Multifunctional Identification and Transition Path of Rural Homesteads: A Case Study of Jilin Province

Abstract

In the context of rural revitalization, identifying the functional characteristics of rural homesteads and clarifying the relationship among various functions are important scientific issues for the transformation of homestead utilization. Taking Jilin Province as an example, this paper analyzes the problems existing in rural homestead utilization from the aspects of quantitative characteristics, human–land matching degree, and the current situation of idle homesteads. An evaluation index system is constructed to measure the functional values of homesteads to identify the advantageous functions of homesteads. The results are as follows: (1) in some areas of the Jilin Province, the per capita homestead area is relatively large, with a high vacancy rate, and there is a phenomenon of inefficient use of homesteads, (2) according to the calculation results of the homestead functional index, the overall performance of the four functions of rural homesteads is in the order of living function > security function > production function > asset function, indicating that traditional living function remains predominant in the study area, (3) based on the relationship between the comprehensiveness and coordination of the four functions of homesteads, villages are classified into “moderate optimization area”, “key improvement area”, “collaborative optimization area”, and “potential improvement area”.

1. Introduction

Today, approximately 7.2 billion people inhabit Earth and, by 2050, this number will have risen to around nine billion, of which about 70% will be living in cities [1,2]. Urban development often comes at the expense of rural areas [3,4,5]. At the same time, rural decline is an indisputable fact and a global issue [6,7]. Many studies have highlighted the phenomenon of rural decline in parts of the developed world, summarized as a loss of agricultural employment leading to a decline in the number and size of rural settlements [8,9]. Since the reform and opening up, China’s rural economic and social development has experienced drastic transformations and reconstructions, leading to many issues such as “rapid non-agriculturalization of agricultural land”, “inefficient construction land use”, and “hollowing out of homesteads”, which have brought serious challenges to the high-quality and sustainable development of rural area [10,11]. The 19th National Congress of the Communist Party of China innovatively proposed that socialism with Chinese characteristics has entered a new era, emphasizing the implementation of the rural revitalization strategy to address the prominent issues of unbalanced urban–rural development and inadequate rural development, and to make up for the shortcomings of rural areas in view of building a moderately prosperous society in all respects [12,13,14]. In the implementation of the rural revitalization strategy, how to innovate the land management system to effectively promote urban–rural integration is a pressing issue and an important topic of multidisciplinary research to meet national strategic needs [3,15]. The homestead is a multifunctional composite space on which the rural population depends for survival and development, and it is the core of the interaction and coupling of human–land relationships in rural regional systems [16,17,18], with its functional attributes exhibiting diversity based on human needs [19,20].

In the early 1990s, Mather, a geographer at the University of Aberdeen in Scotland, pioneered the forest transition (forest transition or forest-area transition) hypothesis [21]. The mechanism of forest transformation has not yet been fully explained by the academic community. Grainger, a geographer from the University of Leeds, proposed the concept of land use transformation (land use transition) from the perspective of national land use form (national land use morphology) change inspired by Mather in 1995 [22]. Longhuou, DeFries, Lambin, and other relevant scholars at home and abroad have developed the theories of land use transformation [23,24].From the perspective of the development history of land use classification in China, the Land Use Classification (GB/T21010-2007) defines rural homestead land as land used for residential use in rural areas, but does not clearly define its connotation and scope [25], CurrentThe Classification of Land Use Status (GB/T 21010-2017) defines homestead land as land for rural living [26]. Scholars have different views on the connotation of homesteads. Long et al. defined rural homesteads in both a broad and a narrow sense, suggesting that, broadly, rural homesteads refer to the land used by rural residents for living and life, including housing land and necessary auxiliary facilities land, which is roughly equivalent to rural residential land in land use change surveys. Narrowly, rural homesteads refer to the land used by rural residents for building houses [27,28]. Chen et al. believe that rural homesteads are lands designated for households to meet their living needs and engage in household sideline production, including construction land and activity space [29]. The acquisition of rural homesteads is a basic right of farmers, and the rural homesteads system is an important supporting system for the rural revitalization strategy [30]. Based on previous research results, this paper believes that rural homesteads are courtyard lands used by farmers for living, with clear ownership characteristics, playing multiple roles in rural life, and having multifunctional characteristics. Therefore, correctly understanding and rationally utilizing homestead functions is of great significance for advancing the improvement of the homestead system and safeguarding farmers’ rights and interests.

The utilization of rural homesteads has always received attention from scholars, and the discussion on homestead functions is gradually increasing. Homestead functions are the collection of functions, effects, performances, and uses exhibited by homesteads during household use in a certain village environment [31,32]. There is no unified standard for the division of homestead functions in academia, with most scholars first focusing on the basic functions of homesteads. For example, Song et al. divided homestead functions into living functions and production functions [33,34,35]. Lin Chao proposed that the political function of the homestead is basically unchanged, the social security function is gradually weakened, and the economic property function is gradually enhanced [34]. Zhang Bailin et al. constructed an analytical framework for the evolution of rural homestead function and used a combination of participatory rural assessment (eRA), GIS, and remote sensing images to take Hetaoyuan Village, Yishui County, Shandong Province as an example for empirical evidence. The results show that the agricultural production function has always been the dominant production function in rural settlements, but there are different contents at different stages [35]. Zhai et al. divided homestead functions into social security functions, production functions, and asset appreciation functions [36,37]. On this basis, some other scholars have paid attention to more functional performances, such as Ma et al., who added the potential function, taking the Pinggu area of Beijing as an example, and Ma Wenqiu, who proposed that the homestead has evolved from a single residential function to a comprehensive function such as residential, industrial production, and commercial services [38]. Others have focused on the natural education function [39], value-added function [40,41], processing function, sightseeing function, leisure function, and health function [42]. Function is the core of the utilization of the homestead; therefore, in recent years, scholars have increasingly explored the direction of rural homestead system reform from the perspective of functional transition under the background of rural revitalization [43,44,45,46]. Therefore, research on homestead functions is the basis for optimizing homestead transition.

Based on the above research results, this paper classifies the functions of homesteads into two main categories: social functions and economic functions, with social functions mainly characterized as living functions and security functions, and economic functions mainly characterized as production functions and asset functions. Based on the current situation of the utilization of homesteads, this study identifies the functional performance and advantageous functions of homesteads, classifies villages according to the comprehensive performance and interrelationships of homestead multifunctionality, and puts forward targeted proposals for rural optimization and transformation.

2. Data and Methodology

2.1. Study Area

The Jilin Province is located in the central part of Northeast China, with the Changbai Mountainous Area in the east, Songliao Plain in the middle, and Horqin Grassland in the west, roughly presenting the land use pattern of forest in the east, agriculture in the middle, and pasture in the west, which is shown in Figure 1. The province has abundant arable land and ecological resources such as forests and grasslands, making it an important grain-producing area and commodity grain base in China, as well as a crucial window for opening up to the north and a central hub for cooperation in the Northeast Asia region. As a major agricultural province in China, the Jilin Province plays a pivotal role in agricultural and rural development, while, in recent years, the low standard of production and living in rural areas and the serious loss of rural talent have been prominent. The seventh national census shows that there is a serious exodus of people from the rural areas of the Jilin Province and a lack of vitality in the main body of rural development; in terms of land use, the rural area of the Jilin Province is rich in collective land resources for construction, but the overall level of land use in the rural areas is on the low side due to the restrictions on the way land can be used.

2.2. Data

This study carried out pre-processing work such as filling in missing data, data standardization, and statistical analysis of data on the population of each region through the collection of the China County Statistical Yearbook, Jilin Statistical Yearbook, and municipal and state yearbooks. Moreover, based on the data from the Third Land Survey of Jilin Province, this study compiled the characteristics of the status quo of rural homesteads and other land use; the data of typical villages’ homesteads come from field surveys. Electricity consumption data come from the agricultural power sector.We used ArcGis 10.6 to map the study area and the Theil index.

2.3. Methodology

2.3.1. Characteristics of Rural Homestead Utilization in Jilin

(1)

Per capita homestead area—current utilization situation

The current status of homestead utilization in the Jilin Province was measured by calculating the per capita homestead area in the Jilin Province. The formula was as follows:

$$\mathrm{P}\mathrm{C}\mathrm{R}\mathrm{S}\mathrm{A}={\displaystyle \frac{RSA}{RP}}$$

(1)

where RSA is the rural homestead area and RP is the rural population size.

(2)

Theil index—human–land match

The Theil index was used to an analyze the layout of the population and homesteads in the Jilin Province. The formula was as follows:

$$T=T_w+T_b$$

(2)

$$T_i={\sum }_{i=1}^n{\displaystyle \frac{R{P}_i}{RP}}\times \mathit{ln}({\displaystyle \frac{{RSA}_i}{RSA}})$$

(3)

$$T_w=\sum _{i=1}^n{\displaystyle \frac{{RP}_i}{RP}}\times T_i$$

(4)

$$T_b={\sum }_{i=1}^n{\displaystyle \frac{{RP}_i}{RP}}\times \mathit{ln}({\displaystyle \frac{{RP}_i}{RP}}/{\displaystyle \frac{{RSA}_i}{RSA}})$$

(5)

$$R_b={\displaystyle \frac{T_b}{T}}$$

(6)

In the formula, T is the overall Theil index of the Jilin Province, ${\mathrm{T}}_{\mathrm{b}}$ and ${\mathrm{T}}_{\mathrm{w}}$ denote inter-regional and intra-regional differences, respectively, ${\mathrm{T}}_{\mathrm{i}}$ denotes the Theil index of each city, ${\mathrm{R}\mathrm{P}}_{\mathrm{i}}$ and RP represent the rural population of each county and city, respectively, ${\mathrm{R}\mathrm{S}\mathrm{A}}_{\mathrm{i}}$ and RSA represent the rural homestead area of each county and city, respectively, and ${\mathrm{R}}_{\mathrm{b}}$ denotes the inter-group contribution to the T variable. The Theil index is non-negative, and a smaller value indicates less disparity. When the RP share equals the share of RSA, the ratio inside the logarithm (i.e., the share ratio) equals one, resulting in a logarithmic value of zero. Consequently, the Theil index becomes zero, indicating no regional differences. The Theil index ranges from 0 to 1; values closer to zero signify a more equitable distribution of the population and the land, while values closer to one indicate greater inequality in the human–land distribution.

(3)

Homestead idle rate—idle condition

According to the statistics related to “one house, one electricity” in rural areas of the power department, we define vacant farm buildings by using the standard of “average monthly consumption of electricity is less than 10 degrees”, and define perennial idle farm buildings by the standard of “average daily consumption of electricity throughout the year is less than 0.2 degrees”, so as to analyze the situation of vacant farm buildings and idle homesteads in the Jilin Province. The group further conducted field surveys, using questionnaires and interviews to carry out research, and farmhouse homesteads that had been unused for two years or more were defined as perennial idle homestead; “Spring Festival return home”, “returning home in the agricultural season”, “avoiding cold in winter”, and other situations were defined as seasonal idle homesteads. Through interviews, we understood the status and willingness of transferring homesteads in the context of the implementation of the strategy of rural revitalization, the change of operation mode and use, the perception of the rights of the “three rights”, and the manifestation of property rights and interests of homesteads. On the basis of the above research, this study evaluates the idle rate of homesteads.

2.3.2. Multifunctional Evaluation of Homestead

(1)

Multifunctional evaluation system of homestead

In this paper, on the basis of the existing multifunctional evaluation research on homesteads (Qi Q, et al., 2021) [29,44,47,48,49,50], and by combining it with field surveys, the functions of homesteads are classified into four functions: living, production, assets, and security. The living function refers to the construction of dwellings on homesteads to provide places for the farmers to rest, live, and socialize in order to satisfy their demand for a place to live, the farmers of the land are guaranteed to enjoy the health care, old age, and the vill. Specifically, the existence of the living room, bedroom, kitchen, toilet, courtyard, and others can allow the farmers to meet guests, sleep, have meals, use the toilet, enjoy leisure activities, and solve other family life problems. The security function is that the homestead can protect the social welfare of the farmers under confirmation rights, maintaining the stability of rural society. With the implementation of the policy of the “Separation of Three Rights” of the homestead, the qualification right recognizes the membership of the collective economic organization of the farmers, so that the rights and interests of the collective are protected. Production functions are defined as the construction of ancillary buildings or as the vacation of vacant land on homesteads that can provide agricultural production or non-agricultural business premises for farmers to meet their material needs, which are mainly used for agricultural production and non-agricultural business. Among them, the agricultural production function is to reclaim the open space in front of and behind the house to develop planting activities, set up livestock and poultry sheds, build agricultural houses to develop breeding activities, or build warehouses to store food or production materials. The non-agricultural business attributes are embodied in the use of the homestead base to set up its own retail stores, agricultural music, lodgings, family workshops, and other forms of businesses, which make the homestead become a commercial house for engaging in commerce, services, and handicrafts. Asset functions are the potential value-added attributes of the homesteads and the residence on it as real estate, which can bring economic value to the farmers. With the deepening of the market economy, infrastructure construction and industrial development in the rural areas have driven changes in the way in which homesteads are utilized and in the main body of the right to use them, and farmers can obtain homestead cascade income or compensation through transfer, mortgage, compensated withdrawal, and cooperative housing construction, thus realizing the economic value of homesteads and promoting the value-added assets [51,52]. The study selects 12 evaluation indicators, as shown in

Table 1. Functional table of typical village homesteads.

Functional Category	Representational Attribute	Evaluation Indicators	Description of Indicators	Effect
Social function	Living function	Average household living space	Number of residential sites/number of households in the village	Positive
		Residential satisfaction	Level of resident satisfaction (1–5)	Positive
		Percentage of perennially unoccupied homesteads	Number of year-round unused homesteads/total number of homesteads in the village	Negative
		Per capita living area	Residential area/total number of people living in a household	Positive
		Average number of inhabitants	Number of inhabitants/number of homesteads	Positive
	Security function	Number of rural pension insurance participants	Number of participants in insurance/total number of households	Positive
		Residential uniqueness rate	Number of households with “one house for one family” on residential land/total number of households in the village (%)	Positive
		Number of rural health insurance participants	Number of participants in health insurance/total number of persons in the household	Positive
Economic function	Production function	Share of agricultural income	Agricultural income/annual net income of farm households	Positive
		Share of non-farm business income	Income from non-farm business on homestead/annual net income of farm household	Positive
	Asset function	Proportion of homestead land abandoned and collapsed	Number of abandoned and collapsed homesteads/total number of homesteads	Negative
		Share of space for transfer of homesteads	Transferred area/total area of homestead	Positive

, and uses the entropy weight method to calculate the comprehensive function index of homesteads.

(2)

Entropy weight method—advantageous function identification

The weights can measure the importance of different indicators for the function of the homestead, and this study used the entropy weight method to calculate the weights of the indicators. The main formulas are as follows.

Firstly, by using the extreme value method to standardize the index value of homestead function, the formula of positive and negative indexes was obtained:

$$y_{ij}={\displaystyle \frac{x_{ij}-Min\left(x_{ij}\right)}{Max\left(x_{ij}\right)-Min\left(x_{ij}\right)}}$$

(7)

$$y_{ij}={\displaystyle \frac{Max\left(x_{ij}\right)-x_{ij}}{Max\left(x_{ij}\right)-Min\left(x_{ij}\right)}}$$

(8)

where $y_{ij}$ ∈ [0, 1], $x_{ij}$ is the original value of the jth evaluation indicator of the ith function, and Max(${\mathrm{x}}_{\mathrm{i}\mathrm{j}})$ and Min(${\mathrm{x}}_{\mathrm{i}\mathrm{j}})$ are the maximum and minimum values of the jth evaluation indicator of the ith function, respectively.

The entropy weight method, which is the most widely used in this paper, calculates the indicator weights to reflect the amount of information contributed by the indicators by measuring the degree of dispersion of the difference information. The greater the degree of dispersion of the indicators, the smaller the information entropy, indicating that the smaller the amount of information contributed by the indicators, the smaller the weight.

$$p_{ij}={\displaystyle \frac{y_{ij}}{\sum _{i=1}^n{y}_{ij}}}$$

(9)

$$e_{ij}=-\mathrm{k}{\sum }_{i=1}^n(p_{ij}\mathit{ln}{p}_{ij}),{ e}_{ij}>0$$

(10)

$$\mathrm{k}={\displaystyle \frac{1}{\mathit{ln}n}}, k>0$$

(11)

$$d_{ij}=1-e_{ij}$$

(12)

$$w_{ij}={\displaystyle \frac{d_{ij}}{\sum _{i=1}^n{d}_{ij}}}$$

(13)

In Formulas (9)–(11), ${\mathrm{p}}_{\mathrm{j}\mathrm{i}}$ is the proportion of the function of the jth type of homestead under the jth index, ${\mathrm{e}}_{\mathrm{i}\mathrm{j}}$ is the information entropy of the jth index, ${\mathrm{d}}_{\mathrm{i}\mathrm{j}}$ is the redundancy of the information entropy of the jth index, and ${\mathrm{w}}_{\mathrm{i}\mathrm{j}}$ is the weight of the jth index.

Based on the standardized index value and its weights, we can calculate the score of each homestead function with the following formula:

$$A_i={\sum }_{j=1}^a{w}_{ij}{y}_{ij}$$

(14)

In Equation (14), ${\mathrm{A}}_{\mathrm{i}}$ is the score of the ith function under the percentage system, and a is the number of evaluation indicators under the ith function. The homestead function score is between 0 and 1, with the larger value representing the stronger function it reveals.

Finally, the multifunctional indices were weighted and summed to obtain a multifunctional composite index:

$$F=A_n\ast 0.384+A_j\ast 0.135+A_p\ast 0.189+A_k\ast 0.192$$

(15)

F is a multifunctional composite index with functional weights of 0.384, 0.135, 0.189, and 0.193 for living, security, production, and assets, respectively.

(3)

Coupling coordination degree model—interrelationships of multifunctionality

As the concept of coupling is extended and popularized, the magnitude of coupling can be used to measure the strength of the degree of interaction between systems. In this paper, the multifunctionality of the homestead was calculated:

$$\mathrm{C}=({{\displaystyle \frac{F\left(x\right)\times G\left(x\right)\times H\left(x\right)\times Y\left(x\right)}{{(\frac{F\left(x\right)+G\left(x\right)+H\left(x\right)+Y\left(x\right)}{4})}^4}})}^{{\displaystyle \frac{1}{4}}}$$

(16)

where C is the degree of coupling with values ranging from 0 to 1: the larger the value, the higher the coordination among the multifunctional systems of the homestead.

(4)

Village classification—transition type identification

In order to explore the transition path, the comprehensive degree and the coupling degree were utilized for classifying types of villages: F was the comprehensive degree, C was the degree of coupling, and the natural breakpoint method in ArgGiS was used to classify the comprehensive degree and coordination of homestead functions into three levels: high, medium, and low. The classification rules were: “low integration degree and medium-to-high coordination degree is priority, medium integration degree and medium coordination degree is potential, high integration degree and medium-to-high coordination degree is moderate”. These were divided into four types, which are: (I) moderate optimization category, (II) key improvement category, (III) collaborative optimization category, and (IV) potential improvement category (Figure 2).

3. Results

3.1. Characterization of Rural Residential Land Use

3.1.1. Status of Utilization

Based on the third national land survey data on homesteads and population data to calculate the per capita area of homesteads, the spatial distribution of per capita rural homesteads in the counties of the Jilin Province shows a pattern of high in the west and low in the east. The per capita homestead area ranged from 75.325 m² to 259.64 m², with more than 55% exceeding 100 m² of per capita homestead area. Due to the poor natural resource conditions in the western part of Jilin, a large number of rural populations have moved from the rural area to the cities, but the withdrawal of rural homestead is lagging behind, thus the per capita homestead area is higher. In the central region, the terrain is flat and suitable for crop cultivation, thus the total rural homestead area is large, but the per capita homestead area is relatively small due to the large rural population.

3.1.2. Situation of Unused Residential Sites

Based on the statistics related to the electricity consumption of farmhouses from 2019 to 2021, the vacancy rate, perennial vacancy rate, and seasonal vacancy rate of farmhouses in the Jilin Province were estimated at 21.08%, 18.66%, and 2.42%. From field surveys, the effective samples of the surveys covered all cities in the Jilin Province, involving 22,451 rural homesteads (4719, 7556, and 10,176 in the east, center, and west, respectively). According to the statistics of the survey results, the idle rate, perennial idle rate, and seasonal idle rate of rural residential land in the Jilin Province were found to be approximately 15.35%, 8.02%, and 7.33%, respectively. Moreover, by refining the utilization status of the east, middle, and west homestead, it was estimated that the idle rate of the east, middle, and west homestead was about 18.80%, 15.96%, and 13.30%, respectively. Regardless of the statistics performed on the electricity utilization data or field surveys, the vacancy rate of homesteads was always above 15%.

3.1.3. Human–Land Matching Degree

The Theil index ranges between 0 and 1; a smaller Theil index denotes a higher degree of human–land matching. A Theil index of zero indicates no regional disparities. In this study, the calculated Theil index values ranged from 0.056 to 0.363, suggesting an overall low level of inequality as measured by the Theil index. The Theil index (Figure 3) indicated that the rural population and rural residential land in the Jilin Province showed a high spatial matching degree, with small regional differences and, thus, no excessive concentrations or uneven distribution. Further decomposition of the total Theil index into intra-regional and inter-regional differences showed that, within the same region, differences in natural conditions, socio-economic development levels, and related policies tended to be smaller, and farmers’ production and lifestyles were more similar, thus the smaller the intra-regional difference, the larger the inter-regional difference. This suggests that the distribution of homesteads and the population in the Jilin Province is well-matched. From a spatial point of view, the Theil index in the eastern Jilin Province was relatively low (Figure 3), and the Theil index in the central Jilin Province was high.

3.2. Analysis of Homestead Multifunctional Evaluation Results

3.2.1. Results of Multifunctionality Index Measurements

The entropy weight method was utilized to measure the indexes of living function, security function, production function, asset function, and comprehensive function degree of typical villages, and it was then divided into three major segments of the Jilin Province: west, central, and east, which are shown in Figure 4.

The results of the functional index of homestead show that the score of the living function ranged from 0.198 to 0.835, the score of the production function ranged from 0.044 to 0.731, the score of the asset function ranged from 0.002 to 0.402, and the score of the social security function ranged from 0.01 to 0.763. As shown by our results, the index of the living function as a whole was much higher than the indexes of the other functions as a whole, indicating that the function of homestead in the Jilin Province continued to fulfill the basic living function. The overall indexes of the production function and asset function were small, indicating that the production function of a typical homestead did not play a strong role, and the asset function could not be revealed, showing a weak economic performance. Further analysis revealed that the maximum value of the four functions exceeded the mean value by three standard deviations, indicating that the values of large regional differences and the median should be used to characterize the overall level. Spatially, the overall function of homesteads in the Jilin Province was central > west > east. Within each region, the performance of the living function was central > east > west. The security function did not differ much between the western and central villages, and it was slightly stronger in the eastern villages. The production function was stronger in the central region, medium in the west, and weak in the east. With respect to the performance of the asset function, it was stronger in the eastern villages and did not differ much between the western and central regions.

3.2.2. Multifunctional Analysis

(1)

Analysis of coupling coordination degree (C) and comprehensive degree (F)

As it can be seen from

Table 2. Coupling coordination (C) and comprehensive degree (F) scores and classification.

	Maximum	Minimum	Mean	Median	Standard Deviation
Comprehensive degree (F)	0.444	0.129	0.242	0.224	0.079
coordination degree (C)	0.912	0.610	0.838	0.838	0.100

, the range of the composite degree (F) was between 0.129 and 0.444, with the lowest value of F being 0.129, which shows that some villages had a weak performance with respect to the function of the homestead. The highest value was 0.444, which is low and indicates that the integrated performance of the functions in typical villages was poor. The standard deviation of F was 0.079, which indicates that the value of F deviated little from the mean, and the mean could be used to characterize F. The range of the coupling concordance (C) was between 0.610 and 0.912, which indicates that the coupling degree of the four functions was better. The mean and the median of C were 0.838 each, which indicates that the distribution of C was uniform. From the scores of F and C, it can be seen that the combined scores of the four functions were low, but the coupling between them was high.

The typical village comprehensive degree (F) was imported into ArcGis and a trend surface analysis was performed to derive a trend in F.

As show in Figure 5, the x-axis points to the east, the y-axis points to the north, and the z-axis points to the attribute (the analyzed variable); the curve on the xz plane indicates the trend in the east–west direction, and the curve on the yz plane indicates the trend in the north–south direction. In the typical villages selected in the whole area of the Jilin Province, it can be seen that the east–west direction presented a micro “U” shape, indicating that the spatial distribution of the composite degree F was high in the east and low in the west, and the north–south direction of the Jilin Province presented a micro-arch distribution, with the score of F being highest in the central part of the country, and the function of the residence base performed best in the central part of the country. In the western part of Jilin, the east–west and north–south directions both showed a micro “U” shape distribution, and the integrated function of the residential land was better in the west and north. In the central region, the east–west direction showed a decreasing distribution, indicating that the villages in the east had a better performance of the function of homesteads, and the north–south direction showed a decreasing and then increasing distribution, indicating that the villages in the central region had a worse performance of the function of homesteads. In the east, the east–west direction showed a “U”-shaped distribution, with the villages in the central part of the comprehensive degree function of the home base exhibiting a poor performance, while the north–south direction showed an arch-shaped distribution, with central villages performing better in terms of comprehensive functions.

With regard to the classification of the comprehensive degree (F) and coupling degree (C), F ranged from 0.190 to 0.204 for low levels, containing 29 villages, where the west/central/east regions had 10, 4, and 15, respectively. It can be seen that there were more villages in the sample with low grades, the overall performance of homesteads was poorer, and villages in the eastern part of the Jilin Province accounted for a larger proportion of villages, with the largest percentage being in the central villages. F ranged from 0.207 to 0.281 for medium levels, containing 20 villages, where the west/central/east regions had 7, 10, and 3, respectively, with the highest percentage of villages in the center and the lowest in the west. F ranged from 0.299 to 0.444 for high levels, containing a total of 17 villages, where the west/central/east regions had 2 and 12. C values ranging from 0.610 to 0.733 were classified as low-level, with 2, 12, and 2 in the west/central/east regions, with the central villages having the highest proportion of villages in the lower range. C ranged from 0.762 to 0.870 for the medium level, with 9, 6, and 11 in the west/central/east regions, respectively; of these, the eastern villages accounted for the largest proportion. C ranged from 0.882 to 0.993 for the high level, with 8, 9, and 8 in the west/central/east regions, respectively; there was little variation in distribution in the west and central part.

3.2.3. Transition Village Type Identification

Based on the classification results of comprehensive and coupling degrees in Figure 6, this study categorized typical villages into transformation categories.

According to Figure 7, in the village sample, 18 villages were assigned to the moderate optimization (MO) category, with 6, 7, and 5 villages in the west/central/east regions, respectively, 10 villages were assigned to the key improvement (KI) category, with 2, 2, and 6 in the west/central/east regions, respectively, 19 villages were assigned to the collaborative optimization (CO) category, with 6, 6, and 7 in the west/central/east regions, respectively, and 19 villages were assigned to the potential improvement (PI) category, with 5, 11, and 3 in the west/central/east regions, respectively. The collaborative optimization category had the largest number of villages in the central part, the key improvement category had more villages in the western part, the moderate optimization category was most common in the central part, and the potential improvement category did not differ much between the western and eastern parts.

According to Figure 8, we can see the proportion of the four categories of villages in the western/central/eastern parts. In the western sample villages, the highest proportion of collaborative optimization villages was 0.333, the lowest proportion of potential improvement villages was 0.143, with moderate optimization and key improvement having similar proportions of 0.238 and 0.286. In the central sample villages, the highest proportion of moderate optimization and collaborative optimization was 0.316, and key improvement had a ratio of 0.105, with potential improvement having a ratio of 0.263. In the eastern sample villages, the highest proportion of potential improvement villages was 0.423, the proportion of moderate optimization villages was 0.269, which was the highest proportion of this type of villages in all regions, and the smallest proportion of key improvement villages was 0.0769, while the proportion of collaborative optimization villages was 0.231. It can be seen that the priority upgrading categories were concentrated in the eastern and western villages, with the largest share of potential upgrading categories in the central villages.

4. Discussion

4.1. Exploration of Transition Paths of Rural Homesteads

In order to achieve effective utilization of homesteads, it is necessary to consider the results of relevant measurements and the classification of zoning guided by the comprehensive degree and coupling of homestead functions. Considering dominant degrees of different types of villages, the following recommendations are made:

(1) For moderate optimization villages, this type of village has a high comprehensive degree of homestead functions and a high degree of coupling, indicating an excellent performance of homestead functions. For this type of villages that can be moderately optimized, and based on what the function indexes revealed, in addition to the living function, other functions have little difference, meaning it can be coordinated and optimized at the same time. Therefore, we suggest that the geographical location advantage of such a kind of villages can be used to expand the non-agricultural production and operation of homesteads, introduce management personnel, and create large-scale characteristic industries. It is essential to integrate local characteristic resources with emerging industries to continually enrich industrial development models. Under the premise of adhering to village planning and land-use regulations, farmers should be guided to relinquish idle homesteads and vacant houses. By means of local reutilization and adjusted reutilization, the economical and intensive use of rural land resources can be promoted. This approach provides land resource guarantees for developing new industries and business forms, such as agricultural product processing and rural tourism, that align with the village’s characteristics.

(2) For key improvement villages, such types of villages have a lower rural homestead comprehensive degree and a higher degree of coupling, accounting for the majority of village types. Therefore, we argue that it is necessary to further strengthen the construction of key villages, continuously optimize living environments, strengthen resource investment, raise the income of the rural population, and attract farmers to stay in the village. This region should prioritize leveraging the organizational and coordination capabilities of grassroots mass self-governing organizations, such as village collectives. Respecting residents’ wishes, efforts should be made to organize on-site repairs or relocations in areas where villagers’ houses are severely damaged. Additionally, traditional agricultural development methods should be transformed by deeply integrating them with rural tourism through initiatives like flower nurseries, pick-your-own farms, and experiential parks. This strategy promotes a coordinated development between the secondary and tertiary industries, actively cultivates rural characteristic industries, and achieves harmonious development among various functional domains.

(3) For collaborative optimization villages, which have a medium comprehensive degree of homestead functions and a high degree of coupling, resource inputs to the production, asset, and security functions should be increased to achieve the collaborative development of the three functions. It is necessary to protect the existing endowment advantages of villages and reasonably utilize natural and cultural resources to create characteristic industries and lead farmers to make a diverse use of homesteads to achieve the sustainable development of villages. This area needs to focus on addressing the housing renovation needs of rural residents in counties (cities, districts) and reasonably planning the spatial layout of rural agricultural and construction land. In suitable towns, the development of ecological and livable small towns should be pursued to meet rural residents’ aspirations for a better life. Concurrently, land consolidation should be intensified and idle homesteads revitalized, promoting homestead reclamation and land transfer to create favorable conditions for achieving industrial spatial agglomeration effects.

(4) For potential improvement villages, this type of villages has a medium comprehensive degree and a medium degree of coupling, indicating an excellent performance of homestead functions. Therefore, we believe it is possible to increase the resource input to production and asset functions with respect to function index to improve the village’s asset and production functions. The homesteads in this area possess a high potential for multifunctional enhancement. Firstly, improvements should be made to infrastructure such as roads and bridges, public service facilities including education and healthcare, and environmental protection facilities like public toilets, garbage disposal stations, and “three wastes” treatment plants to enhance residents’ living environments. Secondly, the productive potential of the land can be activated by transforming agricultural development methods, by developing new agricultural forms such as specialty agriculture and pick-your-own farms, and by promoting non-agricultural production through agricultural production by leveraging operating models like Rural Taobao. Leveraging excellent ecological conservation and rural landscapes can promote ecological and cultural tourism, accelerating the pace of ecological industrialization development.

4.2. Contributions to Research, Limitations, and Future Work

This paper comprehensively explores the connotation and identification methods of homestead multifunctionality, proposing rural homestead transition suggestions for different village types and exploring scientific utilization transition paths. However, the study has limitations that require further research. Firstly, due to the difficulties associated with the obtainment of historical data, the study only addresses issues related to one phase of homestead functionality, without an in-depth analysis of temporal changes. Secondly, there is a need to enrich the number and types of typical villages to make the research results more scientific. Future work should improve data acquisition methods to obtain more research subject information and enhance data methodologies.

5. Conclusions

The main conclusions of this study are as follows. In some areas of the Jilin Province, the utilization of homesteads is extensive and inefficient, with an overall high idle rate. However, the rural population and the homesteads show a high spatial matching degree without excessive concentrations or uneven distributions. The multifunctional measurement results of the typical villages indicate that the living function of rural homesteads currently outperforms other functions, with the functional performance being living function > production function > security function > asset function. Among the three major blocks of the Jilin Province, the functional performance of rural homesteads is best in the central region, followed by the west and, then, the east, where it is weakest. Based on the comprehensive and coupling degrees of rural homesteads, different village transformation types are identified, and specific transformation path suggestions are proposed for each type.