Spatial Layout Optimization of Rural Tourism Destinations in Mountainous Areas Based on Gap Analysis Method: A Case Study in Southwest China

Abstract

Rural tourism plays a crucial role in promoting industrial revitalization in mountainous regions. Drawing inspiration from the site selection mechanisms of nature reserves, this study constructs a gap analysis framework tailored to rural tourism destinations, aiming to provide technical support for their spatial layout and systematic planning. By integrating a potential evaluation system based on tourism resources, market demand, and synergistic factors, the study identifies rural tourism priority zones and proposes a development typology and spatial optimization strategy across five provinces in Southwest China. The findings reveal: (1) First- and second-priority zones are primarily located in the core and periphery of provincial capitals and prefecture-level cities, while third-priority zones are concentrated in resource-rich areas of Yunnan and Guizhou and market-oriented areas of Sichuan, Chongqing, and Guangxi. (2) The Chengdu Plain emerges as the core region for rural tourism development, with hotspots clustered around Chengdu, northern and western Guizhou, central Chongqing, eastern Guangxi, and northwestern Yunnan, whereas cold spots are mainly situated in the western Sichuan Plateau and the Leshan–Liangshan–Zhaotong–Panzhihua–Chuxiong–Pu’er belt. (3) The alignment between tourism resources and rural tourism destinations is highest in Yunnan and Guizhou, while Chongqing exhibits the strongest match between destinations and tourism market potential and synergistic development conditions. Overall, 79.35% of rural tourism destinations in the region are situated within identified priority zones, with Chongqing, Guizhou, and Sichuan exhibiting the highest proportions. Based on the spatial mismatch between potential and existing destinations, the study delineates four development types—maintenance and enhancement, supplementation and upgrading, expansion, and reserve development—and offers regionally tailored planning recommendations. The proposed framework provides a replicable approach for spatial planning of rural tourism destinations in complex mountainous settings.

1. Introduction

Rural tourism is widely regarded as an effective development strategy for revitalizing rural areas in both developed and developing countries [1,2,3]. In the context of rapid urbanization, rural areas—with their picturesque landscapes, pristine ecological environments, and rich agricultural and cultural heritage—have increasingly become attractive destinations for urban residents seeking short-term travel, leisure, and physical and mental relaxation [4,5,6]. Consequently, rural tourism has drawn growing interest from a wide range of disciplines, including economics, management, tourism studies, sociology, and geography [5,7,8]. Across different global contexts, rural tourism has become an important driver of economic growth and has contributed significantly to improving residents’ well-being [1,5,9]. In China, a country with a long agricultural tradition and vast rural territories, the transformation of rural areas has emerged as a critical policy concern. Amid ongoing economic restructuring, enhancing rural economic performance and improving rural living conditions have become pressing challenges [3,10]. In response, the Chinese central government introduced the Rural Revitalization Strategy in 2018, aiming to develop the countryside into a comprehensive regional system that integrates ecological, social, and economic functions [11].

Compared to developed countries, rural tourism in China began relatively late. Due to different stages of development, the research focus in this field also varies across regions. In developed countries, rural tourism studies have evolved to examine complex issues such as community politics, power dynamics, and resource governance [1,12]. More recently, emerging challenges including climate change and pandemics have become important areas of scholarly attention. In contrast, rural tourism research in China remains largely policy-driven and often emphasizes qualitative analysis and case-based approaches [13,14]. One foundational component of rural tourism development is the scientific evaluation of tourism resources, which is essential for informed spatial planning and sustainable destination management [15,16]. Specifically, identifying the spatial distribution and development potential of tourism resources enables more coordinated and efficient regional planning, helping to avoid fragmented, redundant, or underutilized rural tourism layouts. In mountainous regions, rural tourism often suffers from scattered development, resource–market mismatches, and limited spatial coordination, which hinder its capacity to drive rural revitalization and achieve sustainable land use. The complexity of the terrain and uneven infrastructure further amplifies spatial inefficiencies. Therefore, optimizing the spatial layout of rural tourism destinations is not only a practical necessity but also a strategic approach to improve development efficiency, guide investment, and avoid homogenized or redundant construction.

Rural tourism resources encompass a wide range of elements, including natural, cultural, agricultural, social, and economic assets. Early evaluations of such resources were predominantly qualitative, focusing on descriptive characteristics, esthetic appeal, and tourism potential. With the advancement of rural tourism research, scholars have gradually adopted more quantitative approaches, such as the Analytic Hierarchy Process (AHP), the Delphi method, and expert scoring systems, to construct comprehensive evaluation index systems tailored to specific regional conditions [8,15,16]. For example, Xiang (2020) developed a three-level evaluation framework—comprising target, factor, and indicator levels—using AHP and Delphi techniques to rank the importance of rural ecotourism resources [8].

In parallel with technological progress, particularly in remote sensing (RS) and geographic information systems (GIS), spatial analytical methods have become increasingly prominent in tourism research. These methods have been applied to analyze the spatial distribution, accessibility, and land suitability of tourism resources. For instance, Kaptan Ayhan et al. (2020) conducted a GIS-based land use suitability analysis for rural tourism in the Yenice district of Turkey, dividing the region into landscape units using RS and GIS techniques [17]. Similarly, POI (point of interest) data have been widely employed in recent studies: Yang et al. (2022) classified POIs in Xi’an into agricultural, ecological, and creative landscapes and used kernel density estimation and Thiessen polygon analysis to explore spatial patterns of rural cultural landscapes [18]. Liang (2023) examined the spatial structure and driving factors of tourist attractions in Chengdu using POI data and spatial tools such as kernel density, geographic concentration index, and standard deviation ellipse [19]. At a broader scale, Zhang et al. (2023) and Xie et al. (2022) conducted nationaL–Level spatial analyses of rural tourism towns and villages across China, identifying their spatial structures, influencing factors, and regional development implications [20,21].

Despite these methodological advancements, several limitations persist in the current literature. First, most studies adopt administrative boundaries (e.g., county or provincial units) as the basic unit of analysis, often overlooking the need for cross-boundary or regional-scale planning. Second, existing evaluations largely focus on already developed or designated tourism destinations, while insufficient attention is paid to regions with latent development potential—particularly in ecologically sensitive and spatially fragmented mountainous areas. Third, although various spatial analysis techniques have been applied to map resource distributions and accessibility, few studies systematically integrate market demand, infrastructure, and tourism synergies into their spatial evaluation frameworks.

In response to these gaps, this study introduces a gap analysis approach, originally developed for ecological conservation, to the field of rural tourism spatial planning. Gap analysis enables the identification of mismatches between areas with high tourism development potential and the current distribution of rural tourism destinations. This method provides a strategic planning tool for identifying underdeveloped but high-potential regions, especially in complex mountainous terrains such as Southwest China. By constructing a multi-dimensional evaluation framework—including tourism resources, market accessibility, and synergistic conditions—this study evaluates the spatial potential of rural tourism, identifies priority development zones, compares them with existing development patterns, and proposes layout optimization strategies. This approach offers a more systematic, scalable, and policy-relevant solution for rural tourism planning.

2. Materials and Methods

2.1. Theoretical Framework

This study draws upon the concept of gap analysis, a method originally developed in landscape ecology and biodiversity conservation. A gap analysis compares conservation priorities with existing protected areas to identify spatial gaps and inform targeted conservation interventions [22,23]. In early applications, it guided the establishment of national parks by delineating natural regions (as “surfaces”) and selecting representative protected areas (as “points”). Over time, gap analysis evolved into a broader spatial decision-support tool, involving steps such as defining conservation objectives, analyzing existing units, identifying unprotected zones, and implementing adaptive management [24].

Inspired by this methodological logic, this study extends the gap analysis approach to the field of rural tourism geography, constructing a spatial framework for identifying potential development zones and optimizing the spatial layout of rural tourism destinations.

2.2. Gap Analysis

The gap analysis framework for rural tourism (Figure 1) consists of three main stages:

(1) 

Rural tourism potential evaluation and identification of priority zones.

We constructed a rural tourism potential evaluation system based on factors commonly cited in the literature, such as natural resources, economic conditions, market accessibility, and tourism infrastructure [25,26,27]. Considering the specific characteristics of mountainous areas and data availability, we selected 20 indicators across three dimensions: tourism resources, tourism market, and tourism synergy (

Table 1. Evaluation index system of rural tourism potential.

Target Layer	Normative Layer	Factor Layer	Description of Indicators	Weights
Rural tourism potential	Tourism resource	Altitude difference	The greater the difference in altitude, the richer the vertical changes in the natural landscape, which is conducive to rural tourism.	0.04
		Forest coverage	The higher the forest cover, the better the ecological environment of the countryside, which is conducive to rural tourism.	0.03
		Arable land	The larger the area of arable land, the easier it is to create an idyllic landscape for rural tourism	0.05
		River density	The higher the river density, the better the rural waterscape environment and the greater the tourism potential	0.06
		Average annual temperature	Determine that 15 to 17 °C is optimal, with scores decreasing on both sides of the scale	0.02
		National Key Cultural Relics Protection Unit	The more national key cultural relics protection units there are, the richer the cultural tourism resources are	0.05
		National Intangible Cultural Heritage	The more national intangible cultural heritage there is, the richer the cultural tourism resources are	0.03
		Famous Historical and Cultural Village in China	Chinese historical and cultural villages are more likely to be developed as rural tourism destinations	0.06
		Chinese traditional village	China’s traditional villages are easier to develop as rural tourism destinations	0.02
		Villages with Chinese ethnic minority characteristics	China’s Minority Characteristic Villages Easier to Develop as Rural Tourism Destinations	0.04
	Tourism market	Population size	The larger the population, the larger the potential rural tourism market	0.04
		Urbanization rate	The higher the urbanization rate, the greater the potential rural tourism market	0.07
		GDP per capita	The higher the GDP per capita, the greater the demand for rural tourism consumption	0.07
		Per capita disposable income of urban residents	The higher the per capita disposable income of urban residents, the higher the consumption capacity of rural tourism	0.06
		Total retail sales of consumer goods per capita	The higher the total retail sales of consumer goods per capita, the higher the consumption capacity of rural tourism	0.05
		Transportation accessibility	Comprehensive accessibility calculations for motorways, national roads, provincial roads and county roads, the better the accessibility, the better it is for rural tourism trips	0.06
	Tourism synergy	Gross tourism receipts	The higher the gross tourism income, the better the basis for rural tourism development	0.07
		Total tourism number	The higher the total number of tourist arrivals, the better the basis for rural tourism development	0.07
		Number of tourist attraction of 3A and above	The greater the number of tourist attractions, the easier it is to attract tourists and divert them to the countryside	0.06
		Number of natural parks (National forest parks, National geological parks, National wetland parks, National water conservancy scenic areas)	Nature parks are the least intensively protected of the system of nature reserves and the most likely to have tourism activities. The greater the number of nature parks, the easier it is to attract tourists and divert them to the countryside	0.05

Note: Provincial leisure agriculture and rural tourism demonstration destinations are only announced by Guangxi, and provincial rural tourism key villages and towns and leisure agriculture and rural tourism demonstration destinations are regarded as equivalent; since Chengdu City is included in the national leisure agriculture and rural tourism demonstration counties, the 15 counties under the jurisdiction of Chengdu City that are involved in the countryside are all counted as demonstration counties.

). ① Tourism resources refer to the natural and cultural assets that provide the foundation for tourism attraction [21,28]. Key indicators include forest cover, river systems, elevation, intangible cultural heritage, and traditional villages. ② Tourism market reflects the demand-side potential and includes indicators such as population size, economic level, income and consumption, urbanization rate, and transportation accessibility. ③ Tourism synergy refers to the external conditions that support the development and sustainability of rural tourism destinations. It captures regional tourism development capacity and the spillover effects from existing infrastructure and activity. This includes prefecturaL–Level tourism income and visitor arrivals, the number of national 3A-level and above scenic spots, and the presence of ecological and recreational zones such as forest parks, geological parks, and wetland areas.

Given the heterogeneity of indicator effects, principal component analysis and the entropy weight method were employed to assign weights. Based on this, we used ArcGIS 10.2 to perform spatial evaluation at the county level, identifying priority development zones for rural tourism.

(2) 

Analysis of the spatial distribution of existing rural tourism destinations.

As can be seen in

Table 2. Composition of sample points of rural tourism destinations in the Southwest China.

Provinces	Key Villages and Towns for Rural Tourism (Number)				Leisure Agriculture and Rural Tourism Demonstration Counties/Points (No.)
	National Level		Provincial Level		National Level		Provincial Level
	Subdue	Village	Subdue	Village	Counties	Point	Point
Yunnan	6	53	101	213	11	17	-
Guizhou	7	52	49	376	10	16	-
Sichuan	6	49	10	307	29	20	-
Chongqing	6	41	8	141	11	19	-
Guangxi	6	46	12	78	13	19	299
Total	31	241	180	1115	79	91	299

Note: Provincial leisure agriculture and rural tourism demonstration destinations are only announced by Guangxi, and provincial rural tourism key villages and towns and leisure agriculture and rural tourism demonstration destinations are regarded as equivalent; since Chengdu City is included in the national leisure agriculture and rural tourism demonstration counties, the 15 counties under the jurisdiction of Chengdu City that are involved in the countryside are all counted as demonstration counties.

, the rural tourism destination cases used in this study were selected based on data published by official government sources, including the Ministry of Culture and Tourism, the Ministry of Agriculture and Rural Affairs, and provinciaL–Level cultural and tourism departments. We collected data on officially recognized rural tourism destinations from national and provincial sources (e.g., leisure agriculture demonstration counties, tourism characteristic towns and villages). Destination levels were categorized by spatial scale—county (weight = 10), town (2), and village (1). Coordinates were obtained via Baidu Maps and processed using ArcGIS for spatial projection and database construction. Spatial analysis methods were applied to examine clustering characteristics and spatial associations.

(3) 

Identification of development gaps and optimization strategies.

We overlaid the tourism potential results with the current distribution of rural tourism destinations to identify “gap areas”—counties with high tourism potential but insufficient destination development. These are considered priority areas for future tourism investment. This process allows for the formulation of typology-based spatial strategies (e.g., expansion, upgrading, consolidation), supporting the orderly and coordinated growth of rural tourism. This paper presents the first-round gap identification, while future iterations may include annual updates and dynamic feedback mechanisms.

2.3. Spatial Analysis

To further explore the spatial distribution characteristics of rural tourism destinations in Southwest China, the following spatial analysis methods were applied:

The Geographic Concentration Index reflects the degree of spatial concentration of point elements and is used to analyze the concentration patterns of rural tourism destinations in Southwest China. The formula is as follows [29]:

$$G=100\times \sqrt{\sum _{i=1}^n{\left({\displaystyle \frac{X_i}{T}}\right)}^2}$$

(1)

where G is the geographic concentration index, denotes the number of rural tourism destinations in the first province; $n$ is the number of provinces; $T$ is the total number of rural tourism destinations in Southwest China. The value of the G is [0, 100], and the larger the G value, the more concentrated the distribution of rural tourism destinations; the smaller the G value, the more dispersed the distribution tends to be.

Kernel Density Analysis is used to examine the spatial clustering of rural tourism destinations. The method calculates density by taking each grid point as the center, identifying point elements within a specified radius, and computing the number of elements to determine the density at each grid point. A higher kernel density value indicates a greater concentration of rural tourism destinations. The formula is as follows:

$$R_n\left(x\right)={\displaystyle \frac{1}{nh}}\sum _{i=1}^n\left({\displaystyle \frac{x-x_i}{h}}\right)$$

(2)

where R_n $\left(x\right)$ is the estimate of the kernel density of R at certain point x; n is the number of rural tourism destinations; $h$ is the bandwidth; $k$ is the kernel function; $\left(x-x_i\right)$ is the distance from the estimated point to the $x_i$ of the measurement point [30].

Spatial Autocorrelation Analysis is used to assess the distribution patterns, clustering characteristics, and spatial associations of point or polygon elements [31,32]. It includes both global and local spatial autocorrelation. In this study, local spatial autocorrelation is employed to analyses the degree of clustering and spatial differentiation of rural tourism destinations at the county level, identifying patterns of local spatial association and highlighting significant hot and cold spots.

2.4. Data Sources and Processing

The data used in this study cover rural tourism destinations, administrative divisions, natural and cultural resources, tourism markets, and synergistic development elements. Rural tourism destination samples were collected from the official websites of national and provincial departments of culture and tourism, as well as agriculture and rural affairs, with spatial coordinates extracted via Baidu Maps. The administrative boundary base map was obtained from the Standard Map Service Platform of the National Administration of Surveying, Mapping and Geoinformation. Natural resource data include forest cover from Global Forest Watch (https://www.globalforestwatch.org/), cropland area from GlobeLand30, average annual temperature and river data from the Resource and Environmental Science and Data Center of the Chinese Academy of Sciences, and 30 m resolution DEM data (2020) from NASA’s SRTM1 v3.0. Cultural resource data were drawn from several national platforms: key cultural heritage sites were sourced from the State Administration of Cultural Heritage, intangible cultural heritage data from the China Intangible Cultural Heritage Network, and information on historical and traditional villages from the Ministry of Housing and Urban-Rural Development. Additionally, data on ethnic minority villages were obtained from the official website of the State Ethnic Affairs Commission. Regarding tourism market indicators, county-level population and urbanization rate data were extracted from the 2021 Statistical Yearbooks of the five southwestern provinces and municipalities, along with the China County Statistical Yearbook, while the 2020 road network data were retrieved from OpenStreetMap (OSM). As for tourism synergy elements, information on 3A-level and above tourist attractions, national forest parks, geoparks, wetland parks, and water conservancy scenic areas was collected from the official websites of the Ministry of Culture and Tourism, the Ministry of Natural Resources, and the Ministry of Water Resources. Tourism revenue and tourist arrival figures at the prefecture level were obtained from the 2021 Statistical Yearbooks of the five southwestern provinces and municipalities. Since county-level tourism statistics were not directly available, they were estimated using a conversion method based on prefecture-level totals, as detailed in Formula (3).

$${CT}_i={DT}_j\times {\displaystyle \frac{C_i}{D_j}}$$

(3)

where CT_i is the total tourism revenue or attendance of the county, and ${DT}_j$ is the total tourism revenue or total number of people in prefecture-level city $j$, and $C_i$ is the tertiary industry output value of county i in city j, D_j is the output value of the tertiary industry in city j.

3. Results

3.1. Rural Tourism Potential and Priority Zones

Using the natural break classification method, rural tourism potential across counties in Southwest China was evaluated based on three dimensions: tourism resources, market conditions, and development synergy. The results show clear spatial differentiation. Overall, 63.83% of counties demonstrate medium or higher tourism resource levels, with Yunnan (77.52%) and Guizhou (77.27%) leading, while Guangxi ranks lowest (39.64%). For market potential, 64.66% of counties are categorized as medium or above, with strong clusters around urban agglomerations such as Chengdu–Chongqing, central Yunnan, and the Beibu Gulf. Chongqing leads with 86.84% of counties at medium or higher levels, followed by Sichuan, Yunnan, and Guangxi, while Guizhou ranks lowest (51.14%). Development synergy remains relatively weak, with only 48.87% of counties achieving a medium or higher level of development synergy. Chongqing again ranks highest (76.32%), while Yunnan (27.13%) and Sichuan (32.24%) show lower synergy levels (Figure 2a–c).

When overlaying these dimensions, the comprehensive evaluation indicates that 69.10% of counties in Southwest China exhibit medium or higher rural tourism potential. Among the five provinces, Chongqing demonstrates the highest potential, with 94.74% of its counties at medium or above, followed by Guizhou (75.00%), Sichuan (60.11%), Yunnan (58.91%), and Guangxi (56.76%). Spatially, counties with higher potential are mainly concentrated outside the mountainous regions of the Western Sichuan Plateau and Northwestern Guangxi, particularly around major urban agglomerations (Figure 2d).

Based on the evaluation results, counties were further classified into three priority zones for rural tourism development: Priority Level 1 (high potential), Level 2 (medium-high potential), and Level 3 (medium potential). Priority Level 1 and 2 zones account for 17.35% and 24.63% of all counties, concentrated in provincial capitals, prefecture-level city centers, and surrounding areas. Chongqing has the largest shares in Priority Levels 1 and 2 (42.11% and 34.21%, respectively). Priority Level 3 zones make up 27.12% of counties, with Yunnan having the highest proportion (34.11%). Notably, Priority Level 3 zones in Yunnan and Guizhou tend to align with areas rich in tourism resources, while in Sichuan, Chongqing, and parts of Guizhou, they are more closely associated with strong market potential. These spatial differences reflect varying regional advantages: natural and cultural richness in Yunnan and Guizhou, and economic and urban development in Sichuan and Chongqing (Figure 3,

Table 3. Proportion of counties in rural tourism priority areas in Southwest China (%).

Area	Percentage of Non-Priority Areas	Percentage of Priority 3 Areas	Percentage of Priority 2 Areas	Percentage of Priority 1 Areas	Total Proportion of Priority Zones
southwestern	30.90	27.12	24.63	17.35	69.10
Yunnan	41.09	34.11	15.50	9.30	58.91
Guizhou	25.00	30.68	27.27	17.05	75.00
Sichuan	39.89	28.96	21.86	9.29	60.11
Chongqing	5.26	18.42	34.21	42.11	94.74
Guangxi	43.24	23.42	24.32	9.01	56.76

).

3.2. Spatial Distribution Characteristics of Rural Tourism Destinations

The Geographic Concentration Index (G) of rural tourism destinations in Southwest China was calculated as G = 46.01, significantly higher than the theoretical value of G₀ = 20.00 for even distribution, indicating a relatively high degree of spatial concentration at the provincial scale. Kernel density analysis reveals a clear “one core and multiple centers” spatial structure. The Chengdu Plain forms the primary core, with Chengdu radiating influence toward cities such as Deyang and Ya’an. Secondary centers are distributed along the Guiyang–Anshun–Bijie–Qiandongnan belt in Guizhou, around Chongqing’s urban core, and in Lijiang, Dali (Yunnan), and Guilin, Yulin, and Guigang (Guangxi). The clusters in Guizhou and Chongqing are larger in scale compared to Yunnan and Guangxi, reflecting stronger economic and infrastructural advantages (Figure 4a). High kernel density zones are typically found in areas with abundant tourism resources or robust market demand, such as northwest and central Yunnan, eastern Sichuan Basin, central Chongqing, eastern and southern Guangxi, and across all nine prefectures of Guizhou. In contrast, regions with harsh natural conditions or weak markets—such as the western Sichuan Plateau, Nujiang, Lincang, Pu’er, and Hechi—show significantly lower density.

An analysis of the number of rural tourism destinations per county, categorized into five levels, reveals an overall pyramid-shaped structure at the regional scale: only 20.94% of counties fall into the medium or higher categories, while the majority remain in low or lower levels, especially in Sichuan, Guizhou, and Guangxi. At the provincial level, Sichuan, Yunnan, and Guangxi exhibit typical pyramid distributions, whereas Guizhou and Chongqing display spindle-shaped structures, with relatively more counties in the medium range. In Yunnan, only 13.18% of counties are rated medium or above, the lowest among the provinces; in Guangxi and Sichuan, the proportions are 19.82% and 20.77%, respectively. Chongqing leads with 36.84%, followed by Guizhou at 27.27%. High-grade counties are mainly found near provincial capitals (

Table 4. Hierarchical structure of rural tourism destination quantitative in counties in Southwest China.

Number of Rural Tourism Destinations in the County (Number)	Number of Rural Tourist Destinations in the County Ranked	Percentage of Number of Districts of Different Classes in the South-West and Provinces (%)
		Southwest China	Yunnan	Guizhou	Sichuan	Chongqing	Guangxi
0–3	lower	49.00	54.26	25.00	65.03	13.16	47.75
4–8	relatively low	30.05	32.56	47.73	14.21	50.00	32.43
9–16	medium	15.66	7.75	20.45	18.58	26.32	12.61
17–26	high	4.37	4.65	3.41	2.19	7.89	7.21
27–40	your (honorific)	0.91	0.78	3.41	0.00	2.63	0.00

, Figure 4b).

Spatial autocorrelation analysis further highlights the clustering patterns of rural tourism destinations. High-High (H-H) clusters are concentrated in central urban areas of Chengdu, Chongqing, and Guiyang, as well as in southeastern and southwestern Guizhou, northwestern and eastern Yunnan, and near Guilin and Yulin in Guangxi. These areas exhibit high internal density and strong spatial connectivity, driven by favorable resource and market conditions. Conversely, Low–Low (L–L) clusters are located in the western Sichuan Plateau, Leshan, and Chuxiong, where remoteness and weaker markets constrain tourism growth. High–Low (H–L) and Low–High (L–H) outliers are scattered and limited in number across the region (Figure 5a).

Hot and cold spot analysis reveals a distinct “hot east, cold west” pattern. Statistically significant hotspots are concentrated in central, northern, and western Guizhou, Chengdu and surrounding areas, southeastern Aba Prefecture, and Qijiang (Chongqing). Additional hotspots are observed in southeastern Guizhou, northwestern Yunnan, and parts of Guangxi. Cold spots are primarily found in the western Sichuan Plateau and along the Leshan–Liangshan–Zhaotong–Panzhihua–Chuxiong–Pu’er corridor, with smaller cold spot clusters along the Yunnan–Vietnam border (Figure 5b).

3.3. Optimization of the Spatial Layout of Rural Tourist Destinations

The core of the gap analysis lies in assessing the alignment between the spatial distribution of existing rural tourism destinations and the identified priority development zones. By evaluating their match with tourism resource endowments, market potential, and synergistic development conditions, this analysis identifies spatial imbalances and insufficiencies, providing a basis for optimizing the layout of rural tourism destinations in Southwest China.

3.3.1. Alignment Between Rural Tourism Destinations and Development Conditions

The overall alignment between rural tourism destinations and resource endowments in Southwest China is relatively strong, with 70.77% of destinations located in resource-advantaged zones. Yunnan and Guizhou exhibit the highest alignment (86.61% and 83.00%, respectively), with destinations concentrated in resource-rich areas of western, northwestern, southern, and southeastern Yunnan. In contrast, Guangxi shows the lowest alignment (46.78%), with high-matching areas limited to cities such as Guilin and Beihai, while regions like Baise and Hechi remain underutilized (Figure 6a).

In terms of market alignment, 72.40% of destinations are situated in market-advantaged zones. Chongqing ranks highest (91.15%), followed by Sichuan (81.68%), while Guizhou and Guangxi show lower market alignment (61.61% and 61.49%, respectively). Sichuan’s destinations are concentrated in the Chengdu Plain, while Yunnan’s clusters around the central urban agglomeration still lag behind the Chengdu–Chongqing region (Figure 6b).

Synergistic alignment is generally weaker, with only 60.93% of destinations located in synergy-advantaged zones. Chongqing again leads (84.07%), followed by Guizhou (68.44%), while Yunnan (55.08%), Sichuan (51.44%), and Guangxi (45.62%) display lower levels. In many counties with latent synergy potential (such as Pu’er, Chuxiong, Kangding, and Yibin), integrated rural tourism development remains insufficient (Figure 6c).

Encouragingly, alignment with priority zones is relatively high: 79.35% of rural tourism destinations are located within designated priority zones. Chongqing shows the strongest alignment (96.76%), followed by Guizhou (82.55%), Sichuan (81.28%), and Yunnan (77.97%), while Guangxi remains lowest (58.18%). Nevertheless, significant underdeveloped areas persist in remote counties or border regions of each province (Figure 6d).

3.3.2. Development Type Zoning of Rural Tourism Destinations

Based on the spatial match between rural tourism destinations and tourism resource, market, and synergy conditions, counties in Southwest China can be categorized into four development types (Figure 7):

(1) 

Consolidation Type (Maintaining the Perfect Type): This type is distributed across all five provinces, with the fewest counties in Chongqing. These counties already contain a large number of rural tourism destinations and show strong alignment with both tourism resources and market advantages. Future development should focus on shifting from quantity-oriented expansion to quality-oriented improvement—avoiding inefficiency and homogenization—while pursuing high-efficiency and high-quality, boutique development.

(2) 

Enhancement Type (Adding and Upgrading Type): These counties are mainly distributed in Sichuan, Chongqing, and Guizhou, with fewer in Yunnan and Guangxi. Although they already have a certain tourism base, there is still considerable potential to expand the number of destinations. The existing advantages in tourism resources, market, and synergy have not been fully leveraged. Future development should include the moderate addition of new tourism products to address gaps, alongside upgrading the quality of current offerings to better meet evolving market demands.

(3) 

Expansion Type (Expanding Development Type): This type is primarily found in Sichuan and Yunnan, and less so in Guizhou and Chongqing. These counties have a clearly insufficient number of rural tourism destinations, and their tourism resources remain underexplored. Additionally, the tourism market in these areas has not yet been deeply cultivated. Moving forward, development efforts should focus on significantly increasing the number of destinations, fully tapping into resource potential, and promoting integrated rural tourism growth at the county scale.

(4) 

Reserve Type (Reserve Development Type): These counties are mainly concentrated in the Western Sichuan Plateau, with more found in Yunnan and Guizhou, and only two counties in Chongqing. Most of these counties have three or fewer existing rural tourism destinations, and their development is constrained by limited tourism resources and weak market foundations. Although they are not a priority for short-term expansion, selective development is possible by identifying unique local resources and gradually cultivating market demand according to local conditions.

3.3.3. Regional Development Strategy of Rural Tourism Destinations

A differentiated, subregional policy approach is critical to promoting balanced rural tourism development in Southwest China. Based on tourism potential, priority zoning, and existing spatial patterns, two complementary strategies are proposed: ① For lagging regions, efforts should focus on unlocking potential and accelerating development of rural tourism, addressing underdeveloped markets and unexploited resources.② For advanced regions, the focus should shift to refining infrastructure, improving quality and efficiency, and achieving sustainable growth through better resource-market-synergy alignment (

Table 5. Regional development strategy of rural tourism destinations in Southwest China.

Provincial Area	County Rural Tourism Land Zoning Development Strategy
	Maintenance Type	Augmented and Upgraded	Expansion Developmental	Reserve Developmental
Sichuan	Leveraging on Dujiangyan, develop rural tourism around Chengdu’s central city; Cangxi, Wenchuan, Xichong, Miyi, etc., have general potential for rural tourism, and it is advisable to enhance the quality of existing tourist destinations by combining with the county’s characteristics	Constructing Chengdu’s “city-ring” rural tourism belt, developing suburban resorts, idyllic gardens and forest recreation, and extending the industrial chain; upgrading the quality of rural tourism around the central urban areas of Ziyang, Yibin and Ya’an.	Integrate the advantages of natural and human resources in Nanchong, Bazhong, Neijiang, Meishan and Yibin, upgrade rural tourism products, develop diversified rural tourist destinations and open up visitor source markets	The Western Sichuan Plateau has beautiful natural scenery and rich ethnic customs, but poor transport facilities and low density of towns, so it is appropriate to combine the downtown of prefecture-level cities and famous scenic spots to moderately develop cultural experience rural tourism destinations.
Chongqing	Maintaining the good momentum of rural tourism development in Qijiang, Nanchuan, Wulong, Wushan and Tongliang, making use of resources such as Ba culture and river landscape to create ecological leisure and cultural experience tourism boutique villages	The central city and the surrounding Changshou, Jiangjin and other places are still in need of in-depth development, based on the Chongqing metropolitan area’s source market advantage, vigorously develop the agricultural experience and cultural experience of rural tourism places	Most of the counties in the city are in this category, based on the Yangtze River water system and mountainous terrain resource characteristics, the development of leisure along the river, mountainous areas of summer and folk experience tourism villages, to create landscape rural tourism routes	Improve the accessibility of Wuxi and Chengkou to the county, improve the infrastructure and hospitality facilities of rural tourist destinations, highlight the advantages of special agricultural products, and cultivate visitor source markets
Guizhou	Develop idyllic complexes around the “Guiyang-Gui’an-Anshun" metropolitan area, and develop various types of rural holiday products; optimize the structure of rural tourism industry in Xingyi, Dafang, Longli, Shucheng and other counties.	Make full use of tourism resources such as ethnic culture, red culture and karst landscapes in some counties in nine cities and states, upgrade rural tourism products and promote the differentiated development of rural tourist places	Based on the advantages of the visitor source markets in the central urban areas of Guiyang, Zunyi, Bijie, Qiannan and Qiandongnan, explore the development potential of rural tourism and expand the number and types of rural tourist destinations.	Combining the characteristics of tourism resources in Qianxinan, Qiandongnan, Qiannan, Tongren and some other counties in the city and prefecture, develop rural tourist destinations according to local conditions, improve transport conditions and enhance tourism reception capacity.
Yunnan	In-depth development of ethnic culture and natural landscape resources in Yulong, Tengchong, Menghai, Mile, Guangnan and other counties, rural tourism upgraded from static sightseeing to dynamic experience, and gradual development towards boutique products	Tapping into the tourism resources of Dali, Mangshi, Pu’er, Jianshui, Qubei and other counties, exploring domestic and overseas source markets, improving the rural tourism environment, and establishing the brand and image of rural tourism destinations	Vigorously develop urban leisure-type rural tourism destinations in the central Yunnan city cluster; develop rural tourism destinations in Honghe, Wenshan, Lincang and other cities and states around the Greater Western Yunnan Tourism Circle and the border cross-border tourism belt.	Improve the environment and facilities of the existing rural tourism destinations, targeting counties with better tourism resources such as Yuanyang, Cangyuan, Shuangjiang, Yingjiang, Gongshan, etc., to enhance internal and external transport conditions and cultivate visitor source markets
Guangxi	Around the central urban areas of Guilin and Yulin, as well as Rongshui, Daxin, Pubei and other counties, relying on the advantages of the visitor source market and tourism resources, to create boutique rural tourism places such as cultural experiences and recreational holidays	Tapping into the coastal scenery, ethnic customs and landscape and idyllic resources of the Beibu Gulf and Guigang, Hezhou and Hechi, building diversified rural tourism clusters and fostering new forms of rural tourism	Give full play to the advantages of the visitor source market in the central urban areas of Nanning, Guilin, Baise, Laibin, Chongzuo and other prefecture-level cities, and accelerate the development of rural tourist areas through industrial integration and urban-rural integration	Relying on tourism resources such as longevity and health culture, border culture and special agriculture in western Gui, central Gui and eastern Gui, optimize the product system and hospitality services of existing rural tourism destinations

).

Through targeted interventions adapted to local contexts, these strategies aim to promote the coordinated development of rural tourism across the region while reducing inter-regional disparities.

4. Discussion

This study constructed a gap analysis framework for optimizing the spatial layout of rural tourism destinations in Southwest China, integrating tourism resources, market potential, and synergistic conditions. The main results indicate that while the overall rural tourism potential is relatively high across the region (69.10% of counties rated medium or above), significant spatial disparities persist, particularly between core urban agglomerations and peripheral mountainous areas. Moreover, the degree of alignment between existing rural tourism destinations and priority development zones remains uneven, with market alignment generally higher than resource and synergy alignment. This suggests that while market forces increasingly drive rural tourism growth, resource endowments and synergistic infrastructure are not fully utilized in many areas.

Compared to the existing literature, which often focuses on spatial differentiation patterns or influencing factors of rural tourism development [33,34], this study makes several contributions. First, by adapting gap analysis from landscape ecology to tourism geography, it provides a systematic approach to identify spatial mismatches and development gaps in rural tourism. Second, it offers a clear typology of county-level development types (consolidation, enhancement, expansion, reserve), enabling more differentiated and targeted spatial strategies. Finally, it highlights the need for coordinated planning across resource-rich but market-weak regions, especially in mountainous and remote areas, which is often overlooked in previous studies.

Theoretically, gap analysis offers a valuable tool for both conservation and development planning. Originating in landscape ecology, it provides a spatially explicit method for identifying mismatches between existing patterns and desired outcomes. This study enables a precise diagnosis of spatial gaps in rural tourism, supporting both strategic resource allocation and dynamic policy adjustment. This approach enhances planning precision and fosters regional coordination, particularly important in complex mountainous landscapes.

In terms of development pathways, a comparison of Sichuan and Yunnan illustrates two distinct models: clustered development in Sichuan, leveraging urban agglomeration advantages; and dispersed development in Yunnan, reliant on resource-driven attractions. To maximiser the revitalization potential of rural tourism, a “point-to-surface” progression strategy is recommended—using key destinations to drive broader area-wide development, expand market reach, and diversify tourism products. This approach will help achieve sustainable, large-scale rural tourism growth at the county level.

5. Conclusions

Taking Southwest China as a case study, this paper proposes an innovative application of gap analysis for rural tourism, identifying priority development zones based on tourism potential and classifying counties into development types with targeted spatial strategies. This approach addresses previous research limitations by systematically analyzing spatial optimization paths and establishing a technical workflow to support spatial layout regulation of rural tourism destinations in mountainous regions.

The main conclusions are as follows:

(1)

Approximately 69.10% of counties in Southwest China exhibit medium or higher rural tourism potential, concentrated outside the Western Sichuan Plateau and northwest Guizhou. Chongqing ranks highest in overall potential, market strength, and synergy, while Yunnan leads in resource endowment. Priority Zones I, II, and III account for 17.35%, 24.63%, and 27.12% of counties, respectively, with Zones I–II clustered in urban centers, and Zone III covering resource-rich or market-strong areas.

(2)

Rural tourism destinations show a clear “one-core, multi-centre” spatial structure, with the Chengdu Plain as the core. Guizhou forms a belt-shaped cluster; Yunnan, Sichuan, and Guangxi follow a pyramidal pattern, while Guizhou and Chongqing display spindle-shaped structures. Hotspots are concentrated in Chengdu, parts of Guizhou, Chongqing, Guangxi, and Yunnan, while coldspots occur in the western Sichuan Plateau and the Leshan–Pu’er corridor.

(3)

The spatial alignment of rural tourism destinations follows the order: market > resources > synergy. Yunnan and Guizhou show the strongest alignment with resource endowments, while Chongqing leads in market and synergy alignment. Overall, 79.35% of destinations fall within priority zones: Chongqing (96.76%), Guizhou (82.55%), Sichuan (81.28%), Yunnan (77.97%), and Guangxi (58.18%).

(4)

Four county-level development types—Consolidation, Enhancement, Expansion, and Reserve—were identified based on the spatial match between priority zones and destination density. Targeted strategies are needed: for example, central Yunnan should prioritize urban leisure development, while areas such as Honghe, Wenshan, and Lincang, along the Western Yunnan Tourism Belt and border zones, offer potential for expansion.

This study is based on data from a single time point, which limits the ability to capture the dynamic evolution of rural tourism development. As gap analysis is inherently a dynamic planning method, future research should incorporate multi-year, longitudinal data to track spatial changes, evaluate policy impacts, and guide adaptive spatial optimization. Additionally, integrating socio-cultural and environmental sustainability indicators could further enhance the framework’s contribution to rural revitalization and sustainable development in mountainous regions.