) and slope (12.2%) followed- were identified as influential, as both criteria affect irradiance exposure and constructability. South-facing slopes, Fig. 3, received higher scores due to their orientation with solar angles in the Northern Hemisphere. Flat or gently sloping terrain (also shown in Fig. 3) minimizes self-shading and allows for efficient PV layout. These considerations contributed to the designation of favorable zones in the north and northeast.
Wind speed (6.4%) and land use (6.8%) were identified as moderately significant factors in the analysis. While moderate wind contributes to passive cooling of photovoltaic modules, spatial variability within the study area remained limited. Land use map served to distinguish barren zones, which are deemed suitable, from built-up areas or regions with vegetation, considered less suitable. As shown in Fig. 3, the majority of the territory is classified as non-urban, offering enhanced flexibility for development.
Precipitation (5.6%), settlement proximity (4.4%), humidity (4.3%), and elevation (2.6%) were less influential but included for a thorough assessment. Low rainfall and humidity, typical of the arid region, had minor effects on PV soiling or cooling due to limited spatial variation (Fig. 3). Elevation also showed little variation and only modestly influenced temperature.
The lowest-weighted criteria were power line proximity (2.5%) and temperature (1.9%). This is notable: while power lines are necessary for interconnection, the experts indicated that new lines could be extended if the site is otherwise optimal. Likewise, while high ambient temperatures can reduce PV efficiency, the uniform heat across Makkah reduced the discriminatory power of this factor. Both criteria had limited influence on the final suitability output, see Sect.  4.3 Suitability Map and Spatial Distribution.
The findings show that climatic factors—Solar radiation (21.5%), Wind speed (6.4%), Precipitation (5.6%), Humidity (4.3%), and Temperature—with solar radiation having the highest proportion, made up nearly 40% of the overall decision weight. Topographic constraints were next at 29.2%, highlighting the significance of land form for physical feasibility and performance. Economic/infrastructure factors contributed 24.4%, indicating a notable but lesser role compared to environmental criteria. Land use, classified under the environmental category, accounted for 6.8% of the total, which is relatively small but relevant for considerations such as avoiding urban or restricted areas. The AHP matrix’s consistency ratio was 0.024, suggesting reliable and coherent assessments.
During the final stage of analysis, the twelve standardized criteria were integrated according to their AHP-derived weights using the Weighted Overlay tool in ArcGIS Pro. This methodology resulted in a composite suitability surface for solar PV farm development, classified into five categories: Unsuitable, Low, Moderate, High, and Most Suitable, as depicted in Fig. 5. The ‘Holy Sites Limit’ region, shown in grey, is excluded from the analysis. The region is depicted in the figures to provide demonstration and context. The resulting map displays a heterogeneous spatial distribution determined primarily by climatological, topographical, economic, and infrastructure accessibility factors, with environmental constraints exerting a comparatively lesser influence.
Photovoltaic Solar Farm Suitability Map for the Vicinity of the Holy Regions
The most promising zones- classified as “High” and “Most Suitable” (green colored classes) -are predominantly concentrated in the northeast sectors of the study area. These zones correspond to relatively flat open lands that receive excellent solar radiation (GHI) and are unencumbered by development with minimal land use conflict, as shown in Figs. 3, 5 and 6. These regions benefit from being far enough from the densely built pilgrimage camps to have available land, yet close enough to infrastructure like main roads and a power substation near Meena and Muzdalifa to facilitate grid connection. They also have near-optimal orientation and minimal slope, broad valley floors or gently undulating terrain. Based on our analysis, these regions account for 21.25% of the total land area. Approximately 10.38% of the study area is classified as “Most Suitable,” and 10.87% falls under the “High” suitability category, as shown in Fig. 6. These zones have PV output potentials of 1830 and 1810 kWh/kWp/year, respectively, according to Solargis PVOUT data for standard 1-axis tracking PV systems. This is a significant proportion, given the solar resource, indicating a large potential for solar development. Such output is comparable to some of the highest-yield solar farm sites globally, reflecting the superb insolation in Makkah’s climate.
Areas of suitability classes, percentage of total land, and potential PV
Moderately suitable areas (yellow color), which comprise 23.58% of the study region, are primarily found in the central and southeastern portions. These locations have adequate solar irradiance but may present certain limitations, including steeper slopes, increased distances from infrastructure, or more complex land cover such as gravel plains or elevated terrain. Some internal sections between high-suitability zones are also classified within this category. These regions generally exhibit one or two limiting factors that result in mid-range scores. For instance, the northern section near Makkah city benefits from strong solar irradiance but features steeper terrain and greater proximity to urban areas, necessitating careful planning to prevent conflicts with existing land uses. Similarly, certain interior locations may have marginally higher elevations or increased distances from roads, reducing their accessibility. Although these areas remain suitable for development, they may require additional investment in site grading or infrastructure connections.
Areas classified as Unsuitable (29.15%) and Low Suitability (26.02%), which together constitute 55.17% of the total area, are primarily located in the south, southwest, and the northwestern hills. These regions also include zones surrounding the Holy Sites region, which are designated as restricted areas for practical and cultural reasons. Factors such as steep terrain, elevated altitude, proximity to sacred sites (including Meena and Arafat), and distance from roads and electrical infrastructure contribute to these classifications. Land adjacent to pilgrimage camps and developed zones received low suitability scores to maintain buffers around holy sites. These locations are shown in orange and red in Fig. 5 and have lower photovoltaic output potential, averaging 1650–1740 kWh/kWp/year, as illustrated in Fig. 6.
The results indicate that climatic and topographic factors were predominant, collectively representing more than 68% of the decision weight, as illustrated in Fig. 7. In contrast, infrastructure and land use, while essential, contributed less to the overall determination. This outcome aligns with the region’s ample availability of undeveloped land and the strategic emphasis on optimizing energy output. .
Relative influence of grouped criteria on solar PV site selection derived from AHP weights. Climatic factors (39.7%) were the most influential, followed by topographic (29.2%), economic/infrastructure (24.4%), and environmental (6.8%) criteria, highlighting the dominant role of solar resource and terrain in determining optimal sites
A valid consideration arising from the spatial distribution of results (Fig. 6) is the relative distance of the identified “Most Suitable” zones from the primary electricity demand centers in Makkah and the Holy Sites. While proximity to load centers is undeniably a key economic and technical factor in power plant siting, the criterion of ‘distance to Makkah/the Holy Sites’ was not explicitly integrated into the AHP model. This deliberate omission is justified by the unique geographical and infrastructural constraints of the study area. The immediate peripheries of Makkah, Mina, Muzdalifah, and Arafat are characterized by intensive urban development, permanent pilgrim facilities, and the extensive seasonal tent cities, leaving virtually no contiguous parcels of vacant land suitable for utility-scale PV development. Furthermore, the limited undeveloped areas within a close radius are predominantly situated within the rugged terrain of the Hijaz foothills. These zones exhibit steep slopes (> 15°), complex topography, and significant shadowing effects, rendering them economically and technically infeasible for large-scale solar farms-a fact already captured and penalized by the low suitability scores from the slope and aspect criteria in our analysis. Consequently, incorporating a distance-to-demand criterion would not have shifted the high-suitability classification closer to the city. Instead, it would have systematically assigned low scores to the nearby areas due to the dual constraints of land unavailability and topographical incompatibility. Therefore, the model’s prioritization of solar irradiance, terrain slope, land-use compatibility, and access to roads and grid infrastructure logically identified the northeastern sectors as optimal. These areas, though farther from the demand epicenter, represent the only feasible compromise, offering the essential combination of high solar yield, constructable flat terrain, and minimal land-use conflict, which outweighs the increased transmission distance in this specific context.
The spatial analysis herein demonstrates that integrating GIS and AHP is an effective approach for renewable energy site selection in the challenging context of the Hajj holy sites. By quantitatively balancing environmental, technical, and economic criteria, we can pinpoint zones where solar investments will yield maximum benefit with minimal obstacles. For Saudi authorities and stakeholders, a key implication is that there is no shortage of good sites around Makkah for solar PV: concerns about land availability or resource variability should not hinder solar projects in this area. Instead, planning can focus on how to implement projects in the high-suitability zones – for example, securing the land (which likely belongs to public or religious trusts), and scheduling construction in phases that do not interfere with Hajj operations.
From a planning perspective, the availability of over one-fifth of the study area as highly viable for solar farm development is promising. These zones offer minimal land-use conflict, excellent insolation, and flat topography—ideal conditions for cost-effective implementation. Potential clusters near major transportation corridors and grid access points (e.g., northeast of the Holy Sites) can facilitate smooth integration into local infrastructure, such as Hajj support facilities. This suitability criteria and configuration align with findings from other GIS-AHP solar siting studies in arid environments. For instance, studies in Saudi Arabia found that climatic factors (solar radiation, temperature, .etc) significantly influence solar sites selection^8,9, consistent with our highest criterion weight of 21.5% (Table 6). Nevertheless, notable distinctions were observed. In many urban or agricultural contexts, land use considerations typically carry significant weight. In contrast, our study in Makkah found that land use (environment) was of lesser concern due to the extensive availability of open desert. Unlike analyses that necessitate the exclusion of protected or vegetated areas, our research encountered minimal environmental constraints, which diminished the need to prioritize land use in site selection. One recommendation is to pursue a pilot solar farm in the identified high-suitability zones (northeastern of the study area, which is relatively remote from pilgrim activities). A medium-scale PV plant (e.g., 50–100 MW) could be built there and tied into the local grid that supplies the Hajj facilities. This would immediately cut diesel or oil-fired generation needs during Hajj, reducing emissions and serving as a visible testament to the Green Hajj initiative. Over time, additional farms could be added in other high-suitability pockets, potentially creating a network of solar parks encircling the holy sites. These could be connected via a ring transmission line to provide redundancy and ensure reliable supply even if one site is shaded or down for maintenance.
This study advances the field of renewable energy planning by applying a spatially explicit decision-support framework to a uniquely challenging and policy-relevant context. The contribution is multi-layered. Geographically, it fills a critical gap by providing the first high-resolution suitability analysis dedicated exclusively to the immediate surroundings of Islam’s Holiest Sites, whereas prior work in Saudi Arabia and the Makkah region has operated at provincial or national scales^8,31,34. Methodologically, the AHP weights reflect expert judgment tailored to the Hajj’s specific logistical realities (e.g., prioritizing road access for maintenance during brief non-Hajj periods), offering a nuanced model not replicable by generic suitability studies.
A major methodological strength relevant to the primary goal of reducing logistical burdens associated with distant generation is the explicit integration of both infrastructure and proximity constraints. Rather than consolidating these factors into a single criterion, they are addressed through a combination of high-weight and restrictive criteria. The strong emphasis on Road Network Proximity (17.5%, Rank 2) ensures that selected sites are logistically appropriate for construction and ongoing operations. Additionally, the Land Use and Settlement Proximity criteria collectively establish an effective buffer, limiting development near holy sites and pilgrimage infrastructure to prevent potential conflicts. The consideration of Power Line Proximity further ensures that grid connection costs are incorporated into site evaluations. As a result, optimal locations identified in the northeast (Fig. 6, now relabeled as Fig. 5) are not only technically advantageous in terms of solar yield and terrain suitability but are also situated at practical distances from demand centers—facilitating cost-effective grid connections while preserving the sanctity and operational integrity of the pilgrimage zones. This integrated comprehensive approach directly addresses the challenges of “logistical inefficiencies and environmental burdens” linked to remote oil-fired power plants.
Practically, the 30 m-resolution output (Fig. 6) transitions from theoretical regional potential to identifiable project parcels, directly serving the planning needs of entities managing the Holy Sites. Politically, it operationalizes the “Green Hajj” initiative of Saudi Vision 2030, providing a science-based pathway to reduce the pilgrimage’s carbon footprint. Thus, the novelty lies not in the core GIS-AHP technique, but in its targeted application to generate previously unavailable, actionable intelligence for sustainable development at the intersection of high energy demand, extreme logistical complexity, and profound cultural significance.
An important consideration is whether appropriate land can supply the peak Hajj demand of 500–600 MW. Photovoltaic output potentials for the “Most Suitable” and “High” suitability categories were estimated at 1830 and 1810 kWh/kWp/year, placing them among the top globally (see Fig. 7). Together, these regions span roughly 225 km². The “Most Suitable” and “High Suitability” zones offer excellent PV output potentials—1830 and 1810 kWh/kWp/year, respectively (Fig. 6), ranking among the world’s highest yields. These areas total about 225 km² (110 km² and 115 km²). For utility-scale PV in arid regions, a conservative power density is 30 MW/km².
“Most Suitable” category (110 km², 1830 kWh/kWp/year):
({mathbf{Installed}}{text{ }}{mathbf{capacity}}:{text{11}}0 times {text{3}}0,=,{text{33}}00{text{ MWp}},=,{text{3}}.{text{3}}0{text{ GWp}})
({mathbf{Annual}}{text{ }}{mathbf{energy}}:{text{3}}.{text{3}}0{text{ GWp}} times {text{1}}.{text{83TWh}}/{text{GWp}}/{text{yr}},=,{text{6}}.0{text{4 TWh}}/{text{yr}})
({mathbf{Average}}{text{ }}{mathbf{power}}{text{ }}{mathbf{equivalent}}:{text{6}}.0{text{4}}/{text{876}}0,=,0.{text{69 GWavg }}( approx ,{text{69}}0{text{ MWavg}}))
“High Suitability” category (115 km², 1810 kWh/kWp/year):
({mathbf{Installed}}{text{ }}{mathbf{capacity}}:{text{115}} times {text{3}}0,=,{text{345}}0{text{ MWp}},=,{text{3}}.{text{45GWp}})
({mathbf{Annual}}{text{ }}{mathbf{energy}}:{text{3}}.{text{45 GWp}} times {text{1}}.{text{81 TWh}}/{text{GWp}}/{text{yr}},=,{text{6}}.{text{24TWh}}/{text{yr}})
({mathbf{Average}}{text{ }}{mathbf{power}}{text{ }}{mathbf{equivalent}}:{text{6}}.{text{24}}/{text{876}}0,=,0.{text{71 GW}}_{text{avg}}( approx ,{text{713 MWavg}}))
Combined (both categories).
({mathbf{Total}}{text{ }}{mathbf{capacity}}:{text{6}}.{text{75 GWp}})
({mathbf{Total}}{text{ }}{mathbf{annual}}{text{ }}{mathbf{energy}}:{text{12}}.{text{28 TWh}}/{text{yr}})
({mathbf{Total}}{text{ }}{mathbf{average}}{text{ }}{mathbf{power}}:{text{1}}.{text{4}}0{text{ GWavg}})
Based on the preceding calculations, the total potential installed capacity is approximately 6.75 GW, with an estimated annual electricity generation of roughly 12.3 TWh. This substantial resource suggests that developing only 10% of the identified high-quality land (around 22.5 km²) could yield approximately 675 MW, sufficient to meet the Hajj peak demand. The analysis demonstrates that the AHP-GIS land allocation method offers spatially and environmentally suitable options, while also providing technical adequacy for energy security objectives. Consequently, the “Green Hajj” initiative emerges as an achievable and realistic goal.
Several limitations should be acknowledged in this study. Firstly, the criteria weights, validated by consistency ratio, are derived from expert opinion at a specific point in time; these weights could be subject to change with input from different experts or evolving policy directives, although solar resource dominance is likely to remain. Secondly, this static analysis does not capture seasonal variability; because Hajj occurs during a shifting lunar month, associated conditions may differ should the event take place in winter as opposed to summer. Nevertheless, the use of multi-year climate data is intended to reflect typical environmental conditions. Third, this study utilized high-resolution (30 m) data and applied strict criteria thresholds. Data sources include some uncertainty, such as interpolated climate surfaces from NASA, and effects of local terrain may not be fully captured. Future research could address uncertainty analysis or incorporate Fuzzy AHP for more refined suitability classifications. Although there are certain limitations, the study serves as a proof-of-concept for renewable energy planning at sites including the Holy Sites. It shows how data-driven methods can be integrated with broader initiatives, such as Green Hajj, to offer practical recommendations. By identifying areas most suitable for solar development, the resulting suitability map acts as a decision support tool. Authorities can consult this map together with land ownership details, proximity to substations, and other pertinent factors when evaluating project locations.
The deployment of solar farms near the Holy Sites is projected to reduce carbon emissions and improve air quality for pilgrims, in line with Islam’s principles of environmental stewardship. The GIS-AHP analysis indicates high-potential solar PV zones near Meena, Muzdalifah, and Arafat, supporting Saudi Arabia’s renewable energy objectives and the Green Hajj initiative. This method can be adjusted for solar site selection in other regions by modifying criteria and weights, which may support wider adoption of renewable energy globally.
While this study offers an initial suitability analysis, there are several ways to make it more robust and applicable. Additional criteria such as dust and dew point temperature could be included, as these factors influence particle accumulation on solar panels and affect their productivity. Performing a comprehensive sensitivity or uncertainty analysis—like a Monte Carlo simulation—on the AHP weights would help measure how stable the suitability rankings remain when expert opinions vary. The model’s results could be validated by directly involving stakeholders such as energy planners, local authorities, and community representatives, which would enhance the practical value of the findings. Broadening the scope to consider different technological scenarios, such as bifacial panels or hybrid solar-wind systems, and analyzing their performance under future climate projections may also yield important insights for adaptive long-term planning.
This study presents a GIS-based AHP framework to identify optimal sites for large solar PV projects in the complex environment of the Holy Sites in Makkah. Its main contribution is applying this model to a specific micro-region, bridging Saudi Arabia’s renewable energy goals with the challenges of the “Green Hajj” initiative. By factoring in local constraints and expert input, our suitability map provides planners with actionable guidance, setting it apart from previous regional studies. By integrating climatic, topographic, environmental, and infrastructural variables, a comprehensive suitability map was produced to identify optimal locations for solar development surrounding Meena, Muzdalifah, and Arafat. Results demonstrate that approximately 21.25% of the analysed area is categorised as High or Most Suitable for PV installation, primarily situated in the northeast, where solar irradiance levels reach up to 1830 kWh/kWp/year. These areas are further distinguished by relatively flat terrain, minimal land use conflict, and favourable access to road and grid infrastructure. An additional 23.58% of the territory is classified as Moderately Suitable, indicating that nearly 45% of the region has potential for solar farm deployment with appropriate planning and investment. Conversely, the remaining 55.17% is designated Low or Unsuitable due to challenging topography, elevated terrain, or cultural constraints associated with the Holy Sites. The analysis estimates a total potential capacity of about 6.75 GW and annual generation of 12.3 TWh, from the combined “Most Suitable” and “Highly Suitable” classes. Developing just 10% of this top-quality land (22.5 km²) could provide 675 MW, enough for Hajj peak demand.
The AHP weight analysis indicated that climatic factors are the principal determinants in the process of PV plant siting for the Holy Sites, contributing 39.7% to the overall influence. Within this category, solar radiation (21.5%) and wind speed (6.4%) emerged as the most significant variables. Topographic considerations represented 29.2%, underscoring the importance of slope and aspect. Meanwhile, economic and infrastructural factors—including proximity to roads and power lines—accounted for 24.4%, with land use comprising 6.8%. These results align with findings from comparable studies conducted in arid regions of Saudi Arabia, which similarly highlight the critical roles of solar resources and terrain characteristics in evaluating site suitability. The identified zones with high suitability offer considerable potential for establishing clean energy infrastructure to serve the Hajj and its surrounding facilities. The deployment of solar photovoltaic (PV) systems in these regions can reduce reliance on diesel generators, lower emissions, and improve power reliability during peak pilgrimage periods. This aligns with Saudi Arabia’s Vision 2030 and supports the objectives of the “Green Hajj” initiative. Given the significant anticipated energy output, investments in infrastructure- such as the expansion of transmission lines- are well justified. Notably, regions northeast of the study area and of Meena are optimal choices for utility-scale solar installations, including dual-use applications like photovoltaic parking canopies. Beyond the immediate context of Makkah, this study highlights the value of GIS-AHP methodologies for solar site selection in areas with environmental and cultural sensitivities. The approach is transparent, flexible, and scalable, facilitating informed planning that both honors heritage sites and maximizes renewable energy generation. Further research could expand this framework by integrating variable energy demand profiles, storage solutions, or hybrid microgrid systems.
In summary, the landscapes surrounding Islam’s holiest sites can be utilised for both spiritual events and sustainable energy initiatives. Implementing solar planning may assist Saudi Arabia in lowering the carbon emissions associated with the Hajj, demonstrate advancements in clean energy, and contribute to environmentally conscious development within these areas.
The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.
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Applied Geography and GIS Program, Department of Humanities, College of Arts and Sciences, Qatar University, Doha, Qatar
Sarra Ouerghi
Department of Geography and GIS, Faculty of Arts & Humanities, King Abdulaziz University, Jeddah, Saudi Arabia
Nouf Al Jadaani
Qatar Environment and Energy Research Institute (QEERI) Program, Department of Humanities, College of Arts and Sciences, Qatar University, Doha, Qatar
Yasir Mohieldeen
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S. O. : Conceptualization, Methodology, Formal analysis, Writing – review & editing, Writing – original draft, Visualization, Software, Investigation, Data curation, Supervision, Resources, Project administration,.N. A.: Conceptualization, Writing – review & editing, Formal analysis, Data curation.Y. M.: Writing – review & editing, Validation, Resources, Conceptualization, Methodology, Formal analysis, Software.
Correspondence to Yasir Mohieldeen.
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Ouerghi, S., Al Jadaani, N. & Mohieldeen, Y. ​​GIS-based AHP multi-criteria mapping of potential solar PV power plant development: a case study in the vicinity of Holy Sites, Saudi Arabia. Sci Rep 16, 17022 (2026). https://doi.org/10.1038/s41598-026-46353-9
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Received: 31 October 2025
Accepted: 25 March 2026
Published: 12 April 2026
Version of record: 03 June 2026
DOI: https://doi.org/10.1038/s41598-026-46353-9
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