Spatial Structure and Evolution of Territorial Function of Rural Areas at Cultural Heritage Sites from the Perspective of Social Space

Abstract

Affected by multiple factors, differentiated capital investment and power games have led to the uneven regional development of rural areas at cultural heritage sites. Therefore, it is urgent to reflect on the spatial equity and justice of heritage sites from the perspective of social space. This study took the territorial function of rural areas (TFRA) as its research objective, utilizing the UNESCO World Cultural Heritage Site—the Qinshihuang Mausoleum—and the Qianling Mausoleum and the Qiaoling Mausoleum in Shaanxi Province as cases. Based on the theory of spatial production, an index system of TFRA was constructed using social and spatial dimensions. Factor analysis and social–spatial differentiation indices were employed to identify the spatial structure and differentiation of TFRA. The results show the following: (1) the case areas reflect eight principal components, and these components have obvious spatial differentiation characteristics; (2) the principal components related to heritage display and utilization have had a sustained impact over the past decade, which have driven the development of related industries, but the scores of principal components related to the restrictions of heritage protection have been decreased; (3) six functional type zones are designated, and the spatial pattern of TFRA presented a concentric circle with a core-periphery structure, which is influenced by heritage protection zoning; (4) high-value-added functional spaces form and expand along transportation lines; (5) the inherent demand for capital proliferation is the fundamental driving force for the differentiation and evolution of TFRA at heritage sites. Based on the results of the above analysis, strategies of coordinated development between society and space are proposed to address the issue of uneven regional development at heritage sites.

1. Introduction

At present, China has entered a new stage of strengthening the display and utilization of heritage, and promoting the integration of heritage utilization and regional development has become the theme of the current era [1]. As scarce resources with a high value, a wide area, and a strong influence, the protection and utilization of cultural heritage involve profound benefit distributions and spatial adjustments, resulting in the complex interweaving of spatial contradictions and social problems [2,3]. The transformation of space and landscape sat heritage sites causes social problems, such as the transformation of residents’ livelihood modes and the disintegration of rural society and culture. Therefore, the research focus of the academic community has gradually shifted from “heritage” to “heritage site,” which means that the research focus has been expanded to the humanistic and social environment organically connected to cultural heritage [4].

Heritage tourism has driven regional social and economic development. However, due to the influence of local history, transportation, natural conditions, the heritage protection system, and other factors, the coexistence of widespread poverty and poverty alleviation was observed to occur in a number of villages after the exhibition and utilization of cultural heritage [5], which has reduced the sustainability of livelihoods in living heritage sites [6]. These phenomena have exposed uneven development and insufficient development of cultural heritage sites on both macro and micro scales [7]. Heritage protection and utilization is not only a spatial issue but also a complex social issue [8]. In terms of spatial dimension, land use or land cover is commonly used to indicate the spatial evolution of heritage sites [9,10]. The spatial functional structure of heritage sites has obvious differentiation characteristics, and the spatial dynamics of the land use categories are governed on the one hand by natural phenomena and on the other by anthropogenic ones [11,12]. Under the influence of various types of capital investment and heritage protection management, the production methods of heritage communities have evolved and differentiated [13]. This feature is also reflected in the spatiotemporal evolution of housing and land prices before and after heritage protection and utilization [14,15]. In terms of the social dimension, the process of cultural heritage utilization is led by the government, and spatial resources are coordinated through planning, public investment, and policy formulation, which involve various measures, such as relocation, resettlement, and compensation [16,17]. Capital investment and power games result in the transformation and differentiation of the livelihood methods of heritage sites, which in turn leads to the wealth gap among local residents. The use of cultural heritage means transforming the traditional culture and way of life of local villages into “commodities” for sale to foreign tourists, and this commercialization process has exacerbated the alienation of local residents [18,19]. Existing studies have adopted game theory, network analyses, and other methods to analyze the impact of heritage protection and utilization on the participation structure of stakeholders [20,21]. Based on social resilience and tourism empowerment, some scholars have conducted studies on interest distribution and cultural compensation in the protection and utilization of cultural heritage [22]. However, these sociological paradigms cannot reveal the causes of uneven regional development from the spatial dimension. Building a comprehensive analytical framework that combines various socioeconomic indicators with quantitative spatial analysis is a research direction that needs to be deepened.

A superposition analysis of various social and economic attributes in space would help to analyze the connection and differentiation of the rural spatial functions in cultural heritage sites. It is important to reveal the territorial function of rural areas (TFRA) from the perspective of social space in order to accurately determine the rural development status of heritage sites. At the beginning of the 20th century, the Chicago School regarded space as the carrier of society and analyzed the urban regional functional structure from the perspective of the social–spatial structure. Burgess, Hoyt, Harris, et al. put forward models of social spatial structure with concentric circles, fans, and multi-core, respectively [23,24,25]. After summing up the principal components of social differentiation in American cities, Shevky et al. proposed that socioeconomic status, family and race, and other principal components are the basic elements of forming a social area [26,27]. However, this descriptive method could not explain the spatial distribution patterns of these sociological variables. The development of computer technology has made it possible to introduce factor analysis methods into the study of social areas. A follow-up study using a factor analysis showed that the spatial patterns of social areas formed by the above principal components are different. The superposition of various elements in space constitutes a whole urban social–spatial structure model [28,29]. For example, existing studies have revealed social–spatial structures from the perspective of globalization [30], residential spatial differentiation from the perspective of migrant residential isolation [31], and the characteristics of urban social–spatial structures from the perspective of behavioral geography [32]. Facing the complex social contradictions and conflicts in the process of space capitalization, binary opposition analyses of “society–space” are slightly weak. Therefore, Lefebvre spatialized materialist dialectics and put forward the theory of space production, believing that space is not only the product of a society but also a reflection of its social structure [33]. This theory extends the unbalanced investment of capital between industries or sectors to the spatial domain, describes the capital motivation of uneven geographical development from the perspective of the spatial division of labor and space–time compression, and reveals the law of spatial development from the perspective of the capital cycle [34]. Because it is not only constrained by the protection system but also driven by the utilization of tourism, the evolution of TFRA at cultural heritage sites has a uniqueness and a particularity.

This research integrates the comprehensive interaction between society and space, and it constructs an index system from the two dimensions of society and space to determine the principal components affecting the spatial structure and differentiation characteristics of TFRA at cultural heritage sites. Then, functional areas are divided by conducting a cluster analysis, and evolutionary characteristics are presented using multi-time cross-sectional data. This research reveals the causes and mechanisms of imbalanced development in heritage areas. It is of great significance to build a rural development model with the rational utilization of heritage, efficient space development, and social equity and justice.

2. Materials and Methods

2.1. Study Area

As the ancient capital area of the Zhou, Qin, Han, and Tang Dynasties of China, Shaanxi is densely distributed with large-scale cultural heritages, such as imperial tombs and ancient city sites. The cultural heritages in Shaanxi are abundant in quantity, high in level, full in variety, and densely distributed; this is rare in China, even worldwide, and these cultural heritages have an extremely high historical, cultural, and tourism value [35]. In this research, three cultural heritage sites, namely, the Qin Shihuang Mausoleum, Tang Qianling Mausoleum, and Tang Qiaoling Mausoleum, in Shaanxi are selected as study areas. These cultural heritages have been displayed and utilized for a long time, and the surrounding villages have been affected by this process over a long period of time. These sample areas of this study cover the protection zone, the controlled construction zone, and the unprotected zone, and there are 36 villages around the 3 cultural heritage sites (Figure 1).

2.2. Methods

The TFRA at cultural heritage sites is the result of the interaction between space, interest relationships, and policies [36]. The protection and utilization of cultural heritage require immense financial investment [37], and the optimal allocation of capital investment has led to differences in the spatial functions of each surrounding village. At the same time, the processes of space construction and tourism development also affect the local social structures [38]. Under the heritage protection system, heritage communities have used the positive externality of heritage utilization to develop and construct rural space, and space constructions have a feedback effect on the social interest network [39]. Therefore, we need a new, powerful theory to explain the spatial structure and evolution of TFRA.

The production of space is a significant theory used to interpret the relationship between society and space [33,40], and it proposes that social characteristics determine spatial functions [41]. The theory of spatial production puts forward the ternary dialectical framework of space, and it holds that there is a “third space” connecting social reproduction to spatial reproduction. The interaction between society and space is realized through the third space, which is filled with capital, power, and class [41]. The core idea of spatial production is to construct an interactive relationship between concrete and abstract concepts and between materials and society. Imbalanced regional development is the key theme of space production [42]. This research combines the ternary analysis framework of spatial production with the realistic characteristics of heritage sites, and it further incorporates the space of practice, the space of representation, and the representation of space in its theoretical system so as to reveal the spatial structure and evolution of TFRA at heritage sites (Figure 2).

The space of practice is the external material environment guiding individual and group behaviors, which belong to the space category. In this study, it refers to the construction of a spatial environment due to adjustments of production modes or a functional transformation, such as the transformation of land use, housing use, and transportation conditions, reflecting the “man–land relationship”. The space of representation is conceptualized as spatial imagination, which belongs to the social category. Specifically, it represents culture and ideology through policies, systems, and planning, reflecting interests and cooperation modes, such as employment and income status and land ownership. It is the embodiment of “human relationships.” The representation of spaces, or the “third space,” is a comprehensive dialectic of society and space, representing the interactive relationship between society and space [43]. It can be considered that space is the embodiment of production modes, and society is the embodiment of social production relationships.

This research constructed an index system based on two aspects, namely, “space of practice” and “space of representation,” which reflect the two dimensions of society and space, comprising two categories and nine subcategories (

Table 1. Social–space index system of TFRA at cultural heritage sites.

Type	Essential Factor	Specific Indicators
Spatial dimension: space of practice	Agriculture	Per capita cultivated land area, planting area of grain crops, planting area of cash crops, etc.
	Rural enterprises	Area occupied by individual enterprises, number of individual enterprises, number of collective enterprises, area occupied by collective enterprises, etc.
	Traffic conditions	Length of village roads, number of village parking lots, etc.
	Living conditions	Homestead area, housing type, house structure, years of residence, etc.
	Ecological environment	Forest land area, waste slope area, etc.
Social dimension: space of representation	Population structure	Local population, number of migrant populations, outgoing employed population, population employed in the village, sex ratio, age composition, etc.
	Family composition	Total number of households, per household population, number of impoverished households, etc.
	Land ownership	Area of land requisitioned, area of leased land, etc.
	Employment status	Population employed in scenic areas, number of agritainment households, number of commodity sales households, number of stalls, number of tour guides or drivers, number of transportation logistics households, etc.

). A factor analysis and a social–spatial differentiation index were used to clarify the spatial structure of TFRA at the cultural heritage sites. Finally, a dialectical analysis of “social–space” through the “representation of space” was used to reveal the mechanism of the evolution and differentiation of TFRA.

2.2.1. Factor Analysis

The villages around the heritage sites were taken as the basic statistical units, and the indicators in Table 1 were taken as the variables. Then, a principal component analysis was carried out on this original data matrix, and each principal component was given a name according to the level of the indicator load. These principal components can be regarded as the dominant factors of TFRA at heritage sites. The principal component scoring matrix of each village was obtained by multiplying the principal component load matrix by the original data matrix, and the spatial distributions of the principal component scores of each village were plotted. Furthermore, villages with similar features were classified into the same functional area using cluster analysis.

2.2.2. Social–Spatial Differentiation Indices

The social–spatial differentiation indices reflect the degree of differentiation relative to the average distribution pattern. The method is as follows:

$$I_d=\frac{1}{2}{{\displaystyle \sum }}_{i=1}^n\left|\frac{X_i}{{{\displaystyle \sum }}_{i=1}^n{X}_i}-\frac{1}{N}\right|$$

(1)

where I_d represents the differentiation indices, N represents the number of sample villages, and X_i represents the indicator value of village i.

Finally, the values of the differentiation indices in 2010 were taken as the horizontal axis, and the values of the differentiation indices in 2020 were taken as the vertical axis; each index’s value was reflected in the coordinate map, intuitively revealing the evolution characteristics of various indices from 2010 to 2020.

2.2.3. Spatial Statistical Analysis and Spatial Dialectical Analysis

The type and quantity of the villages in each functional area were analyzed based on protection zoning, spatial location, and traffic conditions. Through a questionnaire interview, a participatory evaluation, and other methods, micro-deconstruction, in addition to a macroscopic mathematical analysis, was enhanced to analyze the socioeconomic causes of TFRA at heritage sites.

2.3. Data Source and Processing

The data in this research were acquired from the statistical bulletins of village committees, a questionnaire, and semi-structured interviews. The statistical data include the area of village planting and land use, population and family structure, village enterprise statistics, village history data, and village planning. The questionnaire mainly involved questions about family age, labor force composition, social connection, family management, and livelihood models. The semi-structured interviews involved questions about the changes in the village development process, changes in population, and leading industries. The research group went to 36 villages around the case sites to conduct field investigations from 12 to 20 July and from 7 to 15 September 2021. Samples were taken according to the number of the last house, and questionnaires were issued to ensure that the sample number of each village was more than 20, and 805 valid questionnaires were collected. One or two main leaders of each village were selected for interviews. The above data formed the main basis of this research.

3. Result

3.1. Spatial Distribution and Evolution of Principal Components of TFRA

3.1.1. Spatial Characteristics of Principal Components of TFRA in 2020

(1)

Principal components of TFRA at heritage sites

The dimensions of the 49 indicators of these 36 case villages were reduced using the principal component analysis method. Finally, eight principal components were obtained, and the cumulative variance contribution rate of the eight principal components reached 74.94% after rotation, so they reflected most of the data information. The eight principal components were named as follows: (I) the land acquisition and resettlement factor (22.89%), (II) the tourism driving factor (21.00%), (III) the restriction factor of heritage protection (7.57%), (IV) the agricultural commercialization factor (5.90%), (V) the rural industrialization factor (5.07%), (VI) the natural resource development factor (4.74%), (VII) the ecological factor (4.32%), and (VIII) the scenic spot employment factor (3.45%) (

Table 2. Principal component matrix of TFRA in 2020.

Type	Specific Indicators	Principal Components Load
		Ⅰ	II	III	IV	V	VI	VII	VIII
Spatial dimension	Per capita cultivated land area	−0.478	−0.482	0.451	−0.079	−0.271	−0.013	−0.065	0.314
	Planting area of grain crops	−0.121	−0.368	0.750	−0.117	−0.125	0.153	−0.12	0.224
	Planting area of cash crops	0.092	−0.102	0.01	0.165	−0.171	−0.18	0.165	0.04
	Area occupied by enterprises	−0.027	−0.081	0.089	0.152	0.08	0.715	−0.085	−0.183
	Number of collective agricultural enterprises	0.226	−0.155	0.383	0.044	0.158	0.321	−0.019	0.177
	Number of collective industrial enterprises	−0.027	−0.044	−0.025	0.049	0.931	−0.063	−0.072	0.029
	Number of collective service enterprises	−0.151	0.937	−0.092	−0.051	−0.027	−0.053	−0.042	0.094
	Number of individual agricultural enterprises	0.073	−0.063	0.036	0.891	−0.075	0.028	0.019	−0.118
	Number of individual mining enterprises	0.041	−0.003	0.222	−0.027	−0.063	0.867	0.012	−0.012
	Number of individual manufacturing enterprises	0.153	0.185	0.022	−0.281	0.675	−0.047	0.359	−0.063
	Number of individual tourism enterprises	−0.035	0.901	−0.092	−0.104	0.003	0.018	0.131	−0.074
	Number of agricultural product processing enterprises	0.443	−0.052	−0.149	0.713	0.239	0.003	0.19	0.068
	Number of individual packaging logistics industries	0.451	−0.08	−0.186	0.508	0.147	0.071	0.103	−0.095
	Length of village roads	0.148	−0.227	0.514	−0.031	0.096	0.048	0.268	0.039
	Number of village parking lots	0.036	0.808	−0.127	0.272	0.298	−0.017	0.132	0.082
	Homestead area	0.563	−0.047	−0.056	0.353	−0.047	0.123	−0.041	−0.071
	Number of two-story households	0.547	0.513	−0.357	0.385	−0.16	−0.164	0.008	0.083
	Number of bungalow households	0.461	−0.437	0.616	−0.192	0.152	0.214	−0.028	−0.117
	Number of concrete structure households	0.842	0.257	0.036	0.212	0.125	−0.15	−0.067	−0.046
	Number of brick structure households	0.460	−0.329	0.486	−0.037	−0.153	0.332	0.07	0.043
	Number of wooden structure households	−0.140	−0.351	0.003	−0.175	−0.218	−0.016	−0.072	−0.589
	Housing built in the 70s	−0.033	−0.249	0.213	−0.241	0.446	0.306	0.106	−0.119
	Housing built in the 80s	0.083	0.248	−0.018	−0.112	−0.12	0.063	0.004	−0.045
	Housing built in the 90s	0.618	0.218	0.04	0.119	−0.039	0.297	−0.059	−0.129
	Housing built after 2000	0.937	−0.058	0.022	−0.071	0.131	0.047	0.011	0.125
	Housing built after 2010	0.232	−0.104	0.638	0.41	−0.148	−0.239	−0.025	−0.183
	Forest land area	−0.05	0.112	−0.086	0.173	−0.024	−0.031	0.876	0.039
	Waste slope area	−0.231	−0.143	0.058	−0.156	0.037	0.017	0.635	0.225
Social dimension	Local registered residence population	0.833	−0.131	0.488	0.141	0.03	0.035	−0.009	−0.078
	Migrant population	0.130	0.917	−0.127	−0.051	−0.014	0.179	0.011	0.002
	Outgoing employed population	0.317	−0.305	0.582	−0.193	0.139	0.218	−0.012	−0.216
	Population employed in the village	0.590	0.282	0.322	0.314	−0.161	−0.099	0.316	−0.022
	Sex ratio	−0.582	0.073	−0.168	0.029	0.348	0.034	−0.301	−0.144
	Population under 18 years old	0.695	−0.171	0.003	0.274	0.016	−0.181	−0.343	−0.069
	Population of working age	0.607	−0.089	0.713	0.162	−0.008	0.08	0.152	−0.088
	Population over 60 years old	0.875	−0.11	0.088	−0.065	0.093	0.067	−0.095	−0.021
	Total number of households	0.925	0.018	0.292	0.146	0.009	0.068	−0.02	−0.042
	Per household population	−0.572	−0.555	0.211	−0.056	−0.031	−0.105	0.024	0.029
	Poor households in villages	0.013	−0.293	0.758	−0.165	−0.071	0.183	−0.065	−0.069
	Area of requisitioned land	0.736	0.448	−0.32	−0.006	−0.092	−0.027	0.043	0.107
	Area of leased land	−0.143	−0.03	−0.011	−0.002	−0.034	0.084	−0.041	−0.09
	Population employed in scenic areas	−0.077	0.06	−0.082	−0.2	−0.135	−0.104	0.089	0.86
	Number of agritainment households	−0.119	0.924	−0.007	0.142	−0.049	−0.083	−0.035	−0.006
	Number of commodity sales households	0.239	0.808	−0.142	−0.127	0.052	−0.113	−0.178	−0.023
	Number of catering business households	0.091	−0.081	0.025	−0.036	−0.095	0.01	−0.138	−0.357
	Number of stalls	−0.079	0.833	−0.237	−0.04	−0.101	−0.1	−0.06	0.264
	Number of handicraft production households	−0.012	0.945	−0.146	−0.089	−0.017	−0.005	0.09	0.001
	Number of tour guides or drivers	0.267	0.596	−0.393	−0.162	−0.106	−0.045	0.188	0.321
	Number of transportation logistics households	0.257	0.017	−0.224	0.485	0.648	0.078	−0.162	−0.061

The indicators with relatively high loads in bold.

).

(2)

Spatial distribution of principal components scores

The spatial distributions of the scores of the eight principal components are shown in Figure 3.

(I)

The land acquisition and resettlement factor. This principal component reflects the impact of land acquisition and resettlement on rural development. In the spatial dimension, the area of requisitioned land is large (0.736), and the per capita cultivated land area is limited (−0.478). The housing conditions of the villagers are at a relatively better level, and most households are two-story buildings (0.547) with a concrete structure (0.842). In the social dimension, the registered residence population (0.833) is larger than the migrant population. In order to obtain more resettlement compensation, household divisions are common, so the number of households is large (0.925), and the per-household population is small (−0.572). On the one hand, the villages with a high score for this principal component are mostly distributed around scenic spots and museums. On the other hand, affected by urbanization, they are mostly distributed on the edges of the heritage sites.

(II)

The tourism driving factor. This principal component reflects the driving effect of tourism utilization on heritage villages. In the spatial dimension, although the per capita cultivated land area is limited (−0.482), there are a large number of collective service enterprises (0.937) and individual tourism enterprises (0.901). The degree of space capitalization is high, most of the households are two-story buildings (0.513), and the number of village parking lots is also large (0.808). In the social dimension, the number of migrant populations in the villages is large (0.917). The villagers are mostly engaged in agritainment (0.924), commodity sales (0.808), handicraft production (0.945), stall sales (0.833), tour guide or driving (0.596), and other livelihood activities. In terms of spatial distribution, villages with a high score for this principal component are mostly located around scenic spots and museums.

(III)

The restriction factor of heritage protection. This principal component reflects the restrictions and impacts of cultural heritage protection on the way of life and production in the surrounding villages. In the spatial dimension, there are a number of limitations on agricultural production, and the planting area of grain crops (0.750) is larger than that of cash crops. The housing conditions of the residents are relatively low, and most of the households are bungalows (0.616) with brick structures (0.486). In the social dimension, the working-age population is large, but the proportion of poor households is high (0.758). Most residents go out to work for employment (0.582). In terms of spatial distribution, villages with a high score for this principal component are mostly located in protected areas and far away from scenic spots and major traffic lines.

(IV)

The agricultural commercialization factor. This principal component reflects the level of agricultural commercialization, which means the formation of an agricultural–industrial chain relying on agricultural production, agricultural product processing, packaging, and delivery. In the spatial dimension, there are a large number of agricultural product processing enterprises (0.713) and logistics enterprises (0.508) in the villages. In the social dimension, the proportion of the population engaged in the transportation and logistics industry is relatively high (0.485). Villages with a high score for this principal component are mostly distributed around the main traffic lines at heritage sites.

(V)

The rural industrialization factor. This principal component reflects the development level of rural industrialization. In the spatial dimension, there are a large number of collective industrial enterprises (0.931) and individual manufacturing industries (0.675). In the social dimension, the proportion of villagers engaged in the logistics industry is high (0.648). Villages with a high score for this principal component are mostly located at the edges of heritage sites and close to the traffic trunk roads in these areas.

(VI)

The natural resource development factor. This principal component reflects the dependence of rural industries on natural resources. Rural enterprises cover a large area (0.715), and most of them are mining enterprises (0.867). Villages with a high score for this principal component are distributed around mountains in which the tombs of emperors are placed.

(VII)

The ecological factor. This principal component reflects the ecological conditions and afforestation status. There are large areas of forest land (0.876) and wasteland (0.635). Villages with a high score for this principal component are mainly distributed in areas with obvious topographic relief, and they have superior ecological resource conditions or large-scale afforestation due to cultural heritage protection.

(VIII)

The scenic spot employment factor. This principal component reflects the large number of villagers employed in scenic spots, including security staff, support staff, builders, and gardeners. Villages with a high score for this principal component are located around museums, heritage parks, and other scenic spots, but they are not close to their entrances or exits.

3.1.2. Evolution Characteristics of Principal Components of TFRA from 2010 to 2020

(1)

Evolution characteristics of principal components

This research identified eight principal components of TFRA in 2010, with a cumulative variance contribution rate of 73.5%. The eight principal components were named as follows: (I) The tourism driving factor (21.0%): This principal component indicates that there are large numbers of migrant populations (0.941), commodity sellers (0.803), tour guides (0.708), agritainment households (0.976), individual tourism enterprises (0.881), and collective service enterprises (0.815) in the villages. The majority of village buildings are two-story buildings (0.518). (II) The land acquisition factor (20.7%): This principal component indicates that the area of requisitioned land (0.582) and the homestead area (0.611) are large, but the per household population is small (−0.500), and the population employed in the villages (0.803) is large. (III) The restriction factor of heritage protection (7.7%): This principal component indicates that the area of requisitioned land (0.551) is large; therefore, the per capita cultivated land area (−0.655) is small. The planting area of grain crops in the villages is small (−0.816), and the main residential buildings are bungalows (0.576). (IV) The rural industrialization factor (7.2%): This principal component indicates that there is a large number of collective industrial enterprises (0.657), agricultural product processing enterprises (0.790), and packaging logistics industries (0.759). The proportion of villagers engaged in the logistics industry (0.784) is high. (V) The agricultural and forestry development factor (5.4%): This principal component indicates that there are a large number of agricultural and forestry enterprises in the villages (0.648) and large areas of land occupied by enterprises (0.770) and leased land (0.77). (VI) The economic crop production factor (5.3%): This principal component indicates that there are large areas of land used for the planting of cash crops (0.674) and leased land (0.639). (Ⅶ) The population outflow factor (4.4%): This principal component indicates that the outgoing employed population is large (0.677). (VIII) The ecological factor (4.3%): This principal component indicates that there is a large area of forest land (0.749). By comparing the principal components and their spatial distributions in 2010 and 2020, the following evolution features are discovered:

Firstly, heritage display and utilization have a persistent impact on TFRA. The tourism driving factor, the land acquisition factor, and the ecological factor have been principal components since 2010, with two of them having the highest variance contribution rate. This phenomenon is mainly due to the development of tourism, the construction of scenic spots, and the environmental renovation of heritage sites.

Secondly, heritage display and utilization improved relevant industrial chains. Over the past decade, the economic crop production factor and the agricultural and forestry development factor gradually evolved into the agricultural commercialization factor. The economic crop production factor and the agricultural and forestry development factor reflect economic crop cultivation, agricultural and forestry enterprises, and the local labor force in 2010. After years of evolution, the agricultural commercialization factor now includes agricultural and forestry enterprises, agricultural product processing, packaging and logistics enterprises, and sales operators. This process reflects the cultural value spillover effect of tourism development on agricultural production activities, thereby promoting the connection between agriculture and tourism to form a complete industrial chain.

Finally, the restrictive effect of heritage protection on TFRA gradually weakened. The restriction factor of heritage protection existed in both 2010 and 2020, but its variance contribution rate decreased. On the one hand, the population outflow factor caused by limited industrial and agricultural production disappeared. The scenic spot employment factor appeared in 2020. On the other hand, the tourism driving factor spread from the scenic area to the surrounding areas in terms of spatial distribution, whereas the spatial distribution of the rural industrialization factor decreased in 2020.

(2)

Evolution of social–spatial differentiation indices

The differentiation indices can reflect the spatial differentiation of various indicators relative to the absolute equilibrium distribution. The differentiation indices of the indicators related to tourism and agricultural industrialization decreased from 2010 to 2020 (Figure 4). On the one hand, the spatial differentiation indices of the indicators related to tourism development, such as the number of tour guides, the number of stall holders, the number of households, the number of handicraft production households, the proportion of the population employed in scenic spots, and the number of migrant populations, gradually decreased; this phenomenon indicates that heritage display and utilization drove the development of the tourism industry in a large region. On the other hand, the spatial differentiation indices related to the agricultural industry indicators, such as the numbers of packaging logistics enterprises, agricultural and forestry enterprises, and agricultural product processing enterprises, gradually decreased, which means that heritage tourism drove the expansion of modern agriculture and sightseeing agriculture in a large region.

The spatial differentiation indices of some indicators increased, including the proportion of poor rural households, the number of mining enterprises, and the area of food crops (Figure 4). The increase in the differentiation indices of the proportion of poor households indicates that the gap between the rich and the poor increased from 2010 to 2020. The intensification of the differentiation indices related to industrial production is mainly affected by the government’s closure of mining enterprises at heritage sites, causing polarization effects in industrial production. The increase in the differentiation indices related to food crop cultivation is mainly affected by the development of tourism. Since 2010, large numbers of villages have planted cash crops and promoted agricultural commercialization, which has led to the uneven spatial planting of food crops.

Some differentiation indices decreased at the Qin Shihuang Mausoleum heritage site (Figure 4a)and the Tang Qianling Mausoleum heritage site(Figure 4b) but increased at the Tang Qiaoling Mausoleum heritage site(Figure 4c), such as the proportion of the population engaged in tourism or catering businesses, manufacturing enterprises, and agricultural product processing enterprises. Mainly, this is because the display and utilization of Qin Shihuang Mausoleum and Tang Qianling Mausoleum started early, and tourism-related industries developed maturely with a balanced spatial distribution. The display and utilization of the Tang Qiaoling Mausoleum began only over a decade ago, so only a small number of villages have realized the transformation to tourism development. Development resources are concentrated in a small number of villages, so the differentiation is obvious, resulting in a polarization stage of development.

3.2. Spatial Structure and Evolution of TFRA at Cultural Heritage Sites

3.2.1. Spatial Structure Characteristics of TFRA in 2020

A matrix of 36 × 8 was established based on the scores of the eight principal components of the 36 villages in 2020. The systematic clustering method was utilized to classify these sample villages, and six types of villages were identified by repeatedly comparing the dendrograms. The correlation coefficients (γ_ij) between the eight principal components of each type of village were calculated, so the correlation coefficient matrix was obtained. The mean value of the correlation coefficient represented the main functional characteristics of each type of village. The calculation formula for the mean value of the correlation coefficient is as follows:

$$\overline{R}=\frac{{\displaystyle {\sum }_i{\gamma }_{ij}}}{K-1}$$

(2)

where ?R is the mean value of the correlation coefficient, K is the number of principal components (the number in this study was 8), and γ_ij is the correlation coefficient between the principal components. The two principal components with the highest correlations with the others were selected to define the functional characteristics of each type of rural area. The classification results are shown in

Table 3. Correlation coefficients of principal components in each functional area.

Type of Rural Area	Principal Components
	I	II	III	IV	V	VI	VII	VIII
Tourism service area	0.143	0.174	−0.130	−0.291	0.137	0.096	−0.019	−0.184
Agricultural tourism area	0.259	0.582	0.488	0.523	0.481	0.372	0.202	−0.081
Labor supply area	−0.477	−0.438	0.343	−0.312	−0.249	−0.042	−0.353	0.235
Labor outflow area	0.181	0.157	0.209	0.117	−0.077	−0.413	0.088	0.145
Resettlement area	0.424	−0.013	0.411	−0.008	−0.698	0.306	0.352	0.358
Rural industrialized areas	0.006	0.008	0.181	0.047	−0.078	0.172	−0.187	−0.002

, and the spatial distribution of the classification is shown in Figure 5.

The first category is defined as tourism service areas. This is because the two principal components with the highest average correlation coefficients with the other principal components of the villages are (I) the land acquisition and resettlement factor (0.143) and (II) the tourism driving factor (0.174). The villages of this function type are mainly distributed near the entrances of museums and scenic spots. On the one hand, these villages are located in the protection zone, with a high frequency and a large area of land acquisition, which greatly interferes with traditional agricultural production, forcing the development and transformation of traditional agricultural livelihood models. On the other hand, because these villages are close to the entrances of scenic spots, they have unique advantages in developing rural tourism and souvenir production and sales. Therefore, this has led to the transformation of residents’ production and lifestyles towards tourism services.

The second category is defined as agricultural tourism areas. This is because the two principal components with the highest average correlation coefficients with the other components of the villages are (II) the tourism driving factor (0.582) and (IV) the agricultural commercialization factor (0.523). The villages of this function type are distributed around scenic areas, relying on heritage tourism to realize rural agricultural development. Most rural enterprises are engaged in sightseeing agriculture, modern agriculture, and the packaging and processing of agricultural products.

The third category is defined as the labor supply area of scenic spots. This is because the two principal components with the highest average correlation coefficients are (III) the restriction factor of heritage protection (0.343) and (IV) the scenic spot employment factor (0.235). These villages are located in the protection zone and are restricted by heritage protection without any industries. A large number of surplus laborers in the villages are employed due to the construction and afforestation of scenic spots.

The fourth category is defined as labor outflow areas. This is because the two principal components with the highest average correlation coefficients are (III) the restriction factor of heritage protection (0.209) and (I) the land acquisition and resettlement factor (0.181). The villages of this function type are far away from scenic areas and within the protection zone, which is restricted by heritage protection and cannot benefit from any positive externalities of tourism development. The labor force works all year round. This type of area has the largest number of villages, and the poverty problem of heritage sites mainly occurs in this area.

The fifth category is defined as relocation and resettlement areas. This is because the two principal components with the highest average correlation coefficients with the other principal components of the villages are (I) the land acquisition and resettlement factor (0.424) and (III) the restriction factor of heritage protection (0.411). Villages of this type are mostly located at the edges of the protection zone. Although the living conditions were improved after resettlement, the proportion of residents who go out to work is relatively high.

The sixth category is defined as rural industrialized areas. This is because the two principal components with the highest average correlation coefficients with the other principal components of the villages are (III) the restriction factor of heritage protection (0.181) and (VI) the natural resource development factor (0.172). Most of these villages are located in the controlled construction zone and the environmental coordination zone outside the protected area.

3.2.2. Evolution of TFRA from 2010 to 2020

In this study, the same method was used to divide the functional areas in 2010. When comparing the models of the functional structure in 2010 and 2020 (Figure 6), it was found that the main function types of TFRA at the heritage sites barely changed, and the characteristics of the evolution over the past decade are reflected in the following aspects:

(1)

The scales of tourism service areas and labor supply areas of scenic spots have gradually expanded since 2010 because of the development of heritage tourism. These two types of functional areas were distributed around scenic areas or museums in 2010, and since then, they have gradually formed an enclosure around scenic areas.

(2)

Cash crop production areas have evolved into agricultural tourism areas. This transformation is related to both the development of tourism and the construction of tourist roads. The leading industries in these villages gradually developed from cash crop cultivation to agricultural sightseeing, planting, logistics, packaging, and processing, which form a complete industrial chain.

(3)

Grain production areas have evolved into labor supply areas of scenic spots and labor outflow areas. The livelihood mode of residents has shifted from grain cultivation to employment in scenic areas or in the city. On the one hand, due to the “scissors gap” in the income between grain production and migrant workers, coupled with the restrictions on heritage protection, agricultural production is low, and residents choose to work outside in pursuit of a higher income. On the other hand, China’s large-scale urbanization and construction of scenic spots demand a large amount of rural surplus labor.

(4)

The scale of rural industrialized areas has decreased since 2010. Under the influence of the government’s heritage protection and environmental protection policies, the cement factories, lime factories, and brick factories in and around the heritage sites have been closed down, and the development of industrial production has stagnated.

(5)

Relocation and resettlement areas have been embedded in the heritage sites. The construction activities of scenic spots involved large-scale land acquisition, relocation, and resettlement, and a large number of resettlement houses for villagers have also been constructed during this period. This process is the impact of government power intervention on TFRA.

4. Discussion

4.1. Spatial Structure of TFRA at Heritage Sites

This study combines the GIS spatial analysis method with socioeconomic indicators and classifies spatial functions after defining the main attributes of each village through factor ecological analysis, which is a supplement to the land cover recognition spatial function. The results indicate that the spatial structure of TFRA at heritage sites shows the spatial feature of a concentric circle with three layers (Figure 7). ① The inner layer is not only the area within the protection zone but also the area where scenic spots or museums are located. The spatial functions of this layer include tourism service areas and agricultural tourism areas. The relevant analysis of land use indicates that the impact of artificial construction is relatively strong within 1 km of the buffer zone of the heritage site, and the complexity and diversity of the land cover are relatively high [11]. After combining socioeconomic indicators, it has been found that these spatial constructions have led to the development of rural tourism and agricultural tourism and have driven the development of rural service industries and the sale of local agricultural products. ② The middle circle layer is the area of the controlled construction zone, and this is where the villages with the function of agricultural production and surplus labor supply areas are distributed. The governments lock in land uses and preferences of heritage sites or simply change their priorities to protection or tourism utilization of cultural heritage [44]. The land use or land cover analysis shows that the most extensive land cover is occupied by agricultural areas within a buffer size of 10 km [45]. The industrial development of this region is restricted, and the region cannot benefit from the spillover effect of heritage tourism. The residents proximal to the protected areas have lost the opportunity cost of their own development for heritage protection [46]. The results show that the middle layer of the heritage site is an area with a high incidence of poverty, and residents choose to work outside or find employment in scenic areas. ③ There are many villages in the outer layer that reflect the characteristics of rural industrialization. This area is less affected by the restrictions of protection zoning, and some villages have accomplished the development of rural industrialization, relying on the advantages of traffic location.

The hierarchical spatial feature of TFRA is the result of heritage protection zoning. The protection zoning takes the relic noumenon as the center and delimits the protection zone, the controlled construction zone, and the environmental coordination zone from the inside to the outside. Different levels of control requirements are implemented in different regions in order to coordinate the contradiction between heritage protection and regional development. The functional structure forms a concentric circle pattern of “service industry–surplus labor supply (agriculture)–rural industry” from the inside to the outside because of the circle control of protection zoning.

4.2. Traffic Routes and Value Spillover Effect at Heritage Sites

Museums, scenic spots, and heritage parks, as cultural transmission carriers, convert the cultural value into social and economic value through tourism utilization, and the value spillover has the characteristic of distance attenuation. The villages close to scenic spots with an average distance of 1.4 km are the most affected by the positive externalities of tourism development, and they have developed catering, accommodation, agritainment, and other related tourism industries. The villages with an average distance of 2.4 km from scenic spots have the characteristic of agricultural commercialization, and they are close to the main roads of heritage areas. These villages have realized the accumulation of original capital, relying on stalls selling local agricultural specialties. Since then, they have attracted a large number of migrants and gradually formed a complete industrial chain, including the production, packaging, and sales of agricultural products. Villages with an average distance of 4.2 km from scenic spots are the least affected by the positive externalities of tourism development, but they have developed industries and extractive industries which have little relevance to heritage tourism utilization.

The construction of roads in heritage sites is a controversial issue. In studies on cultural heritage management and monitoring, it is commonly believed that the local road network was an anthropogenic hazard taken into account [12]. The construction of roads, which leads to the advantages and disadvantages of economic development on the protection of cultural relics, brings convenience and also derives many contradictions and destruction [47]. This study found that high-value-added function areas are mostly distributed along the main roads of the heritage sites. A total of 85% of the villages in tourism service areas and 80% of the villages in agricultural tourism areas are located around the main traffic lines. The value spillover generated by the utilization of heritage radiates outward from the traffic line. Compared with other functional areas in the same layer, these spatial functions have a strong external connection and tourism dependence.

4.3. The Driving Role of Capital Proliferation in the Evolution of TFRA

The evolution of TFRA can be seen to be the result of the flow and transformation of production factors, such as capital and labor. The development of this special area is influenced by heritage protection and tourism utilization, capital investment involves different stakeholder groups and power games [48], so the flow and transformation of capital and labor have their own particularities. Land acquisition for heritage site development and heritage protection policies have an impact on the use of space and impose restrictions on agricultural production, and this has separated farmers from cultivated land and generated a large amount of surplus labor. The capital will inevitably digest surplus labor and seek labor-intensive production methods. The construction of museums and the production of tourist artifacts absorb surplus labor from villages around scenic spots, achieving the accumulation of the original capital in the villages. Tourism development has also increased the added cultural value of cash crops, such as local pomegranates, persimmons, and grapes, causing adjustments in agricultural production and sales patterns in some villages, reflecting the characteristics of agricultural commercialization. According to David Harvey’s capital cycle theory, the capital logic of the evolution process is summarized as follows (Figure 8):

(1)

Capital investment in the production of consumer goods. The productive input of capital into consumer goods, such as agricultural production, industrial production, tourism souvenir production, and heritage protection policies, and the optimal allocation choice of capital led to changes in the production modes of villages and their spatial differentiation. Since then, due to homogeneous competition and the overproduction of consumer goods, capital has begun to be invested in space construction to resolve the crisis of overproduction and to provide convenience for production and consumption.

(2)

Capital investment in spatial construction. In this round of the capital cycle, some villages built roads, warehouses, and factories to attract investment from fruit wholesalers, agricultural processing plants, and packaging plants in order to absorb excess agricultural production, thereby forming an agricultural–industrial chain. Some villages carried out rural residential renovation, landscaping, parking lot construction, stall construction, and market construction to facilitate catering operations and souvenir sales. The essence of this process is to maximize benefits and the investment of capital into space construction, and it embodies the characteristics of spatial capitalization.

(3)

Capital investment in social and cultural fields. The capital was invested in cultural services, productive services, and living services to resolve the crisis caused by spatial overproduction. For the purpose of cultural and environmental protection, some industrial enterprises stopped production, resulting in the contraction of rural industrialized areas. The development of the tourism industry requires higher standards for cultural activities and tourism experiences. The management rights of scenic spots were transferred from private to state-owned, and the standardized operation and construction of scenic spots required more labor, resulting in an increase in the scope of labor supply areas.

4.4. Coordination of Social and Spatial Development at Heritage Sites

According to the analysis results, there are differences in the development of each village surrounding the heritage sites, which also contribute to the gap between the rich and the poor. Determining how to integrate regional resources and achieve interaction among functional areas is the key to achieving balanced spatial development.

Firstly, the implementation of differentiated development orientation in each village is a prerequisite for the sustainable development of heritage sites. The management and control of heritage protection vary from village to village, and the resources and location conditions for the development of each village are also different. Therefore, differentiated development strategies of villages should be formulated according to local conditions. In previous conventional planning, all villages were positioned to develop rural tourism, which inevitably led to homogeneous competition.

Secondly, the smooth flow of cultural value spillover channels must be ensured. Transportation facilities are important intermediaries for the spillover and dissemination of heritage values, and they are also significant factors in promoting the transformation of rural development at heritage sites. The construction of tourist roads drove the development of tourism services and agricultural tourism industries in villages along the traffic line, and it also promoted the commercialization of agriculture. Some villages along the roads also achieved rural industrialization. The construction of traffic systems is of great significance for the value spillover and dissemination of cultural resources and the realization of industrial linkage.

Finally, implement a multi-level, multi-node, differentiated resource development and utilization model. Currently, the development of heritage sites excessively relies on the spillover effect of the core of site displays and utilization (scenic spots, museums, etc.), resulting in the low-end homogenization of rural industries. Moreover, the forms of participation are mostly low-tech jobs, such as agritainment, tour guides, tourist drivers, handicraft manufacturing, and sales, which also lead to homogeneous competition and overproduction issues. In the future, it is necessary to upgrade from “relying on the core” to “creating the core” to achieve a multi-level and multi-node spatial development model, promote the spatial connection and radiation of various functional areas, ensure that the spillover value of heritage resources can be fully transformed, and achieve the sustainable development of regional rural economy and society.

5. Conclusions

An analysis of the structure and evolution characteristics of TFRA is an important basis for the implementation of the Rural Revitalization Strategy in China. Affected by the dual factors of cultural heritage protection and tourism utilization, the interplay between heritage protection departments, urban construction departments, tourism enterprises, and local communities has resulted in the particularity and complexity of TFRA at heritage sites. Estimating the TFRA at heritage sites from the perspective of social space is of great significance for adjusting the spatial layout, optimizing the utilization of heritage resources and spatial resources, and solving the problem of the uneven spatial development of heritage sites. According to the research conclusions, there are objective social differences at heritage sites. That is, the surrounding villages have different abilities to obtain resources, which has caused an obvious gap between the rich and the poor.

(1)

Through a comprehensive analysis of society and space, it was found that the rural areas of heritage sites have obvious spatial differentiation characteristics and present six major functional areas. Due to the development of the tourism industry and the expansion of scenic spots, the scales of tourism service areas and labor supply areas increased. The cash crop production areas evolved into agricultural tourism areas. This transformation is related to both the development of tourism and the construction of tourist roads. The scale of rural industrialized areas was reduced because of heritage protection policies.

(2)

The social–spatial differentiation indices related to tourism and agricultural industrialization decreased over the past decade. This phenomenon indicates that heritage display and utilization drove the development of the tourism industry in a large region, so the regional balance of tourism development improved. The spatial differentiation indices concerning poor rural households, areas of food crops, etc., increased, which indicates that the gap between the rich and the poor is gradually increasing.

(3)

The TFRA at heritage sites presents the spatial characteristic of a concentric circle because of the circular gradient control of heritage protection zoning. The protection zone, the controlled construction zone, and the environmental coordination zone, which are designated from the inside out, gradually slowed down the control intensity of industrial and agricultural production activities. Thus, the functional structure formed a concentric circle pattern of “service industry–surplus labor supply (agriculture)–rural industry” from the inside to the outside.

(4)

The high-value-added functional space of heritage sites is distributed along the transportation line, forming a concentric circle fan-shaped regional functional pattern. The value spillovers generated by tourism use radiate outward through transportation lines, thereby driving the development and transformation of villages along the line. The tourism service area, the tourism agriculture area, and the villages in rural industrialized areas are mostly located around the tourist roads connected to scenic spots.

(5)

The inherent demand for capital proliferation is the fundamental driving force for the differentiation and evolution of TFRA at heritage sites. The selection of the optimal investment allocation of capital under the heritage protection system led to regional functional differentiation. The evolution of TFRA can be seen as being the result of the flow and transformation of production factors, such as capital and labor. The phased investment of capital into consumer goods production, spatial construction, and cultural service industries led to the evolution of regional functions.