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1. Introduction

Traditional villages refer to villages that have obvious local cultural characteristics and rich traditional resources. They have high cultural, historical, aesthetic, and economic values [1]. It can fully reflect the farming civilization of a specific historical period in a certain area and is a cultural heritage combining material form and non-material form [2]. However, with the impact of modern civilization, these villages are facing the dilemma of decline and disappearance. Most traditional villages face many problems, such as the aging of the population, the lack of endogenous economic power, and the destruction of the ecological environment. With the disappearance of the main body of cultural heritage and the destruction of the space environment of cultural buildings, the cultural resources in the village disappear. According to statistics, between 2002 and 2017, the number of traditional villages in China decreased by 920,000; that is, 1.6 villages disappeared every day on average [3]. In response to this problem, the state attaches great importance to the protection and development of traditional villages. Since 2012, a series of important documents have been issued one after another, which have made a comprehensive deployment of the investigation, protection, and development of traditional villages possible. As of 2023, a total of 8171 villages in six batches have been included in the list of traditional Chinese villages. At the same time, the protection and utilization of traditional villages and related research work are also carried out in provinces and cities across the country. In 2018, the proposal of the National Rural Revitalization Strategic Plan (2018–2022) saw the protection of traditional villages as an important part of the national rural revitalization strategy, providing new opportunities for the protection, utilization, and development of traditional villages.

Research on traditional villages and related issues has always been a hot topic, and domestic and foreign scholars have conducted a lot of research. International research on traditional villages began in the 1840s. German geographer Johann Georg Kohl systematically expounded the influence of topography on village morphology and its traffic route in the book The Relationship Between Human Traffic and Topography [4]. In 1906, Otto Schluter first proposed the concept of settlement geography, which systematically studied the spatial layout of villages and the causes of their formation and proposed a theoretical framework of village–environment interrelationships. Subsequently, a series of scholars such as Paul, Albert, and Jean conducted in-depth research on the form, function, and distribution of traditional villages [5,6,7]. Through the investigation and comparative analysis of villages in different regions, they revealed the structural characteristics of villages and the relationship between residents’ activity patterns and the natural environment.

In recent years, the research content has mainly focused on the following aspects: (1) The cultural connotation and value evaluation of traditional villages [3,8]. Huang Zongsheng and others used the landscape aesthetic evaluation method to study the beauty of the traditional villages of the Dong nationality in southeastern Guizhou and summarized the aesthetic characteristics of the Dong villages into the ecological harmony of the natural environment of the village, the beauty of the spatial form, and the practical beauty of the function [9]. Željka and others used cultural models to identify and evaluate cultural landscapes in combination with the relationship between the cultural characteristics of traditional villages and natural heritage [10]. On the premise of the comprehensive analysis of regional characteristics, Liu Peilin [11], Shan Yanming, and others highlighted the characteristic evaluation factors and constructed a more perfect traditional village value standard [12]. (2) Protection and sustainable development of traditional villages [13,14,15]. M. Tas believes that in order to solve the problem of historical heritage destruction, a model of government participation in governance should be established to guide the protection and restoration of traditional villages in Turkey [16]. By studying seven traditional villages in China, Marschalek believes that villagers should give full play to their endogenous motivation when participating in the development of villages and actively integrate into the process of village development, which can play a positive role in promoting the development of villages [17]. Zhang Dayu, Li Ping, and others believe that the development of entertainment, tourism, and leisure activities is one of the important functions of traditional villages. Knowing how to achieve differentiated development, promote economic growth, attract population return, and improve the quality of life and happiness of villagers on the basis of making full use of natural landscape and cultural resources is extremely important [18,19]. (3) Analysis of the landscape pattern, spatial distribution, and influencing factors of traditional villages [1,20,21]. Sprague and others used historical maps to depict Japanese rural landscapes and conducted a multi-buffer analysis. The results showed that traditional rural landscapes usually have a specific spatial structure, and similar cultural landscapes exist in the same cultural area. Based on ArcGIS [22], Liu Dajun and others analyzed the spatial distribution characteristics of 1561 traditional Chinese villages and pointed out that the traditional villages in the country are more common in the south and less common in the north, and that the southwestern region and the middle regions of the Yangtze River are more concentrated [1]. Liu Shuhu, Li Mi, Jia Anqiang, and others used the nearest neighbor index, geographical concentration index, imbalance index, buffer analysis, and other methods to explore the distribution density of traditional villages, the number of urban villages, and the balance of village distribution in the Minjiang River Basin, Wuyue Cultural District, Hebei Province, and other research areas [23,24,25]. Based on quantitative geography, Wang Peijia and Hu Xijun studied the spatial distribution characteristics of traditional villages in Southwest China and Fujian Province and quantitatively analyzed the influence of the natural environment and human and social factors on their spatial distribution [26,27].

In addition, some scholars have also studied the traditional village landscape and living environment [28,29], renewal mechanisms [30], public space form and function [31,32], typical local practices [33], and other aspects. In terms of research scale, there are both macro-scale studies such as national, cultural, regional, provincial, and urban areas [23,34,35] and micro-scale studies based on traditional village cases [24]. In terms of research methods, there are not only qualitative research methods such as constructing evaluation index systems and formulating development countermeasures on the basis of induction and deduction [36,37], but also quantitative research methods such as SPSS and ArcGIS spatial econometric models and spatial syntax [29,38]. In general, the research of traditional villages at home and abroad is developing in the direction of systematization and deepening, showing the characteristics of content subdivision and research category extension.

Although the research results of Chinese traditional villages have gradually increased, there are still problems such as unbalanced research areas and single research methods. Most of the existing research focuses on the areas with strong traditional cultural heritage in the central and eastern regions, and little attention has been paid to the Inner Mongolia region. Moreover, most studies only see terrain, water systems, traffic, and other factors as the main factors affecting the spatial distribution of traditional villages and lack research on the intensity of each influencing factor. With the rapid development of information technology and the deep integration of architecture and urban and rural planning, it has become an inevitable trend to study the spatial distribution and influencing factors of traditional villages from the perspective of geography. Inner Mongolia is located in the northern part of China, and there are a large number of traditional villages. It is urgent to analyze the distribution of traditional villages in Inner Mongolia and explore the influencing factors of village distribution, which is the basic work of traditional village protection. However, the distribution characteristics and influencing factors of traditional villages in different regions are different. The spatial differentiation factors of traditional villages not only have scale differences but also regional differences. In addition to common factors, different regions also have their own unique regional factors. For example, the social self-organization of the populations in Guangdong Province and Guizhou Province has an important impact on the spatial distribution of local traditional villages, while the distribution of traditional villages in Shanxi Province is ‘irrelevant’ to the population distribution but has a strong correlation with unique factors such as slope direction and watershed. Therefore, considering the complexity and regionality of the spatial differentiation of traditional villages, this study takes 207 traditional villages in Inner Mongolia as the research object and comprehensively uses GIS spatial analysis and mathematical statistics analysis to reveal the spatial distribution characteristics of traditional villages in Inner Mongolia and the influencing factors of spatial differentiation from the macro level. In terms of influencing factors, in addition to selecting terrain, river system, transportation, and other factors, it also increases population, economy, climate, and other factors to carry out multi-dimensional research. At the same time, the geographical detector is used to analyze the intensity of different factors on the distribution of traditional villages. It is used to provide a reference for the national rural revitalization strategy and the protection and development of traditional villages in Inner Mongolia.

2. Research Area Overview, Data Sources and Research Methods

2.1. Overview of Study Area

Inner Mongolia is located in northern China, and, across the northeast, north, and northwest, the region from the northeast to southwest oblique extension is long and narrow. The geographical location is between 97°12′ to 126°02′ east longitude and 37°24′ to 53°23′ north latitude. It is adjacent to Heilongjiang, Jilin, Liaoning, Hebei, Shanxi, Shaanxi, Ningxia, and Gansu provinces and borders Russia and Mongolia, with a total area of about 1,183,000 km². The landform is dominated by the plateau; the east is the Greater Khingan Mountains forest; the south is the Nenjiang Plain, the West Liaohe Plain, and the Hetao Plain; the west is the Tengger, the Badain Jaran, and the Ulan Buh Desert; and the north is the Hulunbeier and the Xilinguole grassland. This area is one of the birthplaces of the Chinese nation, and it is also the active area of the northern ethnic minorities in ancient China. The unique natural environment and profound historical culture gave birth to the regional landscape of integration and development between different ethnic groups, resulting in many distinctive traditional villages.

2.2. Data Sources

The research objects include: Six batches of Chinese traditional village lists and seven batches of Chinese historical and cultural towns and villages published by the Ministry of Housing and Urban-Rural Development of the People’s Republic of China, 64 of which belong to Inner Mongolia; the State Ethnic Affairs Commission announced three batches of the Chinese ethnic minority villages list, which belongs to Inner Mongolia, a total of 88; the two batches of famous historical and cultural towns and villages announced by the people’s government of Inner Mongolia Autonomous Region and the total number of villages listed in the cultural relics listed by the national key cultural relics protection units of Inner Mongolia Autonomous Region announced by the Department of Culture and Tourism of Inner Mongolia Autonomous Region are 70. A total of 207 traditional villages were obtained as samples after merging and deduplication of the above data sources (see Figure 1). These villages are regarded as point elements, and Google Earth is used for search and calibration to obtain geographic coordinate information. The natural geographical data come from the National Earth System Science Data Center, and the social and economic data come from the 2022 statistical yearbook of Inner Mongolia Autonomous Region.

2.3. Research Method

Using 207 traditional villages in Inner Mongolia Autonomous Region as the research object, this paper uses the nearest neighbor index, imbalance index, geographical concentration index, and spatial Gini coefficient to quantitatively analyze the spatial distribution of traditional villages in Inner Mongolia by using the spatial analysis tool of ArcGIS10.7 and Excel correlation function and calculates the nuclear density. The distribution characteristics of traditional villages in Inner Mongolia are summarized. Secondly, the buffer analysis tool is used to analyze the influence of natural geographical factors and socio-economic factors on the spatial distribution characteristics of traditional villages in Inner Mongolia. Finally, the factor detection method in the geographical detector is used to analyze the intensity of each factor on the spatial differentiation of traditional villages in Inner Mongolia (see Figure 2).

3. Spatial Distribution Characteristics

3.1. Spatial Distribution Pattern

3.1.1. The Nearest Neighbour Index Analysis

From a macro perspective, traditional villages can be abstracted as point elements, and their geographical locations can be represented by coordinate points. There are three types of spatial distribution of point elements: uniform, random, and condensed. It can be judged by the nearest distance and the nearest point index, which can be used to reflect the spatial distribution and dispersion degree of point elements [39]. The calculation formula is as follows:

(1) $\begin{matrix} R = {\dot{r}}_{i} / r_{E} \\ r_{E} = \frac{1}{2 \sqrt{m / A}} = \frac{1}{2 \sqrt{D}} \end{matrix}$

where R is the nearest point index; r_i is the actual nearest distance; r_E is the theoretical nearest distance; D represents the number of elements per unit area; m is the number of points; and A is the area of the study area. When R = 1, the point elements trend toward random distribution; when R < 1, the point elements trend toward aggregate distribution; when R > 1, it shows that the point elements tend to be evenly distributed. In the article, the area of the study area A = 1.183 million km², and the total number of traditional villages in the study area m = 207. Using the average nearest neighbor analysis of ArcGIS spatial statistical tools, the actual nearest neighbor distance between traditional villages in Inner Mongolia is calculated to be 30.2 km, the theoretical nearest neighbor distance is 37.8 km, and the nearest neighbor index R is 0.799 < 1, indicating that the traditional villages in Inner Mongolia are agglomerated.

3.1.2. The Coefficient of Variation Analysis

The coefficient of variation (CV) is a statistical measure used to measure the degree of variation of observations in the data set [40]. In this study, the Tyson polygon analysis method was used to calculate the relative degree of spatial change in traditional village point elements in Inner Mongolia. The area of the Thiessen polygon changes with the distribution of the point set. Therefore, the distribution type of the estimated sample points is measured by the coefficient of variation CV value of the polygon area (that is, the ratio of the standard deviation of the Thiessen polygon area to the average value). The calculation formula for the CV value is:

(2) $C V = X / M \times 100 %$

X represents the standard deviation of the Voronoi polygon, M is the average area of the Voronoi polygon, and CV is the coefficient of variation. When the spatial distribution type of traditional villages is evenly distributed, the polygon area within and between clusters changes little, and the CV value is small; when the spatial distribution type of traditional villages is aggregated distribution, the polygon area in the cluster is small, but the polygon area between clusters is large, so the CV value is also large. According to Duyckaerts, three recommended values are proposed: when 33% < CV < 64%, the spatial distribution type is random distribution; when CV ≥ 64%, the spatial distribution type is clustered; and when CV ≤ 33%, the spatial distribution type is uniform distribution. According to the CV value classification standard, the CV value and CV value distribution of traditional villages in Inner Mongolia are calculated by ArcGIS10.7 software (see Figure 3). The calculation results show that X = 6554.09 km², M = 5391.55 km², CV = 121.56%, and the CV value of coefficient of variation is greater than 64%, which verifies that the spatial distribution type of traditional villages in Inner Mongolia is cohesive.

3.1.3. Spatial Autocorrelation Analysis

Spatial autocorrelation analysis is used to quantitatively describe the spatial dependence of geographical phenomena. Moran’s I index is a statistical index used to measure spatial autocorrelation, which can be used to evaluate the degree of aggregation or dispersion of data in space [41]. This study uses Moran’s I index to explore the overall spatial correlation of traditional villages in Inner Mongolia. Its calculation formula is as follows:

(3) $I = \frac{n \sum_{i = 1}^{n} \sum_{j = 1}^{n} w_{i j} (y_{i} - \bar{y}) (y_{j} - \bar{y})}{\sum_{i = 1}^{n} \sum_{j = 1}^{n} w_{i j} {(y_{i} - \bar{y})}^{2}}$

Here, n is the total number of spatial units, $y_{i}$ and $y_{j}$ represent the attribute values of the ith spatial unit and the jth spatial unit respectively, $\bar{y}$ are the mean values of all the attribute values of spatial units, and $w_{i j}$ is the spatial weight matrix. The value range of Moran’s I is between −1 and 1. When I > 0, it means that the attribute values of all regions have a positive correlation in space. When I = 0, it means that the regions are randomly distributed and there is no spatial correlation. When I < 0, it means that the attribute values of all regions have a negative correlation in space. Here, the spatial proximity matrix (W) defines the proximity between units i and j. It is usually a square matrix, in which the element $w_{i j}$ represents the spatial relationship weight between units i and j. In grid data, the spatial proximity matrix is usually standardized. The calculation formula is as follows:

(4) $w_{i j} = {\begin{matrix} 1 \\ 0 \end{matrix} (i \neq j)$

When i and j space are adjacent, $w_{i j}$ = 1; when i and j space are not adjacent, $w_{i j}$ = 0. Using Moran’s I to calculate, the estimated value of Moran’s I of traditional villages in Inner Mongolia is 0.32744, the z value of normal statistics is 3.247195, and the test effect of p < 0.01 is significant, indicating that the spatial distribution of traditional villages in Inner Mongolia has significant spatial positive correlation and obvious spatial agglomeration characteristics.

3.2. The Equilibrium Degree of Spatial Distribution

3.2.1. Analysis of Overall Equilibrium Degree

The imbalance index can be used to study the equilibrium degree of the distribution of point elements in different regions [42]. This paper uses the imbalance index to measure the distribution equilibrium of traditional villages in Inner Mongolia. The formula for calculating the concentration index in the Lorentz curve is adopted. The calculation formula is as follows:

(5) $S = \frac{\sum_{i = 1}^{n} Y_{i} - 50 (n + 1)}{100 n - 50 (n + 1)}$

Among them, the imbalance index S is between 0 and 1, n is the number of league cities, and $Y_{i}$ is the cumulative percentage of the ith place after the proportion of traditional villages in the study area is ranked from large to small. The results are shown in Table 1. If the traditional villages are evenly distributed in each research area, then S = 0; if the traditional villages are all concentrated in one area, then S = 1. Using EXCEL to calculate the imbalance index S = 0.387, it shows that the distribution of traditional villages in Inner Mongolia is not balanced.

At the same time, according to the cumulative percentage of the distribution of traditional villages in each city in Table 1, the Lorenz curve is drawn (see Figure 4). It can be further seen from Figure 4 that the traditional villages in Inner Mongolia are mainly distributed in Chifeng, Hulunbeier, Baotou, Eerduosi, and other regions. The number of traditional villages in these four urban areas accounts for more than 59.9% of the total, and there are fewer traditional villages in Wuhai, Wulanchabu, Tongliao, and other regions.

3.2.2. Geographical Concentration Index Analysis

The geographical concentration index is an important index to measure the concentration of research objects and an important parameter to deeply understand the spatial distribution of research objects. The calculation formula is as follows:

(6) $G = 100 \sqrt{\sum_{i = 1}^{n} {(\frac{X_{i}}{T})}^{2}}$

Among them, G is the geographical concentration index, X_i is the number of traditional villages owned by the i-th prefecture-level city in Inner Mongolia, T is the total number of traditional villages in Inner Mongolia, and n is the total number of league cities. The value of G is between 0 and 100. The larger the value of G is, the more concentrated the distribution of traditional villages is. The smaller the value of G, the more dispersed the distribution of traditional villages is. Taking the data in Table 1 into the formula, the geographical concentration index G = 35.1 of traditional villages in Inner Mongolia is obtained. If 207 traditional villages are evenly distributed in each union city, the number of traditional villages in each union city should be 207/12 = 17.25. The calculation results G = 35.1 > 17.25, which shows that from the perspective of the league city scale, the distribution of traditional villages in Inner Mongolia is relatively concentrated, which verifies that the distribution of traditional villages in Inner Mongolia is not balanced, and the imbalance index judgment method is correct.

ArcGIS10.7 is used to visualize the distribution of traditional villages in Inner Mongolia, and the distribution map of traditional villages in Inner Mongolia (see Figure 5) is obtained. The darker the color of the color block on the map, the more traditional villages are distributed. The figure shows that the traditional villages in Inner Mongolia are unevenly distributed in the city. Combined with the data in Table 1, the leagues and cities in the front are mainly Chifeng, Hulunbeier, Baotou, and Eerduosi, and the back are mainly Wuhai, Wulanchabu, Tongliao, Xilinguole, and Alashan. Among them, the deepest color block is Chifeng City, with 47, followed by Hulunbeier, Baotou, and Eerduosi, with 31, 28, and 18, respectively.

3.2.3. Gini Coefficient Analysis

The Gini coefficient is an important way to study the spatial distribution of discrete regions in geography, and it can also be used to compare the regional distribution of research objects. This paper uses it to measure the spatial distribution of traditional villages in Inner Mongolia. Its calculation formula is as follows:

(7) $G = \frac{- \sum_{i = 1}^{N} P_{i} l n P_{i}}{l n N}$

P_i is the proportion of the number of traditional villages in the i region to the total number of villages in the total region, and N is the number of regions divided. Theoretically, the Gini coefficient is between 0 and 1, and the larger the coefficient is, the higher the concentration is. According to the differences in various aspects of 12 cities in Inner Mongolia, Inner Mongolia is divided into four different regions: the northern, the eastern, the central, and the western region (see Figure 6). The Gini coefficient is analyzed to judge the regional distribution of traditional villages in Inner Mongolia. The northern district includes Hulunbeier and Xingan; the eastern region includes Tongliao, Chifeng, and Xilinguole; the central region includes Wulanchabu, Baotou, Huhehaote, Bayannaoer, and Eerduosi; and the western region includes Alashan and Wuhai. Through the above formula, the spatial Gini coefficient G = 0.880 of traditional villages in Inner Mongolia can be calculated, indicating that traditional villages are unevenly distributed in the four major regions, showing a concentrated distribution. It is mainly distributed in the central and eastern regions, and the central region, which ranks first, accounts for 40.1% of the total, followed by the eastern and northern regions, accounting for 32.6% and 21.7% of the total, respectively, while the traditional villages in the western region are less distributed, accounting for only 5.3% of the total.

According to Table 2, the eastern area is slightly larger than the western area, and the density of traditional villages is more than four times that of the west. The eastern region contains 68 traditional villages with a density of 1.93/10,000 km², and the western region contains 11 traditional villages with a density of 0.405/10,000 km². The area of the central region is slightly smaller than that of the northern region, and the density of traditional villages is more than twice that of the north. The central region contains 83 traditional villages with a density of 3.30/10,000 km², and the northern region contains 45 traditional villages with a density of 1.46/10,000 km². It can be seen that the distribution of traditional villages in Inner Mongolia is denser in the middle than in the north and denser in the east than in the west.

3.3. Spatial Aggregation Distribution Characteristics

The nuclear density estimation method is used to calculate the density of the elements in the surrounding area. It is believed that geographical events can occur at any spatial location, but the probability of occurrence at different locations is different. The higher the density, the higher the probability of its occurrence in the area [43]. The Nuclear Density tool in ArcGIS10.7 software was used to analyze 207 traditional villages in Inner Mongolia, and the nuclear density analysis diagram of traditional villages in Inner Mongolia was obtained (see Figure 7). The location of the traditional village cultural center can be identified. From the map, it can be seen that there are two highly dense areas and two secondary dense areas in the spatial distribution of traditional villages in Inner Mongolia, and the overall distribution pattern of ‘two main and two vice’ is presented. The two main bodies include: Huhehaote-south of Baotou-southwest of Bayannaoer-northeast of Eerduosi-western five cities of Wulanchabu and Chifeng City, forming the largest gathering area of traditional villages, especially Huhehaote, Baotou, and Chifeng. The nuclear density value is the highest. The two vices include Xingan and central and northern Hulunbeier, forming two sub-intensive areas of traditional villages. Other cities are scattered within the city, with fewer traditional villages.

4. Influencing Factors of Spatial Distribution

Traditional villages are the products of historical accumulation, and their formation, preservation, and continuity are influenced by various factors. In this paper, representative and visually interpretable factors from economics, society, climate, geography, and other aspects are selected to create analytical graphs, further elucidating the correlations between numerical values.

4.1. Natural Geographical Factors

4.1.1. Topography

Elevation

Natural geography is an important factor affecting the distribution of traditional villages, and the influence of topography is the most obvious. There are some differences in sunshine, temperature, and precipitation in different terrains, which affect the means of production and lifestyle in the region and thus affect the distribution of villages [44]. The whole region of Inner Mongolia is a plateau-type landform area with an average elevation of more than 1000 m, which is the second largest plateau among the four major plateaus in China. It has a variety of complex landforms with plateaus as the main body, including mountains, hills, plains, deserts, and other types. The Greater Khingan Mountains, Yinshan Mountains, and Helan Mountains, the ‘three mountains’ obliquely across the whole region, divide Inner Mongolia into north and south parts, which become the boundaries of the natural environment differences in the whole region. Its north is the narrow sense of the Inner Mongolia Plateau; from east to west in turn are the Hulunbeier Plateau, Xilinguole Plateau, Bayannaoer-Alashan Plateau; the south includes the Greater Khingan Mountains to the east of the Nenjiang West Bank Plain, West Liaohe Plain, Tumed Plain, Hetao Plain, and the Eerduosi Plateau in the southwest.

Using GIS10.7 software to superimpose the traditional villages in Inner Mongolia with the Digital Elevation Model (DEM), the distribution of traditional villages in Inner Mongolia at different elevations is analyzed (see Figure 8). It can be seen from Table 3 that traditional villages in Inner Mongolia are mainly distributed in areas with an elevation of 200–1500 m, of which 4 are distributed below 200 m, accounting for 1.93%, 36 are distributed between 200 and 500 m, accounting for 17.39%, 64 are distributed between 500 and 1000 m, accounting for 30.92%, 92 are distributed between 1000 and 1500 m, accounting for 44.44%, and 11 are distributed between 1500 and 3526 m, accounting for 5.31%. The Inner Mongolia region exhibits significant overall elevation variations and complex topography. However, there is a discernible pattern in the relationship between elevation and the number of villages. In areas with lower elevations, as elevation values increase, the number of villages gradually increases, reaching its peak within the range of 1000–1500 m. Subsequently, with increasing elevation values, the number of traditional villages gradually decreases, and beyond an elevation of 150 m, the distribution of traditional villages experiences a sharp decline.

2.. Slope Value

Slope value is a crucial indicator reflecting the macrotopographic relief [45]. Inner Mongolia features numerous mountainous areas with significant topographic variations, making slope a major factor affecting the distribution of traditional villages. As depicted in Figure 9 and Table 4, traditional villages are distributed across various slope ranges. Specifically, 186 traditional villages are located in the flat slope range (0–5°), accounting for 89.9% of the total; 16 traditional villages are situated on gentle slopes (5–10°), representing 7.7% of the total; 4 traditional villages are found on moderate slopes (10–15°), constituting 1.9% of the total; and 1 traditional village is located on steep slopes (15–20°), making up 0.5% of the total. There are no traditional villages in the high-slope category (greater than 20°). Flat slopes are primarily found in river valleys, plains, and low-lying areas, while gentle and moderate slopes characterize hilly terrains. Steep and high slopes are mainly found in the Greater Khingan Mountains, Yinshan Mountains, and Helan Mountains. Overall, traditional villages in Inner Mongolia are predominantly situated in areas with gentle topography, which helps save labor costs in village construction and enhances the convenience of people’s production and daily life, making it a preferred choice for village site selection.

3.. Slope Aspect

Aspect reflects the orientation of local land surfaces in three-dimensional space, determining the duration and intensity of sunlight received by traditional villages. It exerts a significant influence on people’s production activities and daily routines and is an important factor affecting the distribution of traditional villages. As shown in Figure 10 and Table 5, traditional villages in Inner Mongolia are predominantly situated on sunny slopes. Specifically, 117 traditional villages are located on the southern slopes (including southeast, south, and southwest), accounting for 56.5% of the total, while 47 traditional villages are found on the northern slopes (including northeast, north, and northwest), constituting 22.7% of the total. In the overall distribution of traditional villages, there are more villages on south-facing slopes than on north-facing slopes, and more on east-facing slopes than on west-facing slopes. There is a preference for construction and development in areas with better natural lighting. In practice, traditional villages often combine building placement with the local topography to adapt to the specific environment. This integration helps traditional villages maximize their exposure to sunlight. Furthermore, the selection of village sites is closely linked to local wind patterns, as choosing the appropriate aspect can mitigate the impact of unfavorable winds in the local terrain.

4.1.2. River System

The river is one of the most important factors for people to carry out production activities, and living near the river was the guide for the ancients to choose their place of residence [46]. In ancient times, river flow could not only solve the problem of daily water use and realize the self-sufficiency of agricultural and animal husbandry production but also play a defensive role as a natural barrier. However, flood control and flood discharge are also factors to be considered in village site selection. There are hundreds of rivers in Inner Mongolia. According to different natural conditions, they can be divided into the Erguna River system on the west side of the Greater Khingan Mountains, including the Erguna River, the Genhe River, and the Hailar River. The Nenjiang River system on the east side of the Greater Khingan Mountains, including the Nuomin River, the Chuoer River, the Taoer River, and the Huolin River; the Liaohe River system in the West Liaohe River Plain, including the Xilamulun River, Laoha River, and West Liaohe River; the Yellow River system in Hetao Plain on the south side of Yinshan Mountain, including Wujia River and Yellow River; as well as the western desert inland river system, including Murengaole and Emunnegaole. These rivers are intertwined to form a river system network in Inner Mongolia, which provides a material basis for the formation of traditional villages in Inner Mongolia. By using the neighborhood analysis tool in ArcGIS10.7 software, the buffer analysis of the five-level river system in Inner Mongolia is carried out. According to the ‘2020 Evaluation Criteria for Drinking Water Safety in Pastoral Areas’ promulgated by Inner Mongolia, under the premise that the water source basically meets the use, the water convenience is divided into 5 km–10 km–15 km–20 km four levels. The buffer zones are set to 5, 10, 15, and 20 km, respectively, and superimposed with traditional villages (see Figure 11).

According to Table 6, the number of traditional villages distributed within 5 km from the river is the largest, reaching 88, accounting for 42.51% of the total number. There are 24 villages distributed within 5–10 km from the river, accounting for 11.59% of the total number. There are 22 villages distributed within 10–15 km from the river, accounting for 10.63% of the total number. There are 11 villages distributed within 15–20 km from the river, accounting for 5.31% of the total number. Similar to provinces such as Jiangxi, Shanxi, and Guangdong, traditional villages in Inner Mongolia are primarily located in the vicinity of rivers to meet the needs of production, daily life, and transportation. Therefore, the distribution of traditional villages in Inner Mongolia is closely associated with rivers, exhibiting an overall trend where the number of traditional villages decreases as the distance from rivers increases.

4.1.3. Climatic Conditions

Multiple factors in a certain area interact with each other to form a unique microclimate environment, which has an impact on the architectural form, building height, and architectural layout of traditional villages and indirectly changes the spatial distribution pattern of traditional villages. The climate state of a region can be described by multiple meteorological data points, of which the most commonly used indicators are temperature and precipitation [47]. Therefore, the two evaluation indexes of annual average temperature and annual average precipitation are selected to analyze the distribution relationship with the traditional villages in Inner Mongolia. The two index data are superimposed with the traditional villages in the GIS10.7 platform to obtain Figure 12 and Figure 13. It can be seen from Figure 12 and Figure 13 that the temperature in Inner Mongolia gradually increases from east to west while the precipitation gradually decreases. According to Table 7, there are 53, 86, and 42 traditional villages in the range of 193.619–270.796 mm, 193.619–270.796 mm, and 342.325–507.972 mm of annual average precipitation, accounting for 25.60%, 41.55%, and 20.29%, respectively. In the range of 27.972–108.913 mm and 108.913–193.619 mm, there are only 8 and 18 traditional villages, accounting for 3.86% and 8.70%, respectively.

According to Table 8, there are 52, 72, and 48 traditional villages in the range of annual average temperatures of 2.225–5.293 °C, 5.293–7.977 °C, and 7.977–10.81 °C, accounting for 25.12%, 34.78%, and 23.19% respectively, while there are only 14 and 19 traditional villages in the range of average temperatures of −8.742–1.379 °C and −1.379–2.225 °C, accounting for 6.76% and 9.18%, respectively. The research results indicate that traditional village distribution exhibits significant variations under different climatic conditions. Inner Mongolia primarily experiences a temperate continental monsoon climate, and people tend to establish settlements in the central and eastern plains where the annual average temperature is higher and there is more rainfall. However, due to lower precipitation levels in the western region and lower temperatures in the northeast, there are fewer traditional villages in these areas. Therefore, the spatial distribution of traditional villages in Inner Mongolia shows a positive correlation with temperature and rainfall.

4.2. Socio-Economic Factors

4.2.1. Traffic Factor

The highway is not only the link between traditional villages but also the basis of cultural exchanges. It is one of the important factors in the distribution and development of traditional villages. The article uses highway density to reflect the difference in the degree of traffic development and compares the number of traditional villages in each city with the degree of traffic development. According to Figure 14 and Figure 15, Wuhai, Huhehaote, and Bayannaoer are the top four cities in highway density, but the distribution of traditional villages is less, with only 37 traditional villages accounting for 17.9% of the total number of traditional villages. Baotou, Chifeng, Wulanchabu, and Eerduosi are cities with medium highway density rankings. They are the most densely populated areas of traditional villages. There are 103 traditional villages, accounting for 49.8% of the total number of traditional villages. Xingan, Hulunbeier, Xilinguole, and Alashan are the cities with the lowest highway density. There are 67 traditional villages, accounting for 32.3% of the total traditional villages. Traditional villages are inherently fragile and non-renewable, making them susceptible to external interference and destruction. In regions with well-developed transportation infrastructure, communication with the outside world is more convenient and efficient, which accelerates urbanization. However, in areas with inefficient and inconvenient transportation, external impacts can be mitigated to a certain extent, creating a secure space for traditional villages and promoting the continuation and inheritance of rural culture.

4.2.2. Population and Economic Distribution Factors

Villages are vital places for human production and life, representing the outcome of human activities. Consequently, the distribution of traditional villages is influenced to a certain extent by population distribution and economic development. To investigate the relationship between population and economic factors in Inner Mongolia and the spatial distribution of traditional villages, the natural breaks classification method in ArcGIS was used to conduct regional statistics on urbanization rate, total population, per capita GDP, and the proportion of primary and secondary industries, along with a visual representation of traditional village distribution.

From Figure 15 and Figure 16, it is evident that the city of Chifeng, which ranks first in terms of population, also has the highest number of traditional villages, with 47 villages accounting for 22.71% of the total. The top four cities in terms of population, namely Chifeng, Huhehaote, Tongliao, and Baotou, collectively host 100 traditional villages, constituting 48.31% of the total. The bottom four cities in population, Xingan, Xilinguole, Wuhai, and Alashan, have 36 traditional villages, representing 17.39% of the total. From Figure 15 and Figure 17, the top four cities in per capita GDP, Chifeng, Huhehaote, Tongliao, and Baotou, have a total of 57 traditional villages, accounting for 27.5% of the total. On the other hand, the bottom four cities in per capita GDP, Wulanchabu, Tongliao, Chifeng, and Xingan, host 81 traditional villages, comprising 39.1% of the total. From Figure 15 and Figure 18, in terms of urbanization rate, the top four cities, Wuhai, Baotou, Alashan, and Huhehaote, have 54 traditional villages, representing 26.1% of the total, while the bottom four cities, Wulanchabu, Xingan, Chifeng, and Tongliao, have 81 traditional villages, accounting for 39.1% of the total. Among the cities with the highest proportion of the primary sector, Xingan, Hulunbeier, Tongliao, and Chifeng have 102 traditional villages, making up 49.3% of the total, while the cities with the lowest proportion of the primary sector, Huhehaote, Baotou, Eerduosi, and Wuhai, are home to 61 traditional villages, comprising 29.5% of the total. Regarding the proportion of the secondary sector, Wuhai, Eerduosi, Alashan, and Xilinguole have 40 traditional villages, accounting for 19.3% of the total, whereas cities with the lowest secondary sector proportion, Huhehaote, Tongliao, Chifeng, and Xingan, have 86 traditional villages, constituting 41.6% of the total.

Hence, the distribution of traditional villages is closely related to the economic level and total population of a region. In Inner Mongolia, traditional villages are more abundant in areas with a higher total population, lower urbanization rates, a higher proportion of the primary sector, and a less developed secondary sector. These factors may contribute to the preservation of traditional villages in these regions.

4.2.3. Historical and Cultural Heritage Factors

Throughout history, the Inner Mongolia region has always been a contested territory, where the Han population with an agricultural civilization and the Mongolian ethnic group with a nomadic culture engaged in prolonged struggles. These conflicts extended beyond military confrontations and also involved cultural interactions related to commerce, migration, and clan relationships. It is this rich cultural exchange and blending that has given rise to the distinctive architectural styles and village landscapes found in Inner Mongolia. Traditional villages in Inner Mongolia preserve a wealth of cultural heritage, encompassing various types of villages. For instance, Guchengta Village originated as a military village during the Han Dynasty; Guangshengxi Kedan developed as a trading post village due to commerce and business activities; Niuchangliang Village primarily relies on agriculture as its main production method; and Yangwan Village was formed by immigrants (see Figure 19). In order to conduct a more in-depth analysis of Inner Mongolia’s intangible cultural heritage and traditional villages, this study employed ArcGIS for visual analysis.

Since intangible cultural heritage is a crucial indicator for designating traditional villages, in theory, the number of intangible cultural heritage elements should exhibit a positive correlation with the distribution of traditional villages. However, in the Inner Mongolia region, the distribution of traditional villages presents a different scenario. As observed from Figure 20, there are concentrated clusters of traditional villages in areas with both higher and lower numbers of cultural heritage elements. This phenomenon may be attributed to the fact that the selection of intangible cultural heritage and traditional villages for designation is organized by local governments. Therefore, the influence of local government enthusiasm and initiatives on the designation outcomes cannot be overlooked.

5. Geographical Detection of Impact Factors

5.1. Single Impact Factors Detection

The distribution of traditional villages is influenced by many factors. This paper starts with two aspects of natural geographical factors and social economic factors and selects 13 index elements, such as altitude, river distance, annual average precipitation, annual average temperature, slope value, aspect, highway density, total population, per capita GDP, urbanization rate, number of intangible cultural heritage, proportion of primary industry, and proportion of secondary industry. This paper uses the GeoDetector2018 software platform to analyze the spatial differentiation factors of traditional villages in Inner Mongolia and reveals the influence intensity of each influencing factor on the spatial differentiation of traditional villages in Inner Mongolia. The results are shown in Table 9. The q values of each factor were ranked as follows: X7 highway density (0.566) > proportion of primary industry X12 (0.542) > urbanization rate X10 (0.483) > total population X8 (0.481) > per capital GDP X9 (0.477) > number of intangible cultural heritage X11 (0.467) > proportion of secondary industry X13 (0.383) > annual average temperature X4 (0.283) > elevation X1 (0.086) > annual average precipitation X3 (0.035) > river distance X2 (0.003) > slope value X5 (0.003) > slop aspect X6 (0.001).

In general, socio-economic factors and natural geographical factors have a greater impact on the spatial distribution of traditional villages in Inner Mongolia. In particular, socio-economic factors such as highway density, the proportion of the primary industry, and urbanization rate have the strongest explanatory power for the spatial differentiation of traditional villages in Inner Mongolia, followed by natural geographical factors, while factors such as slope value, aspect, and river distance have weak explanatory power. At present, there are few studies on the influencing factors in the spatial distribution of traditional villages. Wang, Hu, and others believe that the natural environment factors have the highest explanatory power when studying the distribution of traditional villages in Southwest China and Fujian Province [26,27]. The reason for the difference between the results of this study and the existing research is that the natural and social environment in Inner Mongolia is significantly different from other studies. In an agricultural society, as long as there is enough cultivated land, sufficient precipitation and sunshine, and suitable climatic conditions, it is easy to form villages. However, in modern society, traditional villages are more susceptible to urbanization and industrialization. Therefore, socio-economic factors have the most obvious explanatory power.

5.2. Interaction Influence Factors Detection

There are different strength connections between different influencing factors, and the interaction of two factors will weaken or enhance their explanatory power [48]. In order to analyze the influence of the interaction between the two factors on its explanatory power, the interaction factor detection in the geographical detector is used to detect the interaction between the above seven influencing factors so as to judge whether any two factors play a separate role or an interactive role in the spatial distribution of traditional villages in Inner Mongolia and to analyze the main driving force of the spatial distribution of traditional villages in Inner Mongolia by the size of the interaction.

The heat map function in Origin was used to reflect the test results (see Figure 21). The results show that the annual average precipitation ∩ the number of intangible cultural heritage (q = 0.718), the annual average precipitation ∩ the highway density (q = 0.703), the annual average temperature ∩ the number of intangible cultural heritage (q = 0.661), and the elevation ∩ the number of intangible cultural heritage (q = 0.649) are the four groups of interactive factors with the greatest explanatory power. In addition, the q values of the remaining interaction factors are greater than the q values of their single factors, and the detection results can be divided into two-factor enhancement or nonlinear enhancement. It shows that for the spatial distribution of traditional villages in Inner Mongolia, different influencing factors are not only the result of single action but also the result of multiple factors. It is worth noting that the interaction factors with strong explanatory power include annual average precipitation, annual average temperature, and altitude, which proves that the climate and topography of Inner Mongolia have an important impact on the distribution of traditional villages.

6. Discussion

6.1. Natural Environmental Factors as the Foundation of Traditional Village Spatial Distribution

Through quantitative analysis using ArcGIS10.7, the research demonstrates that the distribution of traditional villages in Inner Mongolia is uneven, forming high-density areas primarily in the central region (Huhehaote, Baotou) and the eastern region (Chifeng). There are secondary density areas in the central-northern part of Xingan and Hulunbeier. This distribution pattern is the result of the combined influence of natural geographical conditions, socio-economic factors, and human activities. Among these, natural environmental factors are the foundation of traditional village development [20,21,49]. Elevation, topography, hydrology, and climate conditions have an impact on the formation of traditional villages, subsequently affecting village layouts and spatial forms [50,51,52].

In Inner Mongolia, physical geography plays a significant role in shaping the spatial distribution of traditional villages. Over 75% of traditional villages are situated in areas with elevations ranging from 500 m to 1500 m. This correlation with elevation is closely tied to the region’s topography, which transitions from plateaus to mountains and then to plains as one moves from north to south in Inner Mongolia. The average elevation in Inner Mongolia is over 1000 m, making it inevitable for most traditional villages to be located in high-altitude areas. In general, traditional villages in Inner Mongolia are mostly concentrated in the flat terrain of river valleys and plains, with a preference for south-facing slopes. Traditional villages in the southern part of Inner Mongolia are mainly located on the plains impacted by river systems, particularly in areas like the Tumote Plain and the western Liaohe River Plain. These regions have relatively flat topography, fertile land, abundant hydrological resources, and ample sunlight, making them conducive to agricultural and residential activities and thus providing ideal sites for village establishment.

In the northern part, traditional villages also cluster in mountainous and hilly terrain, primarily around the Yinshan Mountains and the Greater Khingan Mountains. These regions have higher elevations, numerous mountains, and inconvenient transportation, with some basin areas having relatively gentle topography. These valley-bottom areas, influenced by topography, are relatively enclosed and isolated, resulting in less connection between the villages and the outside world. This isolation helps in the preservation and continuation of the traditional village’s character and historical culture.

Additionally, river systems are crucial factors in the distribution of traditional villages. Approximately 42.51% of traditional villages in Inner Mongolia are located within 5 km of rivers. For example, in the Huhhot-Baotou area, traditional villages are mainly concentrated around the Yellow River basin, while in the Chifeng region, they cluster around the Xilamuren River and Lao Ha River. The northern parts of Xingan and Hulunbeier have secondary clusters of traditional villages around the Chuoer River, Taoer River, Huolin River, Erguna River, and Hailar River. Furthermore, some traditional villages are located farther from the rivers, beyond 20km, such as in the Yellow River basin and near the Xilamuren River. In these areas, the high frequency of flooding creates an uncertainty in the site selection process, leading some traditional villages to choose locations farther away from potentially hazardous riverbanks. Overall, the prevalence of traditional villages along both sides of riverbanks suggests that rivers are a significant factor in village site selection. People generally favor building villages in regions with a network of rivers, not only for easy access to water supply for daily needs but also for convenient agricultural and pastoral activities, allowing for self-sufficiency, which is consistent with the findings of other scholars [26,53,54]. However, some villages, while still ensuring access to water sources, are located at a distance from rivers to avoid the risk of flooding. This illustrates the historical wisdom of village site selection, adhering to the principle of “being close to water and avoiding water hazards”.

Finally, climate conditions also influence the spatial distribution of traditional villages [23]. Traditional villages in the Inner Mongolia region are primarily found in areas with an annual average temperature ranging from 2.225 to 10.81 °C, accounting for 83.1% of the total, and in areas with an annual average precipitation ranging from 193.619 to 507.972 mm, which constitutes 87.4% of the total. People often choose areas conducive to agricultural production as their preferred location for building homes. Traditional villages are densely distributed in areas with higher annual precipitation and higher annual average temperatures. Due to variations in topography and latitude, Inner Mongolia experiences diverse climate conditions in different regions. For example, in the arid Alxa region of western Inner Mongolia, despite a higher annual average temperature, the low precipitation and frequent droughts make it less suitable for agriculture and settlement, resulting in fewer traditional village distributions. Conversely, the northern part of the Greater Khingan Mountains in Inner Mongolia experiences special climatic conditions, with adequate annual precipitation but lower annual average temperatures. These climatic conditions affect population distribution and village morphology, as traditional villages in these areas, while present, often do not cluster due to climate limitations. In contrast, the central and eastern plains of Inner Mongolia have relatively higher temperatures and ample precipitation. This climatic condition is very suitable for living and agricultural development. Therefore, in these areas, traditional villages tend to be more inclined to form clusters. In general, the distribution of traditional villages is positively correlated with precipitation and average temperature and is more likely to be distributed in areas with sufficient rain and a warm climate.

6.2. Socio-Economic Factors as the Core of Traditional Village Spatial Distribution

In addition to natural geographical factors, traditional villages are also influenced by economic, population, and social development factors [1,55]. From an economic perspective, the level of economic development in traditional villages has both positive and negative effects [56]. In economically less developed regions, such as Hulunbeier and Chifeng, traditional villages are more widespread. Due to lower economic development and slower urbanization, these areas experience fewer external disturbances, which, although resulting in slower village renovations, also contribute to the preservation of traditional villages. At the same time, economically developed regions like Eerduosi and Baotou also have a higher concentration of traditional villages. These areas have a stronger economic foundation and a higher level of urbanization and industrialization, which can potentially lead to the destruction of the traditional village’s appearance. However, as people’s living standards improve, local governments may have the financial resources and capabilities to protect, repair, and manage traditional villages, to some extent aiding in their continuation. This shows that the protection of traditional villages and economic development are not necessarily contradictory. With economic growth, more specialized funding can be allocated to protect traditional villages, providing better opportunities for their preservation and development.

Additionally, population size also impacts the spatial distribution of traditional villages. Higher population numbers can provide an abundant workforce, which supports the development of agricultural production, handicrafts, and other economic activities within the village, favoring the formation and growth of traditional villages. Moreover, areas with higher population density can provide more opportunities for social and cultural exchanges, promoting the prosperity and diversity of traditional villages. In contrast, in areas with lower populations, relatively scarce labor resources may restrict economic activities and social exchanges within the village, making it challenging to establish traditional villages. According to historical records, since the late Ming and early Qing dynasties, due to frequent disasters and limited arable land in the central plains of China, many Han people have migrated to the southern pastoral lands of Inner Mongolia, engaging in agriculture, commerce, and handicrafts. By the late Qing dynasty, the Qing government implemented the “Immigration and Border Settlement” policy in the Mongolian region, encouraging people from the interior of China to migrate to Mongolian lands [57]. These areas included vast plains and hilly regions that became primary destinations for the Han people. The topography in these areas was relatively flat, with abundant sunshine and fertile soil, making them a good choice for agricultural production. As a result, the population density in these areas is relatively high. With the arrival of Han people in Inner Mongolia, advanced farming techniques were introduced, greatly driving the development of the agricultural economy and leading to the emergence and growth of rural settlements.

Finally, there is a mutual relationship between transportation conditions and the distribution of traditional villages. Transportation conditions can directly influence the selection and establishment of traditional villages. Traditional village distribution can also impact the development and improvement of transportation conditions. In the past, people often considered the convenience of transportation when choosing village locations. Some villages might be located near major transportation routes for easy access and transportation of goods. In contrast, other villages were established in remote or geographically complex areas, resulting in transportation challenges. This interaction needs to be considered comprehensively to better understand and protect traditional villages. However, today’s convenient transportation conditions, while enhancing connectivity between villages and the outside world, may also negatively affect the preservation of traditional villages. On the contrary, those traditional villages with medium traffic conditions not only maintain the accessibility of the village but also avoid the impact of frequent exchanges with the outside world on the traditional village itself, which is more conducive to the protection and inheritance of the village, which is also consistent with the previous research results [58].

In summary, the modernization process poses more threats to traditional villages. However, economically less developed regions have more stable relationships between people and their land, making them more conducive to the preservation of traditional villages. Most traditional villages in Inner Mongolia are located in areas less influenced by modernization and industrialization, characterized by low per capita GDP, higher population totals, and relatively underdeveloped transportation conditions. In general, the initial stage of traditional village formation is primarily influenced by natural environmental factors. However, with the acceleration of industrialization, external socio-economic factors have become the core determinants of the continuation and development of traditional villages.

6.3. Future Development Vision of Traditional Villages in Inner Mongolia

Traditional villages serve as the carriers of Chinese culture and bear witness to the historical amalgamation of different ethnicities. However, they are susceptible to external influences. Therefore, it is imperative to achieve the sustainable development of traditional villages in Inner Mongolia. With the introduction of the national rural revitalization strategy, the protection and development of traditional villages have found new opportunities. In the context of safeguarding and developing traditional villages, several crucial steps need to be taken. Firstly, there should be a focus on the collection of information about existing traditional villages. Employing digital technology, digitized data about traditional villages, including essential cultural relics and significant structures, should be gathered. Electronic databases should be established comprehensively to realize the full-factor digitized protection of heritage in traditional villages. Secondly, it is essential to construct a diverse industrial system for traditional villages. This can be achieved by capitalizing on the cultural significance and inherent advantages of these villages. Emphasis should be placed on the development of traditional craftsmanship and service industries, primarily driven by cultural creativity and tourism. By exploring the synergy between primary, secondary, and tertiary industries centered around traditional villages, a multi-dimensional model for rural revitalization should be established. This model could encompass folklore, tourism, sightseeing, eco-friendliness, and cultural creativity, fostering a comprehensive approach to rural revitalization that further advances regional sustainability. Finally, when drafting regional development guidelines and policy systems, it is crucial to formulate specific and localized criteria and protection methods for identifying traditional villages based on the actual conditions of each province. These criteria and methods should preserve the integrity and authenticity of traditional villages while facilitating their protection and utilization. This precision-focused approach should be coupled with the establishment of a robust support system to drive balanced development across Inner Mongolia’s traditional villages.

However, regarding the factors influencing traditional villages in Inner Mongolia, this study primarily focused on a macro-level analysis, considering natural geographical and socio-economic aspects. Factors such as morphological features, architectural types within traditional villages, and more granular aspects were not considered. Future research will need to comprehensively integrate these factors and employ a macro-micro-combined approach to delve into the spatial distribution mechanisms of traditional villages. Moreover, this study relied on nationally and provincially approved traditional villages as its samples. However, there are still traditional villages of value that have not been included in these listings. Consequently, this paper presents the distribution characteristics of traditional villages in Inner Mongolia at the present stage and suggests a comprehensive analytical method. As new traditional villages emerge, the results may undergo revisions accordingly.

7. Conclusions

This paper takes 207 traditional villages in Inner Mongolia as the research object and studies the spatial distribution characteristics and influencing factors of traditional villages in Inner Mongolia. The conclusions are as follows:

Through the nearest neighbor point index, the coefficient of variation analysis, spatial autocorrelation analysis, and kernel density analysis, it can be seen that the traditional villages in Inner Mongolia belong to the condensed distribution, showing the distribution pattern of ‘two main and two vices’ in space, forming a high-density area dominated by the Hubao area in the middle of Inner Mongolia and the Chifeng area in the east.
The imbalance index of traditional villages in Inner Mongolia is S = 0.387. The Lorentz curve is far from the average distribution line, and the bending is obvious. The geographical concentration index = 35.1 > 17.25, which shows that from the perspective of the city, the distribution of traditional villages in Inner Mongolia is uneven, mainly concentrated in Chifeng, Hulunbeier, Baotou, and Eerduosi.
The Gini coefficient shows that the distribution of traditional villages in Inner Mongolia is denser in the center than in the north and denser in the east than in the west, with the densest characteristics in the central region.
Socio-economic factors and natural geographical factors are important factors affecting the spatial distribution of traditional villages in Inner Mongolia, especially socio-economic factors. Among them, the economic level, traffic conditions, population, elevation, and temperature conditions are the main factors affecting the spatial distribution of traditional villages in Inner Mongolia.
Socio-economic factors and natural geographical factors are important factors affecting the spatial distribution of traditional villages in Inner Mongolia, especially the socio-economic factors. Among them, the highway density, the proportion of the primary industry, the number of intangible cultural heritages, and the total population are the main factors affecting the spatial distribution of traditional villages in Inner Mongolia.

Author Contributions

Writing the initial draft and data acquisition and analysis: D.L.; funding support: X.G.; Data organization: S.L.; Translation and review: W.Z.; Image processing: M.Y.; Writing supervision: P.L. All authors have read and agreed to the published version of the manuscript.

Data Availability Statement

Data are contained within the article, the data supporting the findings of this study are available upon request.

Conflicts of Interest

The authors declare no conflict of interest.

Footnotes

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Figures and Tables

Figure 1. Spatial distribution map of traditional villages in Inner Mongolia.

Figure 2. Research approach.

Figure 3. Thiessen polygon distribution map of traditional villages in Inner Mongolia.

Figure 4. Lorenz curve of spatial distribution of traditional villages in Inner Mongolia.

Figure 5. The distribution map of urban area of traditional villages in Inner Mongolia.

Figure 6. Regional distribution map of traditional villages in Inner Mongolia.

Figure 7. The nuclear density analysis map of traditional villages in Inner Mongolia.

Figure 8. The correlation map between the distribution of traditional villages and the elevation in Inner Mongolia.

Figure 9. The correlation map between the distribution of traditional villages and the slope in Inner Mongolia.

Figure 10. The correlation map between the distribution of traditional villages and the slope aspect in Inner Mongolia.

View Image - Figure 11. The correlation map between the distribution of traditional villages and the buffer zone of river system in Inner Mongolia.

Figure 11. The correlation map between the distribution of traditional villages and the buffer zone of river system in Inner Mongolia.

View Image - Figure 12. The correlation map between the distribution of traditional villages and the annual average precipitation in Inner Mongolia.

Figure 12. The correlation map between the distribution of traditional villages and the annual average precipitation in Inner Mongolia.

View Image - Figure 13. The correlation map between the distribution of traditional villages and the annual average temperature in Inner Mongolia.

Figure 13. The correlation map between the distribution of traditional villages and the annual average temperature in Inner Mongolia.

Figure 14. The correlation map between the distribution of traditional villages and the highway density in Inner Mongolia.

View Image - Figure 15. Distribution map of the number of traditional villages and economic development level in various cities of Inner Mongolia.

Figure 15. Distribution map of the number of traditional villages and economic development level in various cities of Inner Mongolia.

Figure 16. The correlation map between the distribution of traditional villages and the total population in Inner Mongolia.

Figure 17. The correlation between the distribution of traditional villages and per capita GDP in Inner Mongolia.

Figure 18. The correlation map between the distribution of traditional villages and the urbanization rate in Inner Mongolia.

View Image - Figure 19. Spatial forms of different types of traditional villages: (a) Military village; (b) trading post village; (c) agricultural village; (d) immigrant village.

Figure 19. Spatial forms of different types of traditional villages: (a) Military village; (b) trading post village; (c) agricultural village; (d) immigrant village.

View Image - Figure 20. The correlation between the distribution of traditional villages and the number of intangible cultural heritage in Inner Mongolia.

Figure 20. The correlation between the distribution of traditional villages and the number of intangible cultural heritage in Inner Mongolia.

Figure 21. The distribution map of urbanization rate of municipalities in Inner Mongolia.

Table 1

A statistical table of traditional villages in various cities in Inner Mongolia.

City Name	Number of Traditional Villages	Billing	Proportion/%	Cumulative Proportion/%
Chifeng	47	1	22.71	22.71
Hulunbeier	31	2	14.98	37.68
Baotou	28	3	13.53	51.21
Eerduosi	18	4	8.70	59.90
Huhehaote	15	5	7.25	67.15
Xingan	14	6	6.76	73.91
Bayannaoer	12	7	5.80	79.71
Alashan	11	8	5.31	85.02
Xilinguole	11	9	5.31	90.34
Tongliao	10	10	4.83	95.17
Wulanchabu	10	11	4.83	100.00
Wuhai	0	12	0	100.00
Total	207

Table 2

Statistical table of regional distribution of traditional villages in Inner Mongolia.

Region	Number of Traditional Villages	Proportion	Area/km²	Density/units/10,000 km²	Including the City
Northern Region	45	40.10%	308,100	1.46	Hulunbeier, Xingan
Eastern Region	68	32.85%	352,135	1.93	Tongliao, Chifeng, Xilinguole
Central Region	83	21.74%	251,568	3.30	Wulanchabu, Baotou, Huhehaote, Eerduosi, Bayannaoer
Western Region	11	5.31%	271,754	0.40	Alashan, Wuhai
Total	207

Table 3

Statistical table of elevation distribution of traditional villages in Inner Mongolia.

Elevation	Under 200 m	200–500 m	500–1000 m	1000–1500 m	1500–3526 m	Grand Total
Number of Traditional Villages	4	36	64	92	11	207
Proportion	1.93%	17.39%	30.92%	44.44%	5.31%	1

Table 4

Statistical table of slope situation of traditional villages in Inner Mongolia.

Slope Value	0–5°	5–10°	10–15°	15–20°	>20°	Grand Total
Number of Traditional Villages	184	16	4	1	0	207
Proportion	88.89%	7.73%	1.93%	0.48%	0%	1

Table 5

Statistical table of slope aspect of traditional villages in Inner Mongolia.

Slope Aspect	Flat Ground	North	Northeast	East	Southeast	South	Southwest	West	Northwest	Grand Total
Number of Traditional Villages	2	17	12	19	47	53	17	22	18	207
Proportion	0.97%	8.21%	5.80%	9.18%	22.71%	25.60%	8.21%	10.63%	8.70%	1

Table 6

Statistical table of river system buffer zone of traditional villages in Inner Mongolia.

Buffer Distance	2.5 km below	2.5–5 km	5–10 km	10–15 km	15–20 km	More than 20 km	Grand Total
Number of Traditional Villages	63	25	24	22	11	62	207
Proportion	30.43%	12.08%	11.59%	10.63%	5.31%	29.95%	1

Table 7

The annual average precipitation statistics of traditional villages in Inner Mongolia.

Annual Average Precipitation Range	27.972–108.913 mm	108.913–193.619 mm	193.619–270.796 mm	270.796–342.325 mm	342.325–507.972 mm	Grand Total
Number of Traditional Villages	8	18	53	86	42	207
Proportion	3.86%	8.70%	25.60%	41.55%	20.29%	1

Table 8

The annual average temperature statistics of traditional villages in Inner Mongolia.

Annual Average Temperature Range	−8.742–1.379 °C	−1.379–2.225 °C	2.225–5.293 °C	5.293–7.977 °C	7.977–10.81 °C	Grand Total
Number of Traditional Villages	14	19	52	72	48	207
Proportion	6.76%	9.18%	25.12%	34.78%	23.19%	1

Table 9

The geographical detection results of the influencing factors of the spatial distribution of traditional villages in Inner Mongolia.

Level of Influencing Factors	Serial Number	Index Factors	q Statistic
Natural Geographical Factor	X1	elevation (m)	0.086
	X2	river distance (km)	0.003
	X3	annual average precipitation (mm)	0.035
	X4	annual average temperature (°C)	0.283
	X5	plop value (°)	0.003
	X6	aspect (°)	0.001
Socioeconomic Factor	X7	highway density (km/(km²))	0.566
	X8	total population (million)	0.481
	X9	per capital GDP (thousand)	0.477
	X10	urbanization rate (%)	0.483
	X11	number of intangible cultural heritage	0.467
	X12	proportion of primary industry (%)	0.542
	X13	proportion of secondary industry (%)	0.383

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This paper takes 207 traditional villages in Inner Mongolia as the research object and uses the ArcGIS10.7 software platform, using the nearest neighbor index, coefficient of variation analysis, spatial autocorrelation analysis, imbalance index, kernel density estimation method, geographical detector, and other methods to explore the spatial distribution characteristics and influencing factors of traditional villages in Inner Mongolia. The research shows that: (1) the spatial distribution of traditional villages in Inner Mongolia is condensed; the distribution of cities is uneven; and the overall distribution pattern of ‘two main and two vice’ is presented. (2) The traditional villages are mainly distributed in the altitude area of 500–1500 m, and their spatial distribution characteristics are positively correlated with the annual average temperature, annual precipitation, total population, the proportion of the primary industry, and the number of intangible cultural heritage, and negatively correlated with the slope, river distance, highway density, per capita GDP, urbanization, and the proportion of the secondary industry. (3) The results of GeoDetector2018 software show that socio-economic factors are the primary factors affecting the spatial distribution of traditional villages in Inner Mongolia, followed by natural geographical factors. The interaction and synergy between the influencing factors have increased significantly, which jointly affects the spatial pattern of the distribution of traditional villages in Inner Mongolia. The purpose of the study is to provide reference for the protection and development of traditional villages in Inner Mongolia and the implementation of the national rural revitalization strategy.

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Title

Spatial Distribution and Influencing Factors of Traditional Villages in Inner Mongolia Autonomous Region

Author

Li, Donghao¹; Gao, Xinchun²; Lv, Siyang¹; Zhao, Wanwan¹; Meng Yuan¹; Li, Pengtao¹

¹ School of Architecture, Inner Mongolia University of Technology, Hohhot 010051, China; [email protected] (D.L.); [email protected] (S.L.); [email protected] (W.Z.); [email protected] (M.Y.); Inner Mongolia Autonomous Region Green Building Engineering Technology Research Center, Hohhot 010051, China
² Inner Mongolia Institute of Architectural Survey and Design, Hohhot 010011, China; [email protected]

First page

2807

Publication year

2023

Publication date

2023

Publisher

MDPI AG

e-ISSN

20755309

Source type

Scholarly Journal

Language of publication

English

DOI

https://doi.org/10.3390/buildings13112807

ProQuest document ID

2893057319

Spatial Distribution and Influencing Factors of Traditional Villages in Inner Mongolia Autonomous Region

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