Analysis of Spatio-Temporal Evolution of Regional Settlements under the Background of Rapid Urbanization: A Case Study in Sishui County, China

Abstract

China’s urbanization has achieved rapid development in the past 20 years, with towns expanding in size and the population increasing, while rural society has also undergone dramatic changes. An in-depth study on the evolution process of rural settlements in the context of rapid urbanization is beneficial to the rational planning of villages and the promotion of green and sustainable urban development. Located in East China, Sishui County is in the transition area between three types of landforms: hills, plains, and mountains. The spatial distribution of rural settlements in the urbanization process shows obvious regional differences. To our best knowledge, research on the spatio-temporal evolution of regional settlements in Sishui County is rare. In this study, we chose Sishui County as the study area, utilized Landsat5 (TM) and Landsat8 (OLI) satellite data as remote sensing data sources, and applied Geographic Information System (GIS) spatial analysis methods, central place theory, and core–periphery theory to explore the evolution process for the pattern, scale, and structure of rural settlements in this region from 2000 to 2021 and to investigate the influencing factors. The results show that: (1) in terms of the evolution of the rural settlement pattern, its distribution shows a gradual increase in the degree of dispersion, which indicates an overall development trend in the region of Sishui County in recent years and that the trend is gradually increasing; (2) in terms of scale evolution, the degree and speed of expansion in rural settlements of Sishui County have gradually decreased, and the scale grade has gradually increased; (3) in terms of structural evolution, the hierarchy system in rural settlements of Sishui County is constantly being improved and optimized from a simple to a complex core–periphery structure. These results will provide data support for the rational planning of villages and sustainable, high-quality urban development. They will also help local governments take appropriate measures to achieve coordinated and sustainable socio-economic and environmental development in the region.

1. Introduction

Since the reform and opening-up, China’s urbanization has gained rapid development, with the urbanization rate increasing from 17.92% in 1978 to 64.72% in 2021, the scale of cities and towns expanding, the numbers in the urban population increasing, and the infrastructure improving. However, while urban society is constantly changing and economic forms are transforming, rural production, living, and ecological space have also changed to different degrees [1]. As the basic spatial unit for the production and life of the rural population and the external expression of rural economy and society [2,3], the spatial layout, scale, and structure of rural settlements have also changed. Under the influence of urban expansion, rural settlements close to towns and cities are gradually merged with towns and cities, and villages far away from towns and cities have intensified the phenomenon of rural hollowing out, mainly characterized by “ sparse population in rural areas, abandonment of arable land and wasteland, abandoned and idle house bases, and lack of motivation for industrial development “, which has even escalated to “rural disease” [4,5]. The rapid development of urbanization has accelerated the conversion process of rural residential land into urban construction land [6], and the excessive development not only destroys the ecological environment but also puts great pressure on the production and livelihood of farmers [7,8]. Therefore, during the process of rapid urbanization in China, the study of rural settlement development has become a hot topic of concern for academia and the government. It is of great practical significance to investigate spatial evolution patterns and influencing factors on rural settlements during the process of rapid urbanization in order to guide the rational planning and sustainable development of rural settlements and to promote the optimization of rural physical and spatial patterns as well as social and economic development. Many scholars at home and abroad have also conducted extensive research on this issue, mainly focusing on rural settlement location, scale, type and classification, spatial structure, evolutionary influencing factors and mechanisms, etc.

In the study of rural settlement morphology, rural settlement morphology represents the interaction between human settlements and the natural environment, as well as socio-political influences across time, and is the main focus of scholars’ research into the spatial evolution of rural settlements. Hill [9] classified the spatial distribution of rural settlements in southern Italy into six types: low-density, high-density, linear, clustered, regular, and random. Chibilev et al. [10] used Statistica 10 software for multidimensional statistical analysis and the municipal district of Orenburg Oblast as the study area, and they were able to distinguish seven types of rural settlement patterns by combining areas with five or more common characteristics. Wang et al. [11] used the Alpha Shape algorithm to extract the shape of a settlement, considering Longzhen in Shaanxi Province as an example, and classified the shape of the study area into five types: block rectangle and its variants, extended shape, dumbbell shape, beaded shape, banded rectangle and its combinations, and linear shape. In the study of rural settlement size, with the rapid progress of urbanization and acceleration in the spatial flow of populations, the spatial size of rural settlements has been changing to different degrees, and scholars at home and abroad have conducted extensive research on these changes. Sumana and Tapas [12] studied the spatio-temporal changes in rural settlements in Saranpur, West Bengal, India, from 2008 to 2018 using satellite images and GIS technology. They found that there was a significant expansion in rural settlement size in the study area during the decade. Chen [13] used frequency analysis and found that most rural settlements in Shandong province are medium to small in size. They also found that the clustering characteristics of the rural settlements show similar clustering when using Global Moran’s I analysis. Ji and Cha [14] used Danfeng County of Shangluo City as a study area and landscape pattern analysis to find that the number and density of rural settlements in Danfeng County decreased from 2010 to 2019, but the area increased and the degree of spatial expansion was obvious. In the study of rural settlement structure, the structure of rural settlements is a comprehensive reflection of the regional spatial distribution of rural settlements at a given level of economic development, and it is the outcome of the overall effect of rural socioeconomic and cultural activities. Zhang et al. [15] analyzed the differences in rural settlement structure in different regions of Liaoning Province using geometric morphological analysis and topological structure analysis, and their study provided suggestions for the development of rural areas in the future. Zheng [16] studied the spatial structure characteristics of rural settlements in nine counties (cities) of the Jianghan Plain region using typological methods and summarized two spatial structure patterns in the rural settlements in the study area: “star point” and “point axis”. In the study of influencing factors on the spatial evolution of rural settlements, settlement space is a concentrated expression of various human–land relationships in a certain area, and the evolution of space involves various factors such as natural, economic, cultural, and policy. Shahi et al. [17] studied the distribution of rural settlements in the High Himalayan region and found that it is mainly controlled by a combination of factors acting on both natural and cultural aspects. Shcherbina and Gorbenkova [18] used the Mogilev region of Belarus as a study area and by means of a systematic approach, a comparative approach, and cartographic modeling, a map of the settlement potential of the Mogilev region was produced and the factors influencing the development of rural settlements were explored. Zhao and Wang [19] found that agriculture, transportation infrastructure, local policies, and institutions, as well as the degree of urbanization, are the main driving forces affecting the spatial distribution of oasis rural settlements in Yutian County by constructing the evolutionary dynamics mechanism of oasis rural settlements in Yutian County. Lai et al. [20] used Banqiao town of Yongchuan district as an example and found that roads and water sources influenced the distribution of rural settlements by analyzing the scale changes in different distances between agricultural land and roads and rivers in different years. They also found that “road directionality” increased and the “water directionality” decreases.

In general, nowadays, most studies on rural settlements are based on the macroscopic perspective of social development and change, analyzing the spatial evolution characteristics of rural settlements, and deriving the spatial characteristics and evolution factors of rural settlements in different periods. However, there are fewer studies on the spatial evolution characteristics of rural settlements in the process of urbanization, and the study areas are mostly concentrated in areas with relatively unique natural conditions [21,22,23,24], relatively high levels of economic development [25,26], or more obvious ethnic characteristics [27,28,29,30]. Less attention is paid to the evolution of rural settlements in East China and transition areas of landscape types during the process of urbanization. Sishui County is located in the southern part of Shandong Province, China. The landform type in the county’s north and south is primarily hilly and mountainous with high terrain, while the center section of the county is plain with low terrain. The county is in the transition zone of three landform types: hilly, plain, and mountainous, and the spatial distribution of rural settlements shows obvious regional differences under the process of rapid urbanization. To our best knowledge, research on the spatio-temporal evolution of regional settlements in Sishui County is rare.

In this study, using Sishui County as an example, we consider urbanization as the main entry point to analyze the spatial evolution of rural settlements and use GIS spatial analysis methods, central place theory, and core–periphery theory to analyze the spatial layout, scale, structural evolution characteristics of rural settlements and influencing factors. Our results can provide the scientific basis for rational planning of villages and further promote green and sustainable urban development. A technological flow chart of this study is shown in Figure 1.

Our main contributions are summarized as follows. First, we use urbanization as an entry point to analyze the spatial evolution of rural settlements. Second, research on the spatio-temporal evolution of rural settlements in the process of urbanization is rare. Therefore, we chose Sishui County, which is located in East China and in the transition region of landform types, as the study area to help improve further research or work on the same topic.

2. Materials and Methods

2.1. Study Area

Sishui County is located in the eastern region of Jining City, Shandong Province, and is 46 km long from east to west and 40.6 km wide from north to south. The county has 13 towns and streets, namely Sihe Street, Jihe Street, Quanlin Town, Xingcun Town, Zhegou Town, Jinzhuang Town, Zhongce Town, Yangliu Town, Miaoguan Town, Sizhang Town, Shengshuiyu Town, Gaoyu Town, Huacun Town, with 586 administrative villages in the county. The scope of the study area is shown in Figure 2.

With population growth and rapid economic development, the level of urbanization in Sishui County has been rising. In 2021, Sishui County achieved a gross domestic product of CNY 20.33 billion, an increase of 8% year-on-year. As of April 2021, the household population of Sishui County was 646,591, the total resident population of the county was 553,400, and the urbanization rate of the resident population was 49.15%, which was 30.93 percentage points higher than the same period in 2000. During the process of rapid urbanization, the spatial distribution of rural settlements in Sishui County shows obvious regional differences, and thus an in-depth study on the evolution process for rural settlements in the context of rapid urbanization is beneficial to the rational planning of villages and the promotion of green and sustainable urban development.

2.2. Data Sources

The original data on remote sensing images were obtained from the geospatial data cloud website, and the Landsat 4-5 TM images in 2000 and 2010 and Landsat 8 OLi images in 2021 were downloaded from this website. We used the pre-processed images to extract rural settlement patches in Sishui County for subsequent analysis. The socio-economic data were obtained from the government of Sishui County website, the Statistical Yearbook of Sishui County (2000–2020), the Statistical Yearbook of Jining City (2000–2020), and the General Urban Plan of Sishui County (2011–2030). A workflow showing the data processing is shown in Figure 3.

2.3. Selection of Research Node

This is a study on the evolution of rural settlements under the background of rapid urbanization, so the determination of research time needs to consider the evolution process of urbanization. According to the statistical data on the urbanization rate collected from 2000 to 2021, the urbanization of Sishui County is divided into two stages, namely the early stage of urbanization development (2000–2010) and the middle stage of urbanization development (2011–2021). At the same time, in combination with the collection of social and economic development data, three time nodes were selected as time points to study the spatial evolution characteristics of rural settlements in this study.

(1)

In 2000, since the reform and opening-up, with continuous deepening of economic and social development and rural reform, the level of urbanization has been continuously increasing. The urbanization rate of Shandong Province in 2000 was 38.15%, which was higher than the urbanization rate of 36.22% in China, and the overall layout of rural urbanization was being completed in Sishui County. Therefore, 2000 was chosen as the 1st time point in this study.

(2)

In 2010, from 2000 to 2009, the average annual growth rate of urbanization in the province was 1.13 percentage points, maintaining a steady and rapid development momentum, and Sishui County was also vigorously implementing an urbanization catch-up strategy, with an urbanization rate of 30.55% in 2010. Therefore, 2010 was chosen as the second time point in this study.

(3)

In 2021, the urbanization rate of Jining City had stepped into the threshold of 60%, the urbanization rate of Sishui County was also increasing year by year, and the urbanization rate of Sishui County had increased by about 20% at this time compared with that in 2010. Therefore, the last study time point was chosen as 2021.

2.4. Methods

2.4.1. Kernel Density Estimation

Kernel density estimation is a nonparametric density estimation method that calculates the density of elements in their surrounding neighborhoods. In this study, a kernel density analysis of points is used to estimate the density of the spatial distribution of rural settlement settlements and to assess the distribution variation status of rural settlements within the spatial area. The kernel density estimation formula is as follows [31]:

$$\mathrm{f}\left(\mathrm{x},\mathrm{y}\right)=\frac{1}{{\mathrm{nh}}^2}{{\displaystyle \sum }}_{\mathrm{i}=1}^{\mathrm{n}}\mathrm{k}\left(\frac{{\mathrm{d}}_{\mathrm{i}}}{\mathrm{n}}\right)$$

(1)

where $\mathrm{f}\left(\mathrm{x},\mathrm{y}\right)$ is the density estimate located at position (x,y); n is the observed value; $\mathrm{h}$ is the bandwidth or smoothing parameter; $\mathrm{k}$ is the kernel function; and ${\mathrm{d}}_{\mathrm{i}}$ is the distance of position (x,y) from the ith observed position.

2.4.2. Average Nearest Neighbor Analysis

An average nearest neighbor analysis is used to investigate whether the spatial distribution of point elements belongs to an aggregation, dispersion, or random pattern [32]. In this study, a mean nearest neighbor analysis is used to estimate the distribution characteristics of rural settlements in each period.

The nearest neighbor index is calculated based on the average distance between each element and its nearest neighbor element and is the ratio of the average observed distance to the expected average distance. If the index is less than 1, the pattern exhibited is aggregation; if the index is greater than 1, the pattern exhibited tends to be discrete or competitive. The formula for the nearest neighbor index is as follows:

$$\mathrm{R}=\frac{\overline{{\mathrm{D}}_{\mathrm{o}}}}{\overline{{\mathrm{D}}_{\mathrm{e}}}} , \overline{{\mathrm{D}}_{\mathrm{o}}}=\frac{{{\displaystyle \sum }}_{\mathrm{i}=1}^{\mathrm{n}}{\mathrm{d}}_{\mathrm{i}}}{\mathrm{n}}, \overline{{\mathrm{D}}_{\mathrm{e}}}=\frac{0.5}{\sqrt{\mathrm{n}/\mathrm{A}}}$$

(2)

$$\mathrm{Z}=\frac{\overline{{\mathrm{D}}_{\mathrm{o}}}-\overline{{\mathrm{D}}_{\mathrm{e}}}}{\mathrm{SE}} , \mathrm{SE}=\frac{0.26136}{\sqrt{{\mathrm{n}}^2/\mathrm{A}}}$$

(3)

where $\overline{{\mathrm{D}}_{\mathrm{o}}}$ is the observed average distance between each element and its nearest neighboring element; $\overline{{\mathrm{D}}_{\mathrm{e}}}$ is the average proximity distance between elements in a random distribution model; ${\mathrm{d}}_{\mathrm{i}}$ is the distance between element i and its nearest neighboring element; n is the total number of elements; and A is the area of the smallest polygon that can wrap all elements. SE is the standard error, which is used to calculate the standardized z-value to measure the degree of clustering or dispersion in the spatial distribution of rural settlements [33].

2.4.3. Spatial Expansion Index

The spatial expansion index is used to characterize the extent of spatial expansion in rural settlement patches at different stages, including the intensity and speed of expansion. In this study, the spatial expansion index is used as an indicator to measure the intensity and speed of rural settlement expansion. The calculation formula is as follows [34]:

$$\mathrm{L}=\frac{{\mathrm{A}}_{\mathrm{s}}-{\mathrm{A}}_{\mathrm{o}}}{{\mathrm{A}}_{\mathrm{o}}}\times \frac{1}{\mathrm{T}}\times 100\%$$

(4)

$$\mathrm{R}=\frac{{\mathrm{A}}_{\mathrm{s}}-{\mathrm{A}}_{\mathrm{o}}}{\mathrm{T}}$$

(5)

where $\mathrm{L}$ indicates the degree of spatial expansion in the settlement. When $\mathrm{L}$ is positive, the larger the value, the larger the scale and stronger the degree of spatial expansion in the settlement; when $\mathrm{L}$ is negative, it indicates that the spatial scale of the settlement has changed from expansion to contraction. $\mathrm{R}$ refers to the expansion speed of the settlement space, and the unit is generally m²/y. ${\mathrm{A}}_{\mathrm{s}}$ is the sum of the areas of all rural settlement patches in the area at the end of a study time period; ${\mathrm{A}}_{\mathrm{o}}$ is the sum of the areas of all rural settlement patches in the area at the beginning of a study time period; and $\mathrm{T}$ is the length of the study time period.

2.4.4. Chris Taylor’s Central Place Theory

The central place theory was developed by Chris Taylor [35], who systematically clarified the number, scale, and distribution pattern of central places. According to Chris Taylor, there are three conditions or principles governing the formation of the central place system: market, transportation, and administrative. Under the different principles, the network of central places presents different structures, and the hierarchical order in the size of central places and market areas is strictly defined, i.e., arranged in a regular and tight series according to the so-called K values. According to the market principle, the center of the higher grade should be located in the center of the equilateral triangle formed by the three central places of the lower grade, which is most conducive to the competition between the center of the lower grade and the center of the higher level, thus forming a system of K = 3. Furthermore, there is a system of central places of K = 4, according to the transportation principle, and a system of central places of K = 7, according to the administrative principle [36]. The number and service area for each grade of central places is shown in

Table 1. The number of central locations and service areas under the market principle.

Center Grade	Number of Centers	Number of Service Areas	Service Radius/km	Service Scope/km2	Number of Types of Goods Offered	Population of the Center	Number of People in the Service Area
M	486	729	4.0	44	40	1000	3500
A	162	243	6.9	134	90	2000	11,000
K	54	81	12.0	400	180	4000	35,000
B	18	27	20.7	1200	330	10,000	100,000
G	6	9	36.0	3600	600	30,000	350,000
P	2	3	62.1	10,800	1000	100,000	1,000,000
L	1	1	108.0	32,400	2000	500,000	3,500,000
Total	729	——	——	——	——	——	——

Source: The Central Place Principle in Southern Germany, Christaller W, 1993.

.

Although it is difficult for settlements to present a perfect central ground hexagonal structure in real life, it provides a methodological guide for studying the changes in the spatial structure of settlements. This study analyzes the evolutionary characteristics of the rural settlement hierarchy in different periods with the help of the central place theory under the market principle of Chris Taylor.

2.4.5. Core–Periphery Theory

The core–periphery theory was proposed by the American geographer Friedman in 1966 [37]. He argued that the regional system of any country is composed of two sub-spatial systems, namely, the core and the periphery. When the spatial aggregation of certain regions forms a cumulative development trend, they will gain a much stronger competitive economic advantage than their peripheral regions and the core of the regional economic system. This theory is often used to describe the spatial formation of “core” and “peripheral” regions in space due to unbalanced development between urban and rural areas or between regions. However, the spatial distribution pattern of core–periphery may show different characteristics at different development stages. In this study, combined with the characteristics of social and economic development in the urbanization development stage of the study area, we use this theory to elaborate on the structural evolution characteristics of the settlement space in different development stages.

3. Results and Analysis

3.1. Analysis of the Spatial Pattern Evolution of Rural Settlements in Different Urbanization Stages

3.1.1. Evolution of the Spatial Distribution Pattern in Rural Settlements

Under the background of rapid urbanization, the basic pattern in the spatial distribution of rural settlements each year is shown in Figure 4. The spatial distribution characteristics are interpreted in combination with the average nearest neighbor index of rural settlement patches in Sishui County, as listed in

Table 2. Nearest neighbor index and related indicators.

	2000	2010	2021
Average observation distance (m)	914.347655	938.414940	1004.521879
Expected average distance (m)	858.488053	870.053085	897.704138
Nearest neighbor index (R)	1.065067	1.078572	1.118990
Z-Score	2.769473	3.289779	4.801988
p-Value	0.005615	0.001003	0.000002

Note: R > 1 indicates dispersion, R ≈ 1 indicates random, R < 1 indicates clustering; Z ≤ 1.645 indicates aggregated distribution, and Z > 1.645 indicates dispersion distribution.

. The average nearest neighbor index of rural settlement patches in Sishui County in 2000, 2010, and 2021 were 1.065067, 1.078572, and 1.118990, respectively, which were close to 1, and the Z-score was greater than 1.645, with a significant p-value. With the combination of the spatial distribution map showing rural settlements each year, it can be seen that the spatial distribution of rural settlements in Sishui County during this period showed the characteristics of a random distribution.

In general, since the rapid development of urbanization, the nearest neighbor index of Sishui County has been fluctuating around 1, and the spatial distribution of rural settlements shows a gradual increase in the degree of dispersion. These results indicate that Sishui County has shown an overall development trend in recent years, and the trend is gradually increasing.

3.1.2. Evolution of the Spatial Distribution Density of Rural Settlements

It can be seen from Figure 5 that the distribution density of villages in Sishui County mainly has the following characteristics:

(1)

The spatial distribution density of rural settlements in the three years shows that there is a high-density “core” concentration area in the spatial distribution of rural settlements.

(2)

Quanlin Town, Yangliu Town, and Sizhang Town had high-density clustering areas in 2000, 2010, and 2021. According to the Statistical Yearbook data for Sishui County, these three townships are rich in tourism resources and have better economic development compared with other townships.

However, with the improvement in the economic development level of the county, the space of its urban built-up areas has been expanding, and the surrounding villages have been merged into relevant streets, resulting in a slight decrease in the distribution density of rural settlements in the study area.

Figure 5. Spatial distribution density of rural settlements in Sishui County. (a–c) The spatial distribution density of rural settlements in 2000, 2010, and 2021, respectively.

Figure 5. Spatial distribution density of rural settlements in Sishui County. (a–c) The spatial distribution density of rural settlements in 2000, 2010, and 2021, respectively.

3.1.3. Evolution of Spatial Distribution Trends in Rural Settlements

In this study, the standard deviation ellipse tool was used to obtain the trend evolution characteristics for the spatial distribution of rural settlements, as shown in Figure 6, and the following characteristics were summarized based on the resultant plots:

(1)

The standard deviation ellipses for rural settlements in Sishui County in 2000, 2010, and 2021 show a “northwest-southeast” layout, which indicates that under the background of rapid urbanization, most of the rural settlements in Sishui County are concentrated in this area. The kernel density estimation map shows that the layout of the standard deviation ellipse for rural settlements in the four years coincides with the areas with higher kernel density concentration.

(2)

The fourth figure in Figure 4 shows that from 2000 to 2021, there is a slight change in the position of the standard deviation ellipse for the spatial distribution of rural settlements without any significant deviation, indicating that the trend in the distribution change in rural settlements is relatively stable during the process of urbanization development.

Figure 6. Standard deviational ellipses for Sishui County. (a–c) The standard deviational ellipse for 2000, 2010, and 2021, respectively. (d) Integration of the standard deviational ellipses for 2000, 2010, and 2021.

Figure 6. Standard deviational ellipses for Sishui County. (a–c) The standard deviational ellipse for 2000, 2010, and 2021, respectively. (d) Integration of the standard deviational ellipses for 2000, 2010, and 2021.

3.2. Analysis of the Spatial Scale Evolution of Rural Settlements in Different Urbanization Stages

3.2.1. Analysis of the Degree and Speed of Spatial Expansion in Rural Settlements

The spatial scale expansions in the three periods of 2000–2010, 2010–2021, and 2000–2021 are shown in Figure 7. Based on the spatial expansion index calculated using the formula in Section 2, the spatial expansion of settlements during these three periods was analyzed. Combined with Table 3 and Table 4, the characteristics of rural settlements expansion in Sishui County under the background of rapid urbanization development are summarized as follows:

(1)

Figure 7a shows that during the period of 2000–2010, the spatial expansion of rural settlements in Sishui County was relatively obvious, with a total expansion area of 29.41 km², and the spatial expansion speed and degree were 1.61% and 1,734,163.93 m²/y, respectively. During this stage, Sishui County gradually established and improved various systems and increased village planning and infrastructure construction, and the level of rural socio-economic development was gradually improved. Based on the above reasons, the scale of rural settlement space was expanding.

(2)

Figure 7b shows that the spatial scale of rural settlements also expanded to a certain extent during 2010–2021. Overall, there were two areas with greater expansion, namely Sihe and Jihe Streets. However, compared with the previous period, the degree of expansion decreased by 3.66%, and the overall degree and speed of expansion also reduced compared with the early stage of urbanization development. During this period, Sishui County enhanced its rural development capacity by building and developing the key Sihe and Jihe Streets. Together with the strong support from the state and the continuous introduction of policies related to the construction of new rural areas and beautiful villages, these enhancements will affect the expansion of rural settlement patches to a certain extent.

(3)

Figure 7c shows that the spatial scale of rural settlements was in the process of expansion from 2000 to 2021, with a total expansion area of 33.56 km2 during this period. The rapid development in urbanization, the improvement in the economic level, and the improvement in people’s living standards influenced the expansion of rural settlements to a certain extent.

Figure 7. Distribution of rural settlement expansion in Sishui County. (a–c) The distribution of rural settlement expansion from 2000 to 2010, 2010 to 2021, and 2000 to 2021, respectively.

Figure 7. Distribution of rural settlement expansion in Sishui County. (a–c) The distribution of rural settlement expansion from 2000 to 2010, 2010 to 2021, and 2000 to 2021, respectively.

Table 3. Spatial scale expansion indicators for rural settlements in Sishui County.

	2000–2010	2010–2021	2000–2021
Expansion min (m2)	133.653099	4.120967	15.716525
Expansion max (m2)	1,026,435.662530	1,291,495.148490	1,291,495.148490
Total expansion area (m2)	29,410,048.235714	21,421,137.290192	33,555,464.013499
Expansion average (m2)	62,707.991974	42,334.263419	65,538.015651
Standard deviation	118,515.892773	82,918.753050	99,934.271385

Table 3. Spatial scale expansion indicators for rural settlements in Sishui County.

	2000–2010	2010–2021	2000–2021
Expansion min (m2)	133.653099	4.120967	15.716525
Expansion max (m2)	1,026,435.662530	1,291,495.148490	1,291,495.148490
Total expansion area (m2)	29,410,048.235714	21,421,137.290192	33,555,464.013499
Expansion average (m2)	62,707.991974	42,334.263419	65,538.015651
Standard deviation	118,515.892773	82,918.753050	99,934.271385

Table 4. Spatial scale expansion index for rural settlements in Sishui County.

	2000–2010	2010–2021	2000–2021
Number of changes in colony patches (pcs)	−17	+38	+21
Length of time period (year)	10	11	21
Degree of spatial expansion (%)	1.61	−2.05	−0.48
Speed of spatial expansion (m2/y)	1,734,163.93	−2,563,275.89	−516,875.97

Table 4. Spatial scale expansion index for rural settlements in Sishui County.

	2000–2010	2010–2021	2000–2021
Number of changes in colony patches (pcs)	−17	+38	+21
Length of time period (year)	10	11	21
Degree of spatial expansion (%)	1.61	−2.05	−0.48
Speed of spatial expansion (m2/y)	1,734,163.93	−2,563,275.89	−516,875.97

3.2.2. Regional Analysis of the Spatial Expansion of Rural Settlements

Using the spatial hot spot detector analysis method, with the help of the local spatial pattern index (Getis-Ord Gi* index), we analyzed the regional changes in the spatial scale expansion of rural settlements in Sishui County during the urbanization process. We used the expansion area of rural settlements in Sishui County for two time periods from 2000 to 2010 and from 2010 to 2021 as the base data, and the results obtained are shown in Figure 8. The red area in the figure is the “hot spot area”, which means the concentrated area with a significant expansion of rural settlement patches, i.e., the Gi* index is positive; the blue area in the figure is the “cold spot area”, which means the concentrated area with a slight expansion of rural settlement patches, i.e., the Gi* index is negative [38]. Figure 6 shows that with the advancement of urbanization, the spatial scale concentration area of rural settlement patches in Sishui County has shifted from the town area to the urban area.

(1)

The early stage of urbanization development (2000–2010): At this stage, the expansion degree of rural settlement patches was large, the concentration was obvious, and the hot spots with strong rural settlement expansion were mainly concentrated in the town area, i.e., the present Yangliu Town, Zhegou Town, and Zhongce Town. There were also local concentration areas in Sizhang Town and Quanlin Town, while other areas had roughly the same degree of expansion.

(2)

The middle stage of urbanization development (2010–2021): The hot spots areas were mainly concentrated in Sihe Street and Jihe Street, while the overall expansion of rural settlement patches in other township areas was the same, and there were no obvious high-value and low-value aggregations

Figure 8. Distribution of hot and cold regions of rural settlement expansion in Sishui County. (a,b) The distribution of hot and cold regions of rural settlement expansion from 2000 to 2010 and 2010 to 2021, respectively.

Figure 8. Distribution of hot and cold regions of rural settlement expansion in Sishui County. (a,b) The distribution of hot and cold regions of rural settlement expansion from 2000 to 2010 and 2010 to 2021, respectively.

3.2.3. Evolution of the Grade Distribution at the Rural Settlement Scale

In order to study the change in the grade of rural settlement scale in Sishui County during the process of urbanization, using the area of rural settlements patches in Sishui County in 2021 as the benchmark, the rural settlement patches were divided into five scale grades using the natural breakpoint classification method, so as to analyze the evolution of the grade of rural settlement scale. Among them, the range of the first-grade settlement is from 808,933.31 to 2,457,766.31 m², the second-grade settlement is from 434,138.15 to 808,933.30 m², the third-grade settlement is from 240,182.98 to 434,138.14 m², the fourth-grade settlement is from 118,506.81 to 240,182.97 m², and the fifth-grade settlement is from 118,506.81 to 240,182.97 m². Figure 9 shows the grade distribution of the rural settlement scale in Sishui County.

As seen from Figure 9, the scale grades of rural settlements in Sishui County have different distribution characteristics at different stages during urbanization, and the scale grades of rural settlements are gradually enriched with the gradual progress of urbanization. The specific evolution characteristics for the grade of rural settlements scale are as follows:

(1)

The early stage of urbanization development (2000–2010): The number of low-grade scale settlement patches decreased slightly, while the number of second-grade scale settlement patches increased significantly, showing a uniform distribution throughout the whole area. The number of first-grade scale settlement patches also increased, mainly concentrated near the urban areas.

(2)

The middle stage of urbanization development (2010–2021): The number of low-grade scale rural settlements was relatively stable, with the third and fifth grades dominating. The number of high-grade scale rural settlement patches decreased slightly, with the number of first-grade scales changing significantly. At this time, the grade of the rural settlement scale in Sishui County was further improved.

Figure 9. Grade distribution of the rural settlement scale in Sishui County. (a–c) The grade distribution of the rural settlement scale in 2000, 2010, and 2021, respectively.

Figure 9. Grade distribution of the rural settlement scale in Sishui County. (a–c) The grade distribution of the rural settlement scale in 2000, 2010, and 2021, respectively.

3.3. Analysis of the Spatial Structure Evolution of Rural Settlements in Different Urbanization Stages

3.3.1. Evolution of the Center Hierarchy

During the process of rapid urbanization, the spatial structure of rural settlements is influenced by socio-economic development, and the hierarchy changes accordingly. The hierarchy of rural settlements is determined by the capacity to provide services for surrounding villages, and the service capacity is affected by factors such as markets, transportation, and policies. Different grades of villages have different service radii, so the evolution of the hierarchy in rural settlements is considered an evolutionary process of their spatial structure. This section is mainly based on the central place system under the market principle of Chris Taylor’s central place theory and analyzes the evolution process for the central place system of rural settlements during the process of urbanization. Due to the lack of data on the population size of rural settlements during each period, this section uses data on the total population and the total area of settlements at each research node (

Table 5. Population and area of rural settlements in Sishui County.

Year	Total Population	Total Area of the Settlement (m2)
2000	552,028	107,987,462.125077
2010	620,315	125,329,101.453992
2021	542,895	96,655,519.555506

) to deduce the size of each hierarchical central place in Sishui County during each period (Figure 10) by combining the relevant indicators for central place under the market principle [39]. The formula is as follows:

$${\mathrm{A}}_{\mathrm{n}} {=\mathrm{P}}_{\mathrm{n}}/\left({\mathrm{Y}}_{\mathrm{i}}{/\mathrm{S}}_{\mathrm{i}}\right)$$

(6)

where ${\mathrm{A}}_{\mathrm{n}}$ is the scale of an area in nth grade central place, ${\mathrm{P}}_{\mathrm{n}}$ is the standard population scale of the nth grade central place, ${\mathrm{Y}}_{\mathrm{i}}$ is the total population of Sishui County in year i, and ${\mathrm{S}}_{\mathrm{i}}$ is the total area of settlement patches in Sishui County in year i. As can be seen from Table 1, the regional population of Sishui County is between the service population of the G-grade and P-grade central regions. Based on the classification of the central regions according to the central region theory under the market principle, it is preliminarily estimated that there are six grades of the rural settlement center in Sishui County, namely, P-grade and below grade.

According to the division of grades for the center scale in

Table 6. Grade and scale data for the central place system of rural settlements in Sishui County.

Grade	Standard Population of Center	Population Number Served by the Center	Scale Grade of the Center
			2000	2010	2021
P-grade senior center town	100,000	1,000,000	19,561,953.76	20,204,106.2	17,803,722.55
G-class central town	30,000	350,000	5,868,586.128	6,061,231.861	5,341,116.766
B-class sub-center town	10,000	100,000	1,956,195.376	2,020,410.62	1,780,372.255
K-class central village	4000	35,000	782,378.1504	808,164.2482	712,148.9021
A-class sub-center village	2000	11,000	391,239.0752	404,082.1241	356,074.451
M-grade grassroots village	1000	3500	195,619.5376	202,041.062	178,037.2255

, a hierarchical system diagram showing the rural settlement center in Sishui County was obtained (Figure 11), and the hierarchy of the rural settlement center in 2000, 2010, and 2021 was visualized (Figure 12). The service area of each grade in the center are indicated with circles of different colors. According to Figure 10, it can be seen that the hierarchical system of rural settlements in Sishui County is an evolution process, and the number of low-grade central places is not exactly three times that of the number of high-grade central places. Therefore, during the rapid urbanization process, the evolution of the rural settlement central place hierarchy is not only influenced by market factors but also by economic, transportation, and policy factors, presenting a “pyramid” quantitative structure as a whole.

The specific evolution progress for the hierarchy system of rural settlement centers in Sishui County is as follows:

(1)

The early stage of urbanization development (2000–2010): According to the spatial layout of the hierarchy system of rural settlements in 2000, the hierarchical system of rural settlements in this period was dominated by low-grade centers. The two B-grade centers appeared in Zhegou and Quanlin Towns. Zhegou Town was vigorously promoting infrastructure construction during this stage. Related roads were built, and the private economy also developed rapidly, while enterprises in Quanlin Town and the villages had developed rapidly. National highway 327 ran from east to west, providing convenient transportation. Therefore, compared with other settlements, it has a strong supply and service capacity and gradually developed into a B-grade center. With the increase in population and economic development, the number of K-grade central places increased in 2010 compared with 2000, which were mainly concentrated near the river.

(2)

The middle stage of urbanization development (2010–2021): According to the spatial layout of the hierarchical system of the rural settlement center in 2010 and 2021, compared with 2010, the B-grade and K-grade centers decreased slightly, and the B-grade center in Quanlin Town disappeared and developed into two A-grade centers. During this stage, the economic level of the village gradually developed to a higher level, and the income of the villagers was relatively optimistic. Since 2019, the number of M-grade centers also decreased as Sishui County has carried out the work of “merging villages “, in which strong villages lead weak villages, rich villages lead poor villages, and large villages lead small villages. In addition, compared with the spatial layout hierarchical system of the rural settlement center in 2010 and 2021, the low-grade centers around the high-grade centers were more likely to evolve into high-grade centers.

3.3.2. Evolution of the Spatial Structure Distribution Pattern in Rural Settlements

Friedman’s core–periphery theory is used to explain the evolution of the spatial structure distribution pattern in rural settlements. As a specific space for economic and social development, rural settlements, along with the process of urbanization, will also present different core–periphery structural distribution patterns at different stages of development. Based on the core–periphery theory, the spatial structure of Sishui County in 2000, 2010, and 2021 was illustrated in ArcGIS using the results from the grade classification of rural settlement centers during each period, combining the influence of traffic and administrative factors. The relationship between the center of each grade and its adjacent centers is shown in Figure 13.

Figure 13 reveals that along with the rapid development of urbanization, the spatial structure distribution patterns of rural settlements in different stages of Sishui County are characterized as follows:

(1)

The early stage of urbanization (2000–2010): With the improvement in the economic level of rural settlements, the number of high-grade centers increased. Some low-grade centers also developed into higher-grade centers due to the advantages of opportunities. However, due to the limitations of natural conditions and their capacity, a simple core-periphery structure or a fan-shaped core-periphery structure was formed in the regional space. The spatial connection between regions was strengthened in 2010 compared with 2000.

(2)

The middle stage of urbanization (2010–2021): The economic development level and the hierarchical structure of rural settlements were further improved, and a core–periphery structure was formed between low-grade central areas and high-grade central areas. With the improvement in road traffic networks, the spatial connection between cross-administrative regions was strengthened, forming a complex semi-circular “core periphery” structure.

3.4. Analysis of the Spatial Structure Evolution of Rural Settlements during Different Urbanization Stages

Using FRAGSTATS software, the landscape shape index (LSI), perimeter area fractional dimension (PAFRAC), and patch area standard deviation (PASD) were selected to analyze the shape evolution characteristics of rural settlements in the research area.

LSI and PAFRAC can reflect the morphological characteristics of the patches themselves, and both were used to indicate the degree of regularity in the shape of rural settlement patches [40]. LSI is a comparison of the shape of rural settlement patches with equal area squares, and the larger the LSI, the more irregular the shape of the patches. The value of PAFRAC ranges from 1–2, and the closer a value is to 1 means the closer the patch shape is to simple circles or squares, i.e., the simpler the shape of the patch; conversely, the more complex the shape of the patch. PASD is used to describe the morphological characteristics of the whole rural settlement landscape, which can measure the dispersion of the patch area distribution in the study area [41]. A larger PASD indicates a larger gap between the scale of rural settlements and the average scale.

Table 7. Shape evolution indicators during each period.

Indicator	2000	2010	2021
LSI	25.7886	26.1025	27.4468
PAFRAC	1.2623	1.3065	1.2887
PASD	23.3281	33.0976	20.9148

shows that the LSI in the study area gradually increased during the three periods from 25.7886 in 2000 to 27.4468 in 2021. PAFRAC showed an expanding trend during 2000–2010, but it slightly decreased in 2021 compared with 2010, which indicates that the shape of rural settlements gradually tended to be more complex, and the boundary shape was more irregular. The PASD increased during 2000–2010 and decreased during 2010–2021, and in general, the difference in the patch area of settlements increased during the three periods.

3.5. Influencing Factors on the Spatial Evolution of Rural Settlements

Exploring the influence mechanism for the spatial evolution of rural settlements will not only help reveal the regularity in their development but also can provide reasonable and scientific suggestions for developing and planning rural settlements. During the process of urbanization, the most basic factor affecting the development of rural settlements is the natural environment, while economic development, roads, and related policies also have a certain influence on the formation, development, and evolution of rural settlements. This section will explore the influence of each factor on rural settlements in Sishui County from four aspects: nature, transportation, economy, and policy.

3.5.1. Natural Factors

Natural factors are the critical basic factors in the spatial evolution of rural settlements, and the evolution of rural settlements is closely related to the natural conditions around them. A superior geographical location and good topography will promote the evolution of rural settlements. For example, in plain areas, the terrain is relatively gentle, and the land is fertile. On the contrary, mountainous and hilly areas, with high terrain, have limited arable land and construction land that can be developed and used by people, and the quality of land is relatively poor, which greatly impacts on the development of rural settlements. An adequate water source is also an important guarantee for people’s daily life, so elevation and water system factors were selected to analyze their impact on rural settlements in Sishui County.

(1)

Elevation factor: The topography and geomorphology of Sishui County are relatively complex. The north and south regions are mostly low mountains with high terrain, and the central part is lowland with river valley plains. In combination with the actual topography of Sishui County, the elevation data of Sishui County was divided into five grades using the reclassification module in ArcGIS software, namely <100 m, 100–200 m, 200–300 m, 300–400 m, and >400 m. The distribution data for rural settlement patches in 2000, 2010, and 2021 in Sishui County were overlaid with its elevation classification vector map to obtain the number of areas and spatial distribution of rural settlements in different elevation ranges (Figure 14).

Table 8. Distribution of the area and number of rural settlements in different elevation ranges in Sishui County.

Elevation	Year	Area of Rural Settlements (m2)	Percentage of the Total Area of Rural Settlements (%)	Number of Patches	Percentage of the Total Number of Patches in Rural Settlements (%)
<100 m	2000	21,350,856.12	19.77	343	29.90
	2010	26,150,787.39	20.87	339	28.27
	2021	20,026,193.85	20.72	321	27.58
100–200 m	2000	75,136,234.78	69.58	650	56.67
	2010	86,520,367.83	69.03	697	58.13
	2021	67,917,992.19	70.27	679	58.33
200–300 m	2000	11,446,749.94	10.60	150	13.08
	2010	12,601,826.69	10.05	159	13.26
	2021	8,683,608.505	8.98	160	13.75
300–400 m	2000	53,621.28535	0.05	4	0.35
	2010	56,119.54678	0.04	4	0.33
	2021	23,000.28632	0.02	4	0.34

verifies some differences in the area and number of settlement sites in Sishui County within the interval of different elevation grades. During the period from 2000 to 2021, rural settlements were mainly distributed in the area with an elevation range of 100–200 m, the area proportion increased from 69.58% in 2000 to 70.27% in 2021, and the number of patches also expanded. The rural settlements below 100 m and 200–300 m in elevation accounted for a higher proportion, while the number of patches within the elevation range of 300–400 m was less, and the area gradually decreased with the increase in years.

In general, the area and number of rural settlements in Sishui County gradually decrease with the increase in elevation. This indicates that the flat terrain and fertile land in areas with low elevation are conducive to the expansion and development of rural settlements and the production and living of residents, while the higher elevation restricts the development of rural settlements to a certain extent.

(2)

Hydrographic factor: A water source is a basic condition for human survival and agricultural production. Therefore, the convenience of water becomes one of the conditions on which people choose their living places. The buffer zone analysis of rivers was performed in ArcGIS using the Multiple Ring Buffer, which was divided into five grades: 0–500 m, 500–1000 m, 1000–1500 m, 1500–2000 m, and >2000 m. The distribution data for rural settlement patches in 2000, 2010, and 2021 in Sishui County were overlaid with its hydrographic grading vector graph to obtain the area and spatial distribution of rural settlements in different distance ranges (Figure 15).

Figure 15 shows that the Sihe River runs through Sishui County, and there are many rivers, most of which run east–west. In

Table 9. Distribution of the area and number of rural settlements in Sishui County at different distances from the river.

Distance from River (m)	Year	Area (m2)	Percentage of Area (%)	Number of Patches	Percentage of Number (%)
0–500	2000	65,673,743.94	60.82%	355	42.72%
	2010	73,845,416.96	58.92%	353	41.63%
	2021	56,013,282.94	57.95%	372	42.42%
500–1000	2000	23,575,056.50	21.83%	270	32.49%
	2010	28,729,600.72	22.92%	283	33.37%
	2021	23,871,638.93	24.70%	283	32.27%
1000–1500	2000	10,122,571.22	9.37%	114	13.72%
	2010	12,173,394.00	9.71%	113	13.33%
	2021	9,633,624.24	9.97%	118	13.45%
1500–2000	2000	4,686,514.72	4.34%	61	7.34%
	2010	5,671,384.97	4.53%	68	8.02%
	2021	4,172,556.44	4.32%	71	8.10%
>2000	2000	3,929,575.75	3.64%	31	3.73%
	2010	4,909,304.81	3.92%	31	3.66%
	2021	2,959,953.15	3.06%	33	3.76%

, within the distance of 2000 m from the river, the area proportion is 96.89%, 96.08%, and 96.94% in 2000, 2010, and 2021, respectively, and the number proportion is 96.27%, 96.34%, and 96.24%, respectively. Rural settlements are mainly concentrated within the distance of 1000 m away from the river. In this buffer area, the topography is mainly plains with relatively flat terrain. The proximity to rivers makes it easy to obtain water resources, which promotes the expansion and development of rural settlements. With an increased distance to the river, the area and number of patches show a decreasing trend, which further indicates that the hydrographic factor has a certain influence on the pattern and development of rural settlements.

3.5.2. Traffic Factors

Roads are the basis for rural residents to communicate with the outside world, which is closely related to people’s production and life, and has a certain influence on the distribution pattern of rural settlements. Multiple Ring Buffer was used for the analysis with 200 m, 600 m, 1000 m, and 1400 m as the buffer radius, and the analysis results were overlaid with the vector data for rural settlement distribution in three phases in Sishui County to obtain the spatial distribution of rural settlements in different distance ranges (Figure 16).

Table 10. Distribution of the area and number of rural settlements in Sishui County at different distances from roads.

Distance from Road (m)	Year	Area (m2)	Percentage of Area (%)	Number of Patches	Percentage of Number (%)
0–200	2000	50,428,858.31	46.70%	353	34.68%
	2010	63,347,655.92	50.55%	343	34.47%
	2021	49,088,912.65	50.79%	374	36.24%
200–600	2000	37,425,457.99	34.66%	409	40.18%
	2010	39,573,998.77	31.58%	395	39.70%
	2021	30,862,141.50	31.93%	415	40.21%
600–1000	2000	13,940,802.11	12.91%	268	16.50%
	2010	15,104,618.49	12.05%	168	16.88%
	2021	11,446,712.08	11.84%	160	15.59%
1000–1400	2000	5,012,399.60	4.64%	71	6.97%
	2010	5,754,989.06	4.59%	71	7.14%
	2021	4,292,329.69	4.44%	68	6.59%
>1400	2000	1,179,944.11	1.09%	17	1.67%
	2010	1,547,839.22	1.24%	18	1.81%
	2021	960,959.80	0.99%	15	1.45%

shows that in the process of urbanization, the area and the number of rural settlements decreased as the distance to the road increased. Within 600 m distance from the road, the area and the number of rural settlement patches during the three phases in Sishui County reached a maximum value. In addition, in the 600 m buffer zone, the number of rural settlement patches increased in 2021 compared with 2000, while at the distance beyond 1000 m, the area, as well as the number of rural settlements, accounted for less, indicating that with the development of urbanization, the road factor had a certain influence on the distribution evolution of rural settlements in Sishui County.

3.5.3. Economic Factors

Under the background of rapid urbanization, the urbanization level of Sishui County increased from 18.23% in 2000 to 49.15% in 2021, and the GDP also exceeded the CNY 20 billion mark in 2021. At the same time, the industry near the countryside also emerged and developed rapidly. The rapid development in the economic level accelerated the speed of rural construction, affecting the layout and structure of the settlement space. With the continuous improvement in the economic level, Sishui County accelerated urban construction, adhered to the urban positioning of “landscape garden- ecological livable”, optimized the spatial layout, enriched the functional forms, constructed a beautiful home suitable for living and working, and gradually implemented the old neighborhood transformation, road construction, optimization of supporting public service facilities, etc. The improved quality of urban infrastructure attracted a largely rural population to buy houses and live in the county, impacting the population scale of rural settlements.

3.5.4. Policy Factors

After the proposal of “new rural construction” and “beautiful countryside construction”, all towns in Sishui County took active actions to strengthen the construction of rural infrastructure, accelerate the construction of communities in villages, promote the development of new rural areas, and create a number of provincial and municipal demonstration villages. At the same time, Sishui County vigorously implemented a rural revitalization strategy, accelerated the modernization of agriculture and rural areas, and effectively played a good role as the ballast of the “three rural.” In addition, the government promoted structural reform on the supply side of agriculture, adding 108 new agricultural business entities and 50,000 mu of new land transfer area. This not only promoted the development of agriculture and rural areas but also improved the happiness index of farmers, which in turn affected the development of rural settlements.

In recent years, the work of merging villages has been promoted rapidly, insisting that strong villages lead weak villages, rich villages lead poor villages, large villages lead small villages, and all villages with a population of fewer than 500 people should be merged in principle. In addition, villages with similar industrial characteristics and those that are driven by large projects should be integrated to achieve collective development, which will further affect the scale and structure of rural settlements.

4. Discussion

Nowadays, most studies on rural settlements are based on the macroscopic perspective of social development and change, analyzing spatial evolution characteristics and influencing factors of rural settlements. However, there are fewer studies on the spatial evolution characteristics of rural settlements during the process of urbanization, and the study areas are mostly concentrated in areas with relatively unique natural conditions [21,22,23,24], relatively high levels of economic development [25,26], or more obvious ethnic characteristics [27,28,29,30]. In this study, using urbanization as an entry point, we explore the evolution process for the pattern, scale, and structure of rural settlements from 2000 to 2021 in Sishui County, which is located in the southern part of Shandong Province, China. The main findings of this study are as follows: in terms of the evolution of the rural settlement pattern, its distribution shows a gradual increase in the degree of dispersion, which indicates that the overall development trend in the region in Sishui County during recent years was shown, and the trend is gradually increasing. In terms of scale evolution, the degree and speed of expansion in rural settlements in Sishui County have gradually decreased, and the scale grade has gradually increased. In terms of structural evolution, the hierarchy system of rural settlements in Sishui County is constantly being improved and optimized, from a simple to a complex core–periphery structure.

However, this study focuses on analyzing the spatial evolution of rural settlements during the process of urbanization from a global perspective, revealing the spatial evolution pattern in rural settlements in Sishui County, and did not explore in depth how to solve a series of spatial problems in rural settlements during the process of urbanization. Therefore, studying how to solve and optimize the spatial problems in rural settlements during the process of urbanization from the perspective of urbanization will be the next part of this study to continue to deepen.

5. Conclusions

This study discussed the evolution of rural settlements in Sishui County from 2000 to 2021. The conclusions are drawn as follows:

(1)

During the process of rapid urbanization, the spatial distribution of rural settlements in Sishui County showed the characteristics of a scattered distribution. At the early stage of urbanization development, the area was concentrated in Yangliu Town, Jinzhuang Town, Quanlin Town, and Jihe Street, and the overall distribution was relatively scattered. With the improvement in the county’s economic level, the space of its urban built-up area continuously expanded, merging the surrounding villages into the relevant streets, resulting in a slight decline in the distribution density of rural settlement in the area. During the process of urbanization development, the spatial distribution of rural settlements in Sishui County showed a process of gradually increasing dispersion, indicating that the overall development trend in the region in Sishui County during recent years was gradually strengthened.

(2)

With the rapid development of urbanization, the expansion degree and speed of rural settlements in Sishui County gradually decreased, and the scale grade was gradually enriched. During the early stage of urbanization development, the socio-economic level of the countryside gradually improved, so the degree of spatial expansion of rural settlements expanded. After entering the middle stage, the ability of Sishui County to drive rural development was enhanced, and the construction and development of the key streets of Sishui River and Jihe Street made the scale of rural settlement patches expand to a certain extent, but the speed decreased compared with that before. During the process of urbanization, the scale grade of rural settlements was gradually enriched, the number of low-grade settlement patches was relatively stable, and the number of high-grade settlement patches slightly reduced.

(3)

With the gradual promotion of urbanization, the hierarchical system of rural settlements in Sishui County is constantly being improved and optimized, and its spatial structure evolved from a simple local core–periphery structure or a fan-shaped core–periphery structure to a complex semi-ring-shaped core–periphery structure. During the early stage of urbanization, the level of rural socio-economic development gradually improved, and the hierarchical system of the central area also gradually improved, forming a local core–periphery structure or a fan-shaped core–periphery structure. With the development of urbanization, in the middle stage, along with the improvement in the road traffic network, the spatial connection between cross-administrative regions was strengthened, forming a complex semi-ring-shaped core–periphery structure.

(4)

Under the background of rapid urbanization, the rural settlement space in Sishui County was mainly influenced by the natural environment, transportation, economic development, and policy factors. With the development of urbanization, the change in the natural environment, the improvement in the road traffic network, the progress of the economic level, and the introduction of corresponding policies will have a certain influence on the layout, scale, and structure of rural settlement space.

These results can provide data support for the rational planning of villages and sustainable and high-quality urban development. They can also help local governments take appropriate measures to achieve coordinated and sustainable socio-economic and environmental development in the region.