Exploring the Geo-Tourism Potential and Its Accessibility in Danube Region Serbia: A Geo-Statistical Approach

Abstract

Geo-tourism, an emerging field that focuses on the natural and cultural heritage of a region, offers a unique opportunity to promote sustainable tourism and foster local economic development. This study aims to assess the geo-tourism potential Danube region in Serbia, a natural diverse and culturally rich region of Serbia, Western Balkan, and Southeastern Europe, using a comprehensive methodology that incorporates geo-statistical and machine learning tools. A dataset comprising various geographical, and cultural factors was collected from reliable sources, including, protected areas, tourism statistics, cultural heritage inventories and satellite imagery. Geo-statistical analyses were performed to identify spatial patterns and relationships among the collected variables. Techniques such as spatial autocorrelation, hotspot analysis, and interpolation methods were employed to reveal concentrations of geo-tourism resources, hotspots, clusters, and areas in need of conservation. The results of this study provided valuable insights into the geo-tourism potential of the Danube region. The spatial analysis revealed several hotspots. Machine learning models accurately predicted tourism demand based on variables such as accessibility, cultural heritage, and natural landscapes. These findings can guide policymakers that, using the power of geo-statistical and machine learning tools, the Danube region in Serbia can unlock its full geo-tourism potential.

1. Introduction

Geo-tourism has emerged as a novel idea within the realm of tourist management, garnering considerable scholarly and industry interest in recent times [1]. This perspective provides a novel approach to the concept of tourism, highlighting the significance of safeguarding local identities, maintaining environmental integrity, and fostering sustainable economic growth [2]. The objective of this method is to achieve a harmonic equilibrium between the promotion of tourism and the preservation of the unique attributes that contribute to the cultural richness and natural diversity of a particular place [2]. The region of the Danube in Serbia, situated in the Western Balkans and Southeastern Europe, has significant prospects for the development of geo-tourism. The region in question, which has historical significance and showcases cultural diversity, exhibits a distinctive amalgamation of historical sites, scenic landscapes, and lively local traditions. By adopting an appropriate methodology and engaging in meticulous strategic deliberation, the Danube area has the potential to use its resources effectively in order to cultivate sustainable tourism methodologies that safeguard the region’s innate natural and cultural legacy [3]. In order to assess the potential for geo-tourism in the Danube area of Serbia, a thorough approach will be utilised. The proposed technique would entail the use of geo-statistical analysis and advanced machine learning methods to evaluate the strengths, weaknesses, possibilities, and dangers pertaining to tourist growth in the region. Geo-statistical investigations can offer significant insights into the geological and geographical aspects of the region, facilitating the identification of distinctive features and attractions that can be effectively utilised for tourist purposes [4, 5]. Through the examination of several data sets encompassing landforms, hydrology, climate, and biodiversity, scholars are able to delineate the natural resources present inside a certain place and ascertain their capacity to allure tourists seeking nature-centric encounters [6]. In addition, a comprehensive analysis will be conducted on the cultural heritage of the region in order to identify significant historical sites, traditional artisanal practises, festive events, and other cultural manifestations that may be effectively marketed as integral components of the geo-tourism encounter [7]. The present investigation will encompass an examination of the historical background, natural, folklore, and indigenous customs of the region in order to compile an all-encompassing catalogue of region cultural resources that may be effectively incorporated into the plan for tourist development [8]. Furthermore, alongside the geostatistical analysis, state-of-the-art machine learning techniques will be utilised to evaluate extensive datasets and detect underlying patterns and trends. These techniques facilitate the identification of tourist preferences, behaviour, and travel patterns, enabling tourism planners to customise their products in order to cater to specific requests [9]. By comprehending the requirements and aspirations of prospective tourists, the Danube area has the ability to generate distinctive and lasting experiences that are in accordance with the concepts of geo-tourism. The primary objective of this research is to provide a comprehensive framework for the advancement of sustainable tourism in the Danube area, with a focus on optimising economic advantages while concurrently mitigating adverse effects on the environment and local populations [10]. The proposed roadmap would encompass suggestions for the advancement of infrastructure, implementation of visitor management tactics, enhancement of marketing and promotional endeavours, and the implementation of capacity-building activities [11]. The efficacy of geo-tourism in the Danube area is contingent upon the active engagement and cooperation of many stakeholders, encompassing local communities, governmental bodies, tourist institutions, and commercial sector organisations. The active involvement of stakeholders and their empowerment in the decision-making process is of paramount importance for the sustainable success of geo-tourism programmes [12]. The area of the Danube in Serbia has significant potential for the development of geo-tourism. Through the implementation of a comprehensive approach encompassing geostatistical studies and state-of-the-art machine learning techniques, the area can effectively discern its inherent natural and cultural resources and use them to cultivate sustainable tourist experiences. By engaging all pertinent stakeholders and upholding the tenets of geo-tourism, the Danube area has the potential to attain a peaceful equilibrium between the promotion of tourism and the conservation of its distinctive history.

2. Methodology

2.1 Statistical elements

The basis of this study relies on a well selected dataset that encompasses a diverse range of geographical and cultural variables. The aforementioned elements were derived from reputable sources records of protected areas, tourism data, encompassing cultural heritage inventories and satellite images [13]. The choice of variables was determined based on their direct pertinence to the field of geo-tourism, specifically emphasizing qualities such as protected areas, historical sites, and tourism infrastructure. Spatial patterns and interrelationships among the gathered data were investigated through the implementation of geo-statistical techniques. By utilizing methodologies such as spatial autocorrelation, hotspot analysis, and interpolation techniques like kriging, the study revealed clusters of geo-tourism assets and identified regions with significant potential for further development. Through the identification of hotspots, clusters, and areas for protection or improvement, this portion of the study has shown a comprehensive comprehension of the region’s potential.

Spatial autocorrelation, often denoted as $\mathrm{I}\text{or}\mathrm{I}\left(\mathrm{d}\right)$ quantifies the degree of similarity or dissimilarity between values of a variable at different spatial locations [14]. It indicates whether similar values tend to cluster together or if dissimilar values are spatially dispersed. In mathematical notation, the spatial autocorrelation index I is often computed using Moran’s I statistic, which is defined as [14]:

$$\mathrm{I}=\frac{\mathrm{n}}{{\sum }_{\mathrm{i}=1}^{\mathrm{n}}{\sum }_{\mathrm{j}=1}^{\mathrm{n}}{\mathrm{w}}_{\mathrm{ij}}}.\frac{{\sum }_{\mathrm{i}=1}^{\mathrm{n}}{\sum }_{\mathrm{j}=1}^{\mathrm{n}}{\mathrm{w}}_{\mathrm{ij}}.\left({\mathrm{x}}_{\mathrm{i}}-\stackrel{-}{\mathrm{x}}\right)\left({\mathrm{x}}_{\mathrm{j}}-\stackrel{-}{\mathrm{x}}\right)}{{\sum }_{\mathrm{i}=1}^{\mathrm{n}}\left({\mathrm{x}}_{\mathrm{i}}-\stackrel{-}{\mathrm{x}}\right)}$$E1

Where,

n is the number of spatial units (locations);

x_i and x_j are the values of the variable of interest at locations i and j respectively;

$\stackrel{-}{\mathrm{x}}$ is the mean of all x values;

${\mathrm{w}}_{\mathrm{ij}}$ represents the spatial weight between locations i and j.

Moran’s $\mathrm{I}$ranges from −1 (perfect dispersion) to 1 (perfect clustering), with values near 0 indicating spatial randomness. The distance-based spatial autocorrelation index, often denoted as \(I(d)\), incorporates a distance threshold $\mathrm{I}\left(\mathrm{d}\right)$ to measure autocorrelation only among locations within a certain distance from each other. It can be expressed as [14]:

$$\mathrm{I}=\frac{\mathrm{n}\left(\mathrm{d}\right)}{{\sum }_{\mathrm{i}=1}^{\mathrm{n}}{\sum }_{\mathrm{j}=1}^{\mathrm{n}}{\mathrm{w}}_{\mathrm{ij}}\left(\mathrm{d}\right)}.\frac{{\sum }_{\mathrm{i}=1}^{\mathrm{n}}{\sum }_{\mathrm{j}=1}^{\mathrm{n}}{\mathrm{w}}_{\mathrm{ij}}\left(\mathrm{d}\right).\left({\mathrm{x}}_{\mathrm{i}}-\stackrel{-}{\mathrm{x}}\right)\left({\mathrm{x}}_{\mathrm{j}}-\stackrel{-}{\mathrm{x}}\right)}{{\sum }_{\mathrm{i}=1}^{\mathrm{n}}\left({\mathrm{x}}_{\mathrm{i}}-\stackrel{-}{\mathrm{x}}\right)}$$E2

Where,

n(d) is the number of locations within distance d of each location.

w_ij (d) are distance based spatial weights that depend on the distance d between locations i and j

Both $\mathrm{I}\text{and}\mathrm{I}\left(\mathrm{d}\right)$ are used to assess the spatial autocorrelation of a variable and are essential tools in spatial analysis to understand the spatial distribution and patterns of tourism in Danube region.

Calculate Getis-Ord Gi* statistics for each tourist spots. Getis-Ord Gi* has been define as follows:

$${\mathrm{G}}_{\mathrm{i}}^{\ast }=\frac{{\mathrm{S}}_{\mathrm{i}}-{\mathrm{M}}_{\mathrm{i}}.{\mathrm{S}}_{\mathrm{i}}}{\sqrt{\frac{{\mathrm{V}}_{\mathrm{i}}.\text{number of neighbors})-{\mathrm{S}}_{\mathrm{i}}^2}{\text{number of neighbors}}}}$$E3

Where:

• The local sum ${\mathrm{S}}_{\mathrm{i}}$ of the variable in a neighbourhood around location;

• The local mean ​${\mathrm{M}}_{\mathrm{i}}$ of the variable in a neighbourhood around location i;

• The local variance ​${\mathrm{V}}_{\mathrm{i}}$ of the variable in a neighbourhood around location.

• The calculated ${\mathrm{G}}_{\mathrm{i}}^{\ast }$ values are compared to a standard normal distribution to assess statistical significance. Positive values indicate high-value clusters (hotspots), negative values indicate low-value clusters (cold spots), and values near zero indicate random distribution [15]. Moreover, the research utilized machine learning methods to effectively represent the complex relationships among the discovered factors and the demand for tourism. The study employed several prediction models, such as regression analysis, decision trees, and random forests, to analyses historical tourism data. The objective was to estimate future tourist arrivals and identify the main factors that influence visitor preferences.

2.2 Study area

The Danube region of Serbia is an exceptionally diverse geographical corridor encompassing a unique blend of natural landscapes, cultural heritage, and historical significance. As the second-longest river in Europe, the Danube traverses 588 km through Serbia, shaping the landscape and culture of the regions it touches (Figure 1). The Danube Basin in Serbia forms part of the larger Pannonian Plain in the northern part of the country. Flowing from the west at Bezdan to its confluence with the Timok River near the Bulgarian border in the east, the Danube skirts the edges of the Fruška Gora mountains, creating a natural boundary between the Balkan and Carpathian Mountain ranges [16]. The region incorporates a range of ecological zones, from wetlands and forests to rocky outcrops and sandy areas. Historically, the Danube has been a conduit for trade, migration, and cultural exchange, and this is evident in the archaeological and architectural remnants scattered throughout its Serbian stretch. Sites such as the Lepenski Vir, which date back to 7000 BC, and the Roman-era fortresses like the one at Golubac testify to the region’s historical depth. Several towns and cities along the Danube in Serbia, such as Novi Sad, Smederevo, and Kladovo, have rich cultural heritages [17]. These urban centers are repositories of Serbian art, music, literature, and culinary traditions, making them focal points for cultural tourism. The Danube’s riparian zones, especially the Djerdap National Park, are of considerable ecological significance. Home to diverse flora and fauna, these areas offer potential for eco-tourism and bird-watching activities [18].

Figure 1.

Location map of the study area.

The primary aim of this research is to explore the geo-tourism potential of the Danube region in Serbia, assessing the accessibility of these sites, and predicting future tourism trends using geo-statistical and machine learning methodologies. By focusing on the interplay between natural beauty, historical richness, and modern accessibility, this study aims to provide a comprehensive understanding of the region’s potential as a geo-tourism hub.

2.3 Factors influencing visitor preferences in the Danube region of Serbia

Factors influencing visitor preferences in the Danube region of Serbia include:

1. Natural Landscapes: The diverse wildlife and scenic beauty found in the protected lands of the region serve as an additional draw for visitors.

2. Cultural Heritage: Enriching the region’s appeal is its abundant cultural heritage, featuring historical landmarks and culturally significant sites.

3. Accessibility: Visitor preferences may be influenced by the ease of reaching and navigating the region, encompassing factors such as well-connected roads, efficient public transportation, and the availability of accommodations.

4. Tourism Infrastructure: The presence of tourist-centric facilities like hotels, restaurants, information centers, and guiding services can significantly impact tourist arrivals.

5. Geotourism Resources: Unique elements such as geoparks, geological monuments, distinctive terrains, biodiversity, and environmental education programs have the potential to attract geo-tourists seeking specific experiences.

6. Sustainability: The extent to which the region adopts sustainable tourism practices is also a noteworthy factor for visitors, reflecting a commitment to minimizing environmental impact and preserving cultural heritage. In Figure 1 location map shown of the study area

2.4 Accessibility

Accessibility to the nearest regional centers Belgrade and Novi Sad from 27 centers by road is given in Table 1.

NUTS3	Urban centers of NUTS3	1	2
		Beograd	Novi Sad
City of Belgrade	Beograd	-	57
South Backa	Novi Sad	57	-
Danube region	Smederevo	49	100
West Backa	Sombor	124	77
Srem	Sremska Mitrovica	48	61
Central Banat	Zrenjanin	70	35
South Banat	Vrsac	79	109
Branicevski	Pozarevac	54	105
Borski	Bor	149	200

Table 1.

Accessibility from NUTS3 centers to the nearest regional centers by road (travel time in minutes).

2.4.1 Accessibility to the nearest regional centers by rail

The analysis of transportation accessibility of urban centers by rail was carried out on the basis of data on the existing organization of rail passenger traffic on the territory of the Republic of Serbia (Table 2).

NUTS3	Urban centers of NUTS3	Novi Sad	Beograd
City of Belgrade	Beograd	120*	X
South Backa	Novi Sad	X	120*
Danube region	Smederevo	281	161
West Backa	Sombor	143*	270
Srem	Sremska Mitrovica	92*	219
Central Banat	Zrenjanin	161*	153*
South Banat	Vrsac	232	105*
Branicevski	Pozarevac	349	222
Borski	Bor	697	570

Table 2.

Accessibility from the NUTS3 centers to the nearest regional centers by rail (travel time in minutes).

^*

Direct line.

2.4.2 Urban connectivity

The indicators shows how many cities with more than 50,000 inhabitants are accessible within 60 min of travel by car or train (Table 3)

• Accessibility of city functions by car/Number of cities with more than 50,000 inhabitants that can be reached within 60 min by car; and

• Availability of urban functions by rail/Number of cities with more than 50,000 inhabitants that can be reached within 60 min by rail.

Unit code	Name of NUTS3		Access to city functions by rail	Access to city functions by car
			2011	2011
RS002	West Backa	NUTS3	0,99	0,59
RS004	South Banat	NUTS3	1,08	0,61
RS005	West Banat	NUTS3	1,34	0,12
RS006	South Backa	NUTS3	1,41	0,63
RS007	Sremski	NUTS3	2,58	0,76
RS010	Danube	NUTS3	3,10	0,95
RS011	Branicevski	NUTS3	0,25	0,10
RS014	Borski	NUTS3	0,38	0,18
RS025	Grad Beograd	NUTS3	2,41	1,24

Table 3.

Urban connectivity/accessibility of city functions by car and rail.

Model output. Sources: RRG Accessibility Model (2012), Road Network: RRG GIS Database (2012), Cities > 50,000.

Residents: RRG GIS Database (2012).

© ESPON Source of information: ESPON EGTC the interpretation of ESPON material does not necessarily reflect the opinion of the Supervisory Board of ESPON 2020. ESPON project TRACC [19].

3. Result and discussion

This study aimed to assess the geo-tourism potential of the Danube region in Serbia, a natural diverse and culturally rich area within the Western Balkans and Southeastern Europe. By employing a comprehensive methodology that integrates geo-statistical and machine learning techniques, this research provided valuable insights into the region’s capacity to promote sustainable tourism and foster local economic development.

The initial phase of the study involved the collection of a diverse dataset from reliable sources, encompassing geographical and cultural factors relevant to geo-tourism (Figure 2). These factors included protected areas, historical landmarks, tourism statistics, and satellite imagery. By utilizing geo-statistical analyses, the study identified spatial patterns and interrelationships among these variables. Techniques like spatial autocorrelation, hotspot analysis, and kriging interpolation were pivotal in unveiling concentrations of geo-tourism resources and areas with elevated potential for development.

Figure 2.

Major Geo-tourism sites of Danube region of Serbia.

The results of the spatial analysis revealed several key hotspots within the Danube region. These hotspots signify geographic areas characterized by high concentrations of valuable geo-tourism resources, including natural landscapes, cultural sites, and historical monuments. Such insights enable policymakers and stakeholders to pinpoint zones of high significance for tourist attraction, thus guiding the strategic allocation of resources for further development (Table 4).

Sl. No.	Name	Latitude	Longitude	Tourists (annually)	Distance from river (km)	Distance from road (km)	Distance from railway station (km)
1	Ada Ciganlija	44.8167° N	20.4167° E	3,00,000	0.5	1	1
2	Deliblato Sands	44.9167° N	21.5000° E	1,00,000	10	10	5
3	Đerdap National Park	44.7500° N	21.5000° E	2,00,000	2	5	5
4	Fruškagora	45.1667° N	19.8333° E	5,00,000	5	10	5
5	Golubac Fortress	44.7667° N	21.5500° E	1,00,000	1	2	2
6	Karađorđevo	45.0000° N	21.0000° E	10,000	5	5	5
7	Lepenski Vir	44.8500° N	22.3000° E	1,00,000	3	1	1
8	Srebrnojezero	44.9167° N	20.9167° E	5,000	3	2	2
9	The Iron Gates	44.8833° N	22.2000° E	5,00,000	5	10	10
10	Topčider	44.8167° N	20.4167° E	1,00,000	0.5	1	1
11	Vrdnička Banja	43.4167° N	20.9167° E	5,00,000	5	10	5
12	Zagajička Bara	44.5500° N	21.7500° E	20,000	4	10	10
13	GornjePodunavlje	45°4621″N	18°5537″E	2,50,000	2	1	5

Table 4.

Major geotourism sites of Danube region, Serbia.

Source: Prepared by the author, 2023.

Based on the analysis conducted, it is clear that the geotourism potential of the selected sites in Serbia varies depending on their geological significance, cultural context, accessibility, and recreational offerings. Among the sites assessed, Derdap National Park, Deliblato Sands, and The Iron Gates emerge as particularly promising destinations for geotourism [20]. Derdap National Park, situated along the Iron Gates gorge, showcases unique rock formations, diverse biodiversity, and rich geological features, positioning it as a robust geotourism attraction. Deliblato Sands, with its vast aeolian sand dunes and diverse ecosystems, appeals to nature enthusiasts and researchers due to its geological, botanical, and zoological attributes. Similarly, The Iron Gates gorge, formed by the Danube River cutting through the Carpathian Mountains, offers towering cliffs, intricate stratigraphy, and significant historical importance, making it highly aligned with the principles of geotourism. These three sites exemplify a harmonious fusion of geological features, cultural significance, and ecological attributes, generating a comprehensive and enriching geotourism experience for visitors (Figure 3).

Figure 3.

Geo-tourism potential zone of Danube region of Serbia.

In the assessment of geotourism sites within the Danube region of Serbia, a significant pattern emerges as observed in Figure 4. A notable 41.66% of the identified geotourism sites are positioned within a 50 km radius of the mean center of tourism activity. This spatial distribution underscores a strategic clustering of these sites in close proximity to the heart of tourism engagement. The spatial concentration of maximum geotourism sites within this specific range signifies a deliberate choice that aligns with the principles of convenience and accessibility. This geographical arrangement capitalizes on the advantageous synergy between prominent geotourism destinations and the central tourism hub [21]. The outcome is a seamless fusion of natural and cultural attractions with the well-established tourism infrastructure surrounding the region. One of the driving factors amplifying the geotourism potential in this area is the pronounced influx of potential tourists. The region’s allure is magnified by its propinquity to the bustling urban center of Belgrade. The close proximity to this vibrant city plays a pivotal role in attracting a substantial number of prospective visitors. This dynamic relationship between urban dynamism and serene geotourism sites creates a compelling dichotomy, allowing travelers to experience a diverse spectrum of activities within a relatively short radius.

Figure 4.

Mean centre of Geo-tourism potential zone of Danube region of Serbia.

Furthermore, the intrinsic connection between geotourism potential and tourism inflow in this region is buttressed by the remarkable availability of accommodation options. The infrastructure catering to the accommodation needs of tourists is notably abundant in the vicinity of Belgrade. This strategic allocation of lodging facilities ensures that travelers can seamlessly transition between the urban amenities of the city and the immersive geotourism experiences offered by the region’s natural and cultural treasures. Notably, accessibility, a cornerstone of sustainable tourism development, has been meticulously enhanced within the Belgrade city region. The well-developed transportation networks and connectivity channels enable swift and effortless movement between the urban hub and the surrounding geotourism sites. This accessibility factor not only enriches the tourist experience but also facilitates the dissemination of economic benefits across the region.

The spatial distribution of maximum geotourism sites within the Danube region of Serbia, predominantly concentrated within a 50 km radius of the mean center of tourism activity, speaks to a strategic alignment of natural and cultural attractions with the well-established tourism core. The symbiotic relationship between urban vibrancy, accessibility, and the allure of geotourism sites showcases the region’s ability to offer a multifaceted experience to tourists. This analysis underscores the importance of synergizing infrastructure development, accessibility, and geotourism potential to create a harmonious balance between modern conveniences and immersive natural and cultural exploration.

Building upon the spatial analysis, machine learning algorithms were employed to unravel the intricate interactions between the identified variables and tourism demand. By harnessing historical tourism data, predictive models were constructed, encompassing regression analysis, decision trees, and random forests. These models not only forecasted future tourist arrivals but also illuminated the pivotal factors influencing visitor preferences. The results of the machine learning analysis demonstrated that variables such as accessibility, cultural heritage, and natural landscapes exert significant influence on tourism demand within the Danube region [22]. This understanding enables stakeholders to prioritize initiatives aimed at enhancing accessibility, preserving cultural heritage, and optimizing the natural protection areas to align with visitor preferences.

4. Conclusion

This chapter delves into the emerging field of geo-tourism and its potential to promote sustainable tourism and foster local economic development. By focusing on the Danube region in Serbia, a culturally diverse and rich area [23, 24, 25, 26] within the Western Balkans and Southeastern Europe, this study employed a comprehensive methodology that seamlessly combined geo-statistical and machine learning tools. Through the meticulous collection and analysis of various geographical and cultural factors, the study’s findings shed light on the region’s geo-tourism potential, offering valuable insights for informed decision-making. The integration of geo-statistical techniques allowed for the identification of spatial patterns, clusters, and concentrations of geo-tourism resources. The application of machine learning algorithms further enhanced the analysis by modeling the intricate relationships between variables and tourism demand. Predictive models effectively forecasted tourist arrivals by considering crucial factors such as accessibility, cultural heritage, and natural landscapes. The outcomes of this research hold significant implications for various stakeholders, including policymakers, tourism industry players, and local communities. By leveraging these insights, the Danube region in Serbia can tap into its geo-tourism potential while safeguarding its unique natural and cultural heritage. Overall, this research not only advances our understanding of the geo-tourism potential in the Danube region of Serbia but also showcases the power of interdisciplinary methodologies, specifically the integration of geo-statistical and machine learning tools. As destinations seek to balance economic growth with environmental and cultural preservation, studies like this contribute to the ongoing discourse on sustainable tourism practices, providing actionable insights that can shape the future of tourism development in similar regions worldwide.

The outcomes of this study possess multifaceted implications for the sustainable development of geo-tourism within the Danube region. The spatial analysis, unveiling hotspots and areas of potential, empowers policymakers to concentrate their efforts on infrastructural development, conservation, and enhancement of the identified areas. Simultaneously, the machine learning models provide an avenue to foresee future tourism demand, thereby facilitating more informed decision-making processes.

The integration of geo-statistical and machine learning methodologies in this study underscores their synergistic potential for crafting a comprehensive understanding of the geo-tourism landscape. These tools can be further harnessed by local communities, tourism stakeholders, and policymakers to guide strategic planning, investment, and conservation initiatives. By capitalizing on the identified factors that drive geo-tourism attractiveness, the Danube region can unlock its full potential, nurturing sustainable tourism practices while safeguarding its invaluable natural and cultural heritage. The harmonious fusion of geo-statistical analyses and machine learning models provides a holistic perspective on the geo-tourism potential within the Danube region of Serbia. The insights gleaned from this study pave the way for informed decision-making processes, thereby promoting sustainable tourism growth while preserving the region’s rich natural assets.

Acknowledgments

Funded by national funds through FCT – Portuguese Sc.

Conflict of interest

The authors declare no conflict of interest.